HK1075190B

HK1075190B - Passive physiological monitoring (p2m) system

Info

Publication number: HK1075190B
Application number: HK05107541.4A
Authority: HK
Inventors: P．K．沙利文; K．C．K．张; C．J．沙利文; P．伯南布哥怀斯
Original assignee: 赫艾纳医疗公司
Filing date: 2002-03-25
Publication date: 2010-04-09

Description

Passive physiological monitoring (P2M) system

Background

After the soldier is damaged, the time for transporting the soldier to a medical care institution of a proper grade is very necessary to be reduced as much as possible, so that the wounded soldier can be ensured to be treated in time, and the timely treatment is very important for the survival of the wounded soldier. During this time, aeronautical medical care in the rescue helicopter environment is often used to identify and transport the victim.

Whether in the war or peace period, routine aerial medical procedures (aeronautical interventions) are performed by military units, which expose patients and flight/medical personnel to noise or environmental stress and harsh monitoring conditions. As in the civilian community, military nurses provide accurate patient monitoring in a variety of environments based on reliable and effective monitoring equipment, some of which are hostile and reckless to the use of traditional monitoring equipment. Although aeronautical medical escort is a life-saving process for most people, it is almost impossible for medical personnel to monitor vital signs in high noise environments.

In general, vital signs monitoring is only a simple routine procedure involving the collection of pulse, respiration and blood pressure data. These parameters can be easily determined in a relatively quiet environment. However, acquiring physiological signals of interest in a helicopter environment is a challenging problem for several reasons. Limitations on vital sign collection include high noise, vibration, audible interference, ineffective monitoring equipment, cramped operating conditions, bulky equipment during airborne escorts, and electromagnetic interference with aircraft systems caused by some medical equipment. The additional complexity of the leads and electrodes is compounded by noise and environmental concerns. The physiological parameters of the vital signs are in the frequency range generated by the helicopter. Also at these frequencies, helicopter frequencies have more power. Vibration and acoustic artifacts are also significant problems. Therefore, the signal-to-noise ratio problem must be solved in other ways than by low-pass and high-pass filtering methods. Due to the limitations of the working conditions, medical staff cannot accurately monitor heart activity or blood pressure using a stethoscope.

Military medical systems require portable, non-invasive devices that can monitor soldier vital signs in a field environment in less than ideal environments. The system needs to be useful for military medical personnel throughout the range of care distribution, such as in mass casualty conditions, aeronautical medical convoys, ground casualty convoys, hospital care, and intensive care units. Recent studies have found that thirty-two percent of the avionics equipment flown with a rotary wing ambulance aircraft fail at least one environmental test.

Quartz crystals are a mineral that generates an electric field when pressure is applied, i.e. has a piezoelectric effect. Materials scientists have discovered other materials with piezoelectric properties. The versatility and potential use of piezoelectric materials is known, but sometimes cost prohibitive.

However, the recent decline in manufacturing costs now allows engineers and researchers greater application. The superior quality of piezoelectric materials has found applications in medical, security, acoustics, defense, geological and other fields. The development of the application of piezoelectric materials is still in its infancy.

Medical practice and research applications based on piezoelectric instruments are now emerging. Piezoelectric methods have been successfully used for plethysmography, blood pressure monitors using piezoelectric contact microphones, heart rate monitoring of avian embryos and artificially hatched fry/birds, and various piezoelectric probes. Piezoelectric materials are used as detectors for sensing motion to determine human tremor, small animal body motion in response to pharmacological manipulation, respiratory motion for Nuclear Magnetic Resonance (NMR) animal testing. In combination with ultrasound, piezoelectric methods have been used to assess the hemodynamic properties of coronary arteries, the elasticity tensor, the image within the artery, and the receptor field dimension (receptor field dimension). In addition, piezoelectric sensors have been attached to the chest wall and used with automated auscultation equipment and a microcomputer for lung sound analysis. Piezoelectric films (piezo electric film) have been applied and studied to measure joint contact pressure, while piezoelectric discs have been used to record muscle sounds and qualitative monitoring of neuromuscular mass.

Stochastic fluctuation theory is commonly used in marine engineering to analyze pseudo-periodic phenomena, but can also be used to show spectral peaks of respiration and heart rate. The heartbeat, respiration, and blood pressure of a person are repetitive in nature, reflecting complex mechanical-acoustic events. However, various problems in the development of piezoelectric instruments have prevented their full implementation. The measurement of human tremor can only be successfully performed when the environment is absolutely silent. In fact, in most hospital rooms, there is often external noise such as equipment, fans, human speech, and the patient's own voice. Those noises mask and distort the signal of interest, thus limiting the usefulness of the piezoelectric instrument. In experimental animal studies, animal noise makes data collection difficult. In non-laboratory environments, medical applications of piezoelectric instruments for use in the human body still present problems due to their inherent signal-to-noise problems.

One of the main tasks of military nurses is to ensure that the sick and wounded soldiers are timely cared and/or escorted to the designated medical care facility. Performing appropriate medical treatment activities during the time period between battlefield injury and wounded transport is critical to the welfare of soldiers and may be other than life and death. The period when the diagnosis and treatment start and convoying (e.g. by rescue helicopters) take place is a critical time.

Unfortunately, the extremely large noise and vibration inherent in the helicopter environment prevents nurses and medical staff from being able to accurately measure vital signs. Not only does the electronic medical monitor become ineffective due to the intense vibration; but also the conventional method of measuring pulse and blood pressure using a stethoscope becomes unreliable under high noise. Tight operating conditions and bulky equipment during aerial escort magnify these problems.

Most conventional methods employ devices that use electrodes, leads, wires, and a wrap (wrapped cuff) to measure one or more vital signs, such as a sphygmomanometer, an ECG monitor, a pulse oximeter. Existing monitors require some accessories and are therefore not passive or passive. Furthermore, conventional devices are highly sensitive to noise, such as the noise of the engines and impellers of helicopters or airplanes.

It is clear that this common situation requires a monitor which can measure vital signs consistently and accurately during medical interventions with high noise and vibration. The monitors are relatively autonomous and intervention by a nurse or technician is not necessary. With the increased capabilities of telemetry for remote monitoring and communication, information can be delivered in real time via wireless communication to the location of medical and other care-givers.

There is a need to develop better methods and devices for physiological monitoring.

Disclosure of Invention

The invention is called passive physiological monitoring, P²M or simply P2M. A data record with a large amount of information (e.g., blood pressure) is measured, recorded, and can then be delineated to determine the physical state of the monitoring subject.

Recent developments in material science and data processing have created the possibility of new monitoring devices utilizing piezoelectric films, electroactive fluoropolymers. Although medical applications of piezoelectric films are still in the first stage, testing of medical devices is promising.

The cardiovascular system is modeled as tubing, pumps and other accessories using an engineering phenomenon known as "water hammer" as the basis for a working model of data analysis in blood pressure calculations.

The "water hammer" is a compression wave that propagates through the network of pipes and valves that supply and drain water to and from the home when the water is suddenly cut off. The result is a noticeable sound and damage to the plumbing system. Sudden speed changes cause an increase in the pipe pressure and thus water hammer, which typically occurs after water is cut off during valve closure. The compressional wave is described as follows:

c＝(1/ρ)*(dP/dV) (1)

where c is the velocity of the compression wave (ft/sec);

dV is the change in speed (V)_initial-V_final)；

ρ ═ fluid density; and

dP is the change in pressure.

Skalak (1966) developed a theory using the theory of linearization of viscous flow that can be used to understand the dominant waveform characteristics in arteries and veins. The vascular system is equivalent to a network of non-uniform transmission lines.

Prior to Skala's theory, womersley (1957) has applied those principles to a single uniform tube representing an arterial segment and compared the results to experimental data extracted on dogs. There is good agreement between the measured flow and the flow calculated from the measured pressure gradient.

Anliker (1968) indicates that scattering phenomena associated with intravascular wave propagation are a potential measure of vascular and other cardiac parameter distribution (disturbance). Anliker assumes that the vessel behaves like a thin-walled cylindrical shell filled with a non-viscous compressible fluid. A more complete model already provides good consistency.

Karr (1982) studied the velocity of pressure waves in humans and developed a method of determining the velocity of pulse propagation. The invention recognizes that this information may be used to determine platelet aggregation, cholesterol accumulation, and arterial wall thickness in the arterial wall.

Equation (1) can determine the pressure change (dP) from the heart pulse according to the dispersion relation between the pulse wave propagation velocity (c) and the flow velocity (v). The method of Karr measures flow velocity to determine dP in relation to systolic (pS) and diastolic (pD) pressures.

The new invention measures pressure energy based on heartbeat and respiration together. The effect of the heart on the energy spectrum can be determined by removing the effect of respiration in the energy spectrum. By comparing the calculation of the velocity energy spectrum with velocity measurements obtained by electromagnetic and doppler methods, the breathing energy can be filtered out. Since sympathetic tone (sympathic tone) can affect the accuracy of blood pressure measurements, a new monitor can be designed with one of its piezoelectric sensors serving as a dedicated doppler sensor that utilizes ultrasound to adjust the interpretation of data related to the patient's sympathetic tone. The selective omission of the P2M signal and selective comparison of the P2M sensor data with data from other parts of the body, as well as comparison between two or more simultaneously triggered sensors, separates the energetic effects of the heart. The P2M energy spectrum determined from the foot is different from the energy spectrum derived from the chest, which provides a method of separating cardiac energy when the foot energy spectrum is substantially free of energy from breathing.

Once the velocity (v) is known, the relationship between systolic and diastolic blood pressure (2) and bernoulli's equation (3) is used to measure blood pressure. The bernoulli equation is a fundamental fluid-dynamic relationship derived from newton's dynamics and the law of conservation of energy. A more compressed version of the same equation can be derived to reflect the more complex unsteady flow.

p＝pD+(1/3)*(pS+pD) (2)

Wherein

pst — systolic blood pressure;

pD is diastolic pressure; and

p is the average pressure.

p＝ρgh+(1/2)*p*V² (3)

Wherein

Where p is the density of the fluid,

g is a gravitational constant, and

h is height, the main energy term (head energy term).

From these equations, we can derive expressions for pD and pS, both of which are functions of pulse wave propagation velocity (c), flow velocity (v), and pulse wave pressure (dP):

pD＝(1/2)*ρ*v²-ρ*C*dV (4)

pS＝pD+ρ*C*dV (5)

P2M is well suited to assist medical personnel in several areas including, but not limited to:

(1) medical monitoring of vital signs of a heavy victim in a noisy and vibrating environment such as a rescue helicopter, where current monitoring techniques are very cumbersome or impossible;

(2) monitoring wounded persons due to serious disasters such as aviation accidents, earthquakes and floods;

(3) physiological monitoring of a large number of patients by the use of "smart stretchers" that are readily available to medical personnel on-site;

(4) continuous military hospital bed monitoring without disturbing the patient; and

(5) patient monitoring when processing is delayed due to temporary overloading of the medical device.

The development of P2M or passive sensor arrays (multi-sensor systems) is a significant innovation in passive monitoring. By using a grid of passive sensors, noise from correlated signals from different pads (pads) is reduced to identify noise from the bio-signal. This is very important in high noise environments. In addition, the importance of passive multi-sensor systems is that it provides the opportunity to monitor patients more comprehensively. As a tool, passive sensor grids provide an innovative approach to monitoring patients under adverse environmental conditions. The system provides a means by which various parameters other than blood pressure, heart rate, and respiration can be measured. These parameters include, but are not limited to, patient movement and sleep habits, pulse intensity on different parts of the body, relative blood flow, and cardiac output, among others.

The passive physiology (P)²M) the main components of the system being passiveSensors, hardware for amplification, filters, data-acquisition and signal-analysis software. In a preferred embodiment, the single passive sensor has dimensions of 20 cm x 25 cm, preferably enclosed within a protective cover. The leads from the sensor are connected to electronics (amplifiers, filters, data-acquisition card, desktop computer), where the raw analog voltage signal is filtered and amplified and converted to digital form. Digital filtering and software operation of the data is then performed in the form of frequency analysis. Finally, signal processing techniques are utilized to extract physiological information from the digital signal.

Preferably, the sensor pad is located directly under the back of a patient lying supine on the ambulance stretcher. The mechanical/acoustic signals generated by cardiopulmonary function are transmitted via the body to a passive transducer, which converts the signals into analog voltages. An example of a prior art P2M device is shown in fig. 6. The main hardware used in laboratory equipment is: a desktop computer, a multi-function programmable charge amplifier, and a roll-around rack (rack) that surrounds the rack to package all hardware. To maintain the versatility of the initial research and development, most devices choose to improve functionality at the expense of space efficiency.

It is an object of the present invention to provide the military medical community with an inexpensive, non-limiting, portable, lightweight, accurate and reliable device that can be used on-site or in a stationary setting to provide accurate measurements of heart rate, respiration and blood pressure in high noise and vibration environments to improve medical care in mass casualty situations, aeronautical medical care and hospital settings.

It is an object of the present invention to condition signal noise to allow utilization of piezoelectric instruments in patient ambulance transport, hospital bed monitoring, and other applications in military and civilian medical environments.

It is an object of the present invention to develop experimental physiological monitors using piezoelectric films in different field environments. Variations in accuracy, precision, user characteristics, and patient comfort determine the value of the field instrument to collect vital sign data.

It is an object of the present invention to provide a non-invasive means of monitoring vital function without employing electrical leads or wires on the patient. Heart rate, respiration and blood pressure are determined by using acoustic and electromagnetic signals of the human body.

These and further and other objects and features of the invention will be apparent in the disclosure, which includes the above and ongoing written specification, as well as the claims and drawings.

Drawings

Fig. 1 is a schematic diagram of the components of a P2M system.

Fig. 2 is a perspective view of the P2M system.

FIG. 3 is a graphical comparison of the results of the P2M bench test and human evaluation measurements.

Fig. 4 is a front view of the faceplate screen and user interface of the P2M system in acquisition mode.

Fig. 5 is a front view of the front panel screen of the P2M system in monitor mode.

Fig. 6 is a schematic diagram of a preferred embodiment of the P2M sensor.

Fig. 7 shows a Graphical User Interface (GUI) of the P2M system.

Fig. 8 shows a graphical user interface of the P2M system, which is displaying a time series and frequency domain representation of physiological data.

Fig. 9 shows the measurement of Pulse Wave Transit Time (PWTT).

Fig. 10 shows the system test and evaluation results in one diagram.

FIG. 11 is a high noise and vibration test at a Wheeler military airport (Wheeler Army Air Field).

Fig. 12 shows the measurement through body armor.

Fig. 13 shows a test of determining a poison proof attitude suit (MOPP gear) combination through body armor and military.

Fig. 14 shows a schematic of a passive physiological monitor (P2M) system utilizing a passive sensor array and microelectronics incorporated into a rescue stretcher.

Detailed Description

The preferred P2M system is a monitoring device with two major subsystems, one for measuring signals and the other for processing data into meaningful information.

Fig. 1 shows a schematic view of the system, while fig. 2 shows a perspective view of the system. First, the piezoelectric film, an electroactive fluoropolymer, converts mechanical energy, such as motion caused by the heartbeat, into voltage measurements that can support time series analysis techniques. The voltage is then recorded and analyzed by a microcomputer control system, which is done to distinguish the signal from background noise and display it on a screen or print out. Techniques such as preamplification and preadjustment using high-pass and low-pass filters reduce noise.

The piezoelectric material 1 used is a polymer polyvinylidene fluoride (PVDF) which can be formed into cables, films or thick tiles. PVDF piezoelectric films are environmentally strong, lightweight, flexible, inherently strong, durable, easily patched, and can be over-sized or disassembled for shipment. Since the material is inert, it can be used in the human body. Ultraviolet radiation passes harmlessly through PVDF films made at different thicknesses. In addition, the piezoelectric film is waterproof, can work between 0 and 145 ℃, and can not tear under the stress state. The PVDF can convert the temperature reading to an electrical output. The PVDF membrane is incorporated into a fluid-filled vinyl pad, with a surface area of approximately 10cm x 10 cm. The pad is located at different positions above/below/above the patient.

P2M measures cardiac and respiratory motion and monitors pulse, respiration and apnea respiratory event 3. Cardiac and respiratory motion are recorded simultaneously by selective filtering of the raw signal. The piezoelectric element 1 is a pressure sensing detector that functions as a highly sensitive strain gauge providing high dynamic range and linearity. The analog signal is transmitted to the amplifier (x 200-x 5000)5 via a band-pass filter and is visually displayed. The analog acoustic signal is converted into a digital value by means of a multichannel converter 7 with a sampling frequency exceeding 5 kHz. The data is converted to the frequency domain using a Fast Fourier Transform (FFT). The system uses a microcomputer 9 to record, analyze and represent data so that online evaluation and real-time determination of data can be performed.

In its simplest mode of operation, the PVDF piezoelectric film 1 is used as a piezoelectric strain gauge. This voltage output is up to four orders of magnitude higher than the output produced by the unamplified signal from the circuit used in the resistive wire approach. Both linearity and frequency response are good. Although similar to existing strain gauges, no current needs to be applied since the device is self-generating. Unlike the strain gauge, the present invention does not generate an infinite increase in charge with sustained stress. The slowest frequency measured for the polymer film is one kilo-second for an electrical event and up to one gigahertz (microwave). The piezoelectric film is passive and biologically safe, as opposed to conventional strain gauges that require an applied current.

PVDF sheets are mass produced finished products (COTS) with the type and specifications selected for optimum sensitivity range and flexibility. Each board contains seven feet of additional shielded twisted pair (for noise suppression) leads 11 to carry the charge generated by the board.

The piezoelectric plate 1 is located under the chest and feet of the patient, or at the same distance from the body, or can be placed on the body as a wrap. The pressure variations imposed by the patient's breathing and heartbeat cause the piezoelectric film to generate a voltage which is transmitted through a radio frequency filter 13 via a nonmagnetic micro coaxial cable 11. The signal is then passed to a high input impedance amplifier 5 and a computer system 7 for data processing. Conventional oscilloscopes and chart recorders display this output. The respiration and heart rate 15 are then calculated from the energy spectrum from the time-series data.

Several techniques can reduce noise and vibration interference. Active Cancellation (Active Cancellation) employs two piezoelectric sensors, one of which is not in contact with the body. The sensor that is not attached to the body is exposed to ambient acoustic and vibratory signals while the sensor that is attached to the body is exposed to ambient and body signals. Subtracting one output from the other output yields the body signal of interest.

Another preferred noise reduction technique includes a band pass filter/band reject filter. Band-pass or band-stop filters remove external signals from the total signal by identifying the external electronic or acoustic noise and its particular frequency.

In addition, signal processing techniques utilizing prior knowledge of the desired signal extract the desired information from the piezoelectric signal. Spectral techniques help identify the frequency and amplitude of events of interest and distinguish them from external noise.

The cardiac activity analysis uses a band pass frequency limit of 0.1-4.0Hz, while the respiration analysis uses a frequency limit of from 0.01-3.0 Hz. The filtered cardiac and respiratory signals are supplied to a recording system. Body motion can be analyzed by band-pass filtering the raw signal at the frequency limit of 0.1-20 Hz.

Once the signal generated by the film sensor becomes a voltage, amplified and filtered, it is processed by the P2M instrument. Including, but not limited to, a 586 processor computer 9 with enhanced RAM and disk capacity capable of processing large amounts of data. A patch panel (board) with an audio range facilitates data acquisition, signal pre-processing and signal processing.

For system operation, the main program 17 combines three separate software modules for data acquisition/control, signal processing/analysis, and data display/user interface. All three subroutines use LabVIEW^TM"G" graphical programming language. The analog voltage signal is digitized and analyzed in the time and frequency domains. Programs developed for signal preprocessing and analysis include digital filtering, spectral analysis, autocorrelation, and noise suppression programs. The data can be displayed in real time in a monitoring mode or an acquisition mode. When a new data update is made, the monitor mode displays the current data and discards the old readings, while the acquisition mode saves the data for later analysis. In the acquisition mode, the data volume cannot exceed the hard disk storage capacity of the computer.

As shown in fig. 2, for protection and ease of transport, the entire P2M system 19 is enclosed in a metal process cabinet 21 with casters (not shown) and locking glass doors (not shown). The device further comprises a rescue stretcher 23 fitted with sensors. The device may be incorporated into a stretcher so that no patient attachment is required, or may be miniaturized as a portable field device in a pocket with wireless communication means.

To verify the availability and accuracy of the P2M system, effective field and analytical tests were conducted. The piezoelectric film measures mechanical, thermal, and acoustic signals. In order to non-invasively measure vital signals, high sensitivity is necessary. For pulse rate, the physical beating of the heart is transmitted as a mechanical pulse through the body to the pressure membrane sensor pad. Respiration is measured by mechanical pulses delivered to the sensor based on chest motion. The sensitive pressure membrane sensor pad measures all external motion and speech, forming a voltage signal output superimposed on the physiological signal. As a result, the movement or voice created by the subject may cause reading errors.

In this measurement environment, the P2M sensor measures all physical shocks, including physiological signals of the patient, ambient artificial noise and activity signals, noise and vibration from the machine, and Electromagnetic (EM) noise emitted by the lights and instruments. Although the output signal includes all of these signals, most are weak and do not affect the measurement, other noise, such as EM noise, can corrupt the readings. The noise may be removed by processing the signal through filters and other signal processing algorithms. The pre-processed signal is then analyzed by a procedure that includes a Fast Fourier Transform (FFT) that identifies the original signal frequency. For a silent, non-talking patient, the dominant frequency is usually breathing and the second highest frequency is heart rate. Patient position and frequency harmonics complicate this distinction, requiring additional logic to isolate and identify the frequency peaks of the heart and respiration. The logic algorithm must be robust enough to be able to determine the peak values of the respiration and the heart under various conditions.

To improve resolution, a large number of high-sampling-rate data points are selected and re-sampled at a lower rate to simplify the computation of accurate analysis. The minimum sampling interval is thirty seconds.

Fig. 3 shows the results of twenty breath/pulse rate measurements made using the P2M system. As a comparison, measurements for human evaluation (human evaluator) were also performed at the same time. Under ideal conditions, P2M accurately measures pulse 25 and respiration 27, but patient motion or speech can interfere with the precision measurement. The heart rate measurement quality is not degraded by lack of breathing, while P2M matches the comparison measurements 29, 31 with an error less than beats per minute.

Fig. 4 shows the panel of P2M in acquisition mode. The upper graph 33 shows a thirty second window of time-series measurements of all physiological signals. The heart beat spike is shown in the upper (time series) graph 33, along with the low frequency sinusoidal function corresponding to the respiration signal. The lower graph 35 shows the same data in the frequency domain. The first and maximum spikes 37 correspond to approximately 16.4 breaths/minute. The control group 31 measures 17 ± 2 breaths/minute. The larger amplitude of this spike indicates that the breath is the largest pulse measured by the sensor pad. The second largest spike 39 is sixty times per minute, which is consistent with the actual heart rate measured by the fingertip sandwich rate monitor. The energy measured by this amplitude is less than one third of the energy present in the breathing frequency and the ratio varies with the physiology of the patient and the position of the sensor pad. The smaller spikes 41 in the lower graph represent respiratory and heart rate harmonics, the result of which is not an ideal sinusoidal function. Since the heart rate may drop at exactly the same frequency as the respiratory harmonics, it is necessary to check the harmonics with a logic algorithm. The heart rate and respiratory harmonics can be distinguished by comparison of signals taken at different parts of the body.

Buttons and menus 43 on the panel of the interface program enable control of the data acquisition and analysis program. Thirty second data records may be stored for archiving or additional evaluation.

Fig. 5 shows the P2M system in monitor mode. The upper graph 45 shows time series data with a typical high frequency heartbeat spike 47 superimposed on a low frequency respiratory wave 49. The middle graph 51 shows heart rate 53 and respiration 55 updated every five seconds. When a new five second data string is obtained, the oldest five second data is discarded, while the heart rate and respiration are recalculated by analyzing the thirty second data string with the new data. The upper curve 53 is red, representing heart rate; the lower curve 55 is blue, representing breathing. The centre rate appeared stable in the middle 50s range with breathing in the middle ten seconds. The two (2) are favorably compared with a manually controlled measurement. The outliers 57 after 25 updates may be attributed to patient motion or external and erratic noise/vibration events. The lower graph 59 shows the fast fourier transform of the time series signal. The regular voltage signal of the heartbeat provides an intensity signal that is a level related to blood pressure. The time between signals at different parts of the body or the pattern of secondary signals provides information about the circulation or blockage or interference of blood flow.

In another preferred embodiment, FIG. 6 shows a schematic view of a P2M system with a single passive sensor 61 positioned on the patient 63. Fig. 7 shows a Graphical User Interface (GUI) of the P2M system. The upper graph 65 shows a 30 second window of digital voltage data in which low frequency oscillations are caused by respiration and high frequency spikes are the result of heartbeat measurements on a patient on a stretcher. The time series signal is converted into frequency data by fourier transform and displayed as an energy spectrum, as in the middle graph 67. From this data, pulse and respiration can be acquired by examining the energy associated with the dominant frequency 69.

In a preferred method of blood pressure measurement, passive measurement of blood pressure (systolic and diastolic) can be performed using pulse wave analysis. The measurement and characterization of Pulse Wave Velocity (PWV), or alternatively, Pulse Wave Transit Time (PWTT), inherently requires more than one measurement location. Therefore, multiple sensors are required to take measurements at different locations. For example, the sensor may measure pulse wave characteristics along the brachial artery, along with other measurements described herein.

Fig. 8 shows pulse measurements at two locations along the arm. The time separation between the two respective peaks 71, 73 gives the Pulse Wave Travel Time (PWTT). This value can be used for the relevant systolic and diastolic pressure. Likewise, several measurements for PWTT and blood pressure must be calibrated simultaneously to establish a calibration curve. Barschdorff & Erig shows that blood pressure (systolic and diastolic) is approximately linear with respect to PWV and PWTT.

The P2M system was tested and evaluated at TAMC at 2 months 1998. Simultaneous measurements of pulse and respiration were made using P2M, an electronic monitor, and human assessment. Figure 9 shows a picture of the test at TAMC. A total of 11 volunteers were monitored according to the test protocol for this test item.

The results of this test are shown in fig. 10. The accuracy of P2M is over 95% compared to the conventional method, while several cases where P2M is inconsistent with the conventional method prove to be valuable in subsequent modifications and improvements in the software of the present system. In addition, 12 volunteer nurses performed physiological monitoring of pulse and respiration using P2M, an electronic monitor, and human evaluation. After this monitoring has been performed, the nurse has completed the comparison and grading survey using the three methods described above.

On 5 months 3 1999, at the wheeler military airport, a P2M system test was performed for pulse and respiration in a high noise and vibration environment. The test was performed during rescue helicopter ground demonstration (static display). The main purpose of the test was to characterize a high noise/vibration environment with P2M, microphone and accelerometer. The results show that by filtering and signal analysis, the P2M is able to discriminate physiological signals from high amplitude and frequency noise caused by helicopters to accurately output pulse and respiration. Since this high noise environment would make the conventional method ineffective, the conventional method is not performed in this test.

FIG. 11 shows the P2M high noise and vibration test at the Wholer military airport on 3/5 of 1999.

Subsequently, the ability of the P2M system to accurately monitor pulse and respiration through multiple layers of clothing and braces was also tested in order to reply to the airrandom physician's survey during the wheeler test on day 5, 3/1999. Ballistic sheet body armor, military-specific poison attitude armor, and combinations of the two were tested using the P2M system. The results show that with additional layers between the body and the sensor, the accuracy of the P2M test is still high, mainly due to the increased contact area and the efficient transmission of mechanical and acoustic signals through these solid layers.

Single sensor P that has proven to accurately measure pulse and respiration²The M-structure is sensitive to patient position relative to the main sensor pad. The quality and magnitude of the physiological signal received by the system is location dependent. The preferred optimal location is to position the sensor directly below the center of the patient's chest. If the sensor is moved from this position, or if the patient position changes, the integrity of the input signal also changes. Thus, the preferred configuration is to utilize multiple sensors in a pattern that covers the entire area of the stretcher, the patientThe person lies therein so that one or more activity sensors are always in the optimal measuring position, whether the patient is moving or stationary.

In a preferred embodiment, the present invention is a passive system that utilizes a set of distributed sensors (or "multisensors") that are capable of accurately and robustly monitoring certain physiological signals of the human body. These signals can then be processed to determine the vital signs currently used by nurses and other caregivers, such as heart rate, respiration, and systolic/diastolic blood pressure.

Passive monitoring of parameters such as cardiac output, cardiac function and internal bleeding is within the scope of the present invention. The invention provides in particular a passive (completely non-invasive), unobtrusive and an autonomous device; i.e. the device never interferes with the patient's activities nor with other monitoring devices, while being able to operate with minimal technical knowledge. In addition, the device can operate reliably in high noise environments and other situations that render alternative and existing methods ineffective. These environments include, but are not limited to, operations performed by helicopter or ambulance rescue (MEDEVAC) and through military determined defense attitude (MOPP) protectors and body armor.

With the development of reliable multi-sensor monitoring systems for such harsh and noisy operation, in the hospital ICU (intensive care unit) environment, noise is substantially less and the application here is simpler. It is of significant intrinsic value to make completely non-invasive, passive, pulse, respiration, blood pressure (and cardiac output measurements, internal bleeding, shock, etc.) measurements even in a noise-free environment, using a patient-agnostic sensor system. The passive and autonomous operation of such a system is suitable for telemetry and real-time remote monitoring, while the last feature of the invention is a telemetry design for remote and telemonitoring.

Fig. 14 shows a schematic of P2M incorporated into a rescue stretcher using passive sensor arrays and microelectronics. A schematic of the inventive technique incorporated into a rescue stretcher is shown in fig. 14 below. The stretcher 75 contains an array 77 of 32 sensors, each of which measures both acoustic and hydraulic inputs from the patient 63. Each of these signals contains a physiologically generated signal and a measurement of ambient noise. The ambient noise on each pad is similar, while the physiologically generated signal is location dependent. This information can be used to separate the signal from the noise by inspection techniques.

The position-dependent physiological signals are used to determine the patient's position, heart rate, respiration, blood pressure, pulse intensity distribution and potentially some measure of cardiac output.

In addition to ambulance stretchers, the present invention may be incorporated into a number of applications. The operation of configuring the passive sensor array on a hospital bed or on a common mattress used at home does not change much. Of particular note is the care area for premature infants. In such cases, securing the sensor lead to the infant is often difficult and can result in irritation of sensitive skin and tangling of the lead. The sensor may be incorporated into equipment employed in the civilian and military sectors. The sensor may also be incorporated into field devices, clothing, and military uniforms. This includes, but is not limited to, neck collars, body armor, biological and/or chemical hazard protective apparel, extraction devices (extraction devices), clothing, and padding on seats and seat backs. Training devices such as stationary bicycles, treadmills, or walkers may benefit from coupling the sensors to the support.

Physiological parameters such as heart rate can be measured by the handle, which helps regulate exercise. Other useful applications may include the use of passive sensor systems in psychometric chairs or beds. Monitoring of the subject's physiological signs may provide an indication of emotional fluctuations caused by triggering words or events during discussion. The size of each sensor, the number of sensors in the array, and the configuration of the sensor array can be adjusted to meet specific needs and circumstances without requiring many trials. For example, for a mattress, 32 or more sensors in a rectangular array may be required.

Preferred passive sensors may employ piezoelectric membranes and ceramics, hydrophones, microphones or pressure sensors. The amplification hardware may include signal amplification circuitry and hardware such as a charge amplifier. The system uses data acquisition hardware and signal processing hardware (circuitry) and software. For the connection between the sensor and the patient, a layer of solid, fluidized (air) or fluid, such as gel, water, foam, rubber, plastic, etc., can be used. The connection facilitates the transmission of physiological signals.

The invention has great medical value and can be used for on-site monitoring, hospital monitoring, transportation monitoring and home/remote monitoring. For example, the present invention may be applied to every hospital that performs passive monitoring of patients. The invention is imperceptible to the patient, which increases the comfort of the monitoring process.

Although the present invention has been described with reference to specific embodiments, various modifications and changes can be made without departing from the scope of the present invention.

Claims

1. A device for passively monitoring patient physiology, the device comprising:

at least two sensors, each of said sensors comprising a piezoelectric film for detecting physiological signals from the patient and environmental signals from the environment surrounding the patient;

a converter in communication with the at least two sensors for converting the physiological and environmental signals to digital signals;

a processor in communication with the converter for isolating a physiological digital signal from the digital signal by comparing the digital signal between the at least two sensors to provide physiological data; and

a monitor in communication with the processor for displaying the physiological data in real time.

2. The apparatus of claim 1, wherein the piezoelectric film comprises a polyvinylidene fluoride film.

3. The apparatus of claim 1, further comprising at least one band pass filter coupled to the at least two sensors for filtering out at least one of the ambient signals.

4. The apparatus of claim 3, further comprising a preamplifier coupled to said band pass filter for preamplifying at least one of said physiological and environmental signals.

5. The device of claim 1, wherein the physiological and environmental signals are selected from the group consisting of mechanical, thermal, and acoustic signals.

6. The apparatus of claim 1, wherein the physiological and environmental signals are indicative of cardiac output, cardiac function, internal bleeding, respiration, pulse, apnea, temperature signals, and combinations thereof.

7. The apparatus of claim 2, further comprising a liner incorporating the polyvinylidene fluoride membrane.

8. The device of claim 7, wherein the pad is a fluid-filled contact surface for facilitating physiological signal transmission.

9. The apparatus of claim 8, wherein the fluid is an inactive substance selected from the group consisting of gel, water, air, foam, rubber, and plastic, or a combination thereof.

10. The apparatus of claim 1, wherein the processor further comprises a frequency fourier transform for converting the physiological digital signal into frequency data.

11. The apparatus of claim 10, further comprising a microcomputer for recording, analyzing and displaying said frequency data for on-line evaluation thereof while responding to said frequency data in real time.

12. The device of claim 1, wherein the piezoelectric membrane is placed at different locations under a patient.

13. The apparatus of claim 1, wherein the piezoelectric film is placed on the patient as a wrap.

14. A passive physiological monitoring device for monitoring the physiology of a patient, comprising:

a plurality of sensors for detecting data by placement on a patient, each of the plurality of sensors comprising a piezoelectric film comprising a polymer for detecting data from the body and converting the detected data into voltage measurements, the polymer comprising polyvinylidene fluoride, wherein the plurality of sensors comprises a plurality of pairs of sensors for detecting the detected data from the patient and for independently detecting ambient noise;

a converter in communication with each of the plurality of sensors for converting the detection data into a signal;

computing means in communication with the converter for receiving and computing the signals and for outputting computed data; and

an instrument in communication with the computing device for real-time interaction with the device and for displaying the computed data.

15. The apparatus of claim 1 or 14, wherein at least one of the sensors is located on a substrate, the substrate being furniture.

16. The apparatus of claim 1 or 14, wherein at least one of the sensors is located on a substrate selected from the group consisting of a portion of clothing, a corbel, a bed, a stretcher, a neck collar, body armor, a uniform, an extraction device, a training apparatus, a mat, a seat, and a seatback.

17. The apparatus of claim 14, wherein the plurality of sensors are configured to measure pulse wave velocity at a plurality of locations on the patient.

18. The apparatus of claim 14, wherein the plurality of sensors are configured to measure pulse wave transit times at a plurality of locations on the patient.

19. The apparatus of claim 1, wherein the at least two sensors comprise an array of sensors distributed at different locations for measuring acoustic and mechanical signals from the patient with each sensor.

20. The apparatus of claim 19, further comprising a stretcher incorporating the sensor array for measuring acoustic and hydraulic signals from the patient and from the adjacent area while the patient is on the stretcher.

21. The apparatus of claim 20, wherein the acoustic and hydraulic signals comprise physiological signals from a patient and environmental signals from the vicinity.

22. A device for passively monitoring patient physiology, the device comprising:

a first piezoelectric sensor in contact with a patient;

a second piezoelectric sensor in close proximity to, but not in contact with, the patient;

detecting a physiological signal and an environmental signal with the first sensor while detecting an environmental signal with the second sensor;

a converter for converting the physiological and environmental signals into physiological and environmental digital signals;

a processor for separating the physiological digital signal from the environmental digital signal by subtracting the environmental signal detected by the second sensor from the signal detected by the first sensor; and

a display for displaying the physiological digital signal.

23. The apparatus of claim 22, further comprising a band pass filter for filtering out the ambient signal.

24. The apparatus of claim 22, wherein the sensor is adapted to detect mechanical as well as acoustic signals.

25. The apparatus of claim 22, further comprising:

a third sensor placed on the patient at a location remote from the first sensor; and

measuring a pulse wave velocity with the first and third sensors.

26. The apparatus of claim 22, wherein the first sensor is in contact with the patient and the second sensor is in an environment surrounding the patient but not in contact with the patient.

27. The apparatus of claim 26, wherein the processor compares the physiological signal detected by the first and second sensors, respectively, to an environmental signal to isolate the physiological signal.

28. The apparatus of claim 22, wherein a first sensor is located at a first location and a second sensor is located at a second location, and wherein the processor determines a pulse wave velocity from a time difference of physiological signals between the first sensor and the second sensor.

29. The apparatus of claim 28, wherein the processor calculates blood pressure data from the pulse wave velocity.

30. The apparatus according to claim 25, wherein said processor is adapted to convert said pulse wave velocity into systolic and diastolic blood pressure data and said display is adapted to display said blood pressure data.

31. The apparatus of claim 22, further comprising:

a third sensor coupled to the patient at a location remote from the first sensor; and

measuring a pulse wave transit time between the first sensor and the third sensor.

32. The apparatus according to claim 31, wherein said processor is adapted to convert said pulse wave transit time into systolic and diastolic blood pressure data, and said display is adapted to display said blood pressure data.

33. The apparatus of claim 22, wherein the sensor is adapted to detect the physiological signal through one or more layers of clothing, body armor, or a combination thereof.

34. A device for passively monitoring patient physiology, the device comprising:

a first piezoelectric sensor coupled to the patient;

a second piezoelectric sensor at a location proximate to but not in contact with the patient;

the first sensor is adapted to detect a physiological signal and an environmental signal, and the second sensor is adapted to detect an environmental signal;

a processor for separating the physiological signal from the ambient signal by subtracting the ambient signal detected by the second sensor from the signal detected by the first sensor; and

a display for displaying the physiological signal.

35. The apparatus of claim 34, further comprising:

a third piezoelectric sensor coupled to the patient at a location remote from the first piezoelectric sensor;

detecting a physiological signal and an environmental signal with the third sensor; and is

Wherein the processor is further adapted to compare the physiological and environmental signals from the first sensor with the physiological and environmental signals from the third sensor to determine the location of the first and third sensors on the patient.

36. A device for passively monitoring patient physiology in a vibrating environment, the device comprising:

at least two piezoelectric sensors for detecting physiological signals from the patient and vibrational signals from the patient's surroundings;

a converter in communication with the at least two sensors for converting the physiological signal and the ambient vibration signal into digital signals;

a processor in communication with the converter for providing physiological data by correlating the digital signals between the at least two sensors to isolate a physiological digital signal from the digital signals; and

37. The apparatus of claim 36, wherein each of the piezoelectric sensors comprises a polyvinylidene fluoride membrane.

38. The device of claim 37, wherein the pad includes a fluid contact surface for facilitating the transmission of physiological signals, the fluid being an inactive substance selected from the group consisting of gel, water, air, foam, rubber, and plastic, or a combination thereof.

39. The apparatus of claim 36, wherein the piezoelectric sensors are placed at different locations under the patient.

40. The device of claim 36, wherein the physiological and ambient vibration signals comprise mechanical, thermal, and acoustic signals, and/or wherein the physiological and ambient signals are indicative of cardiac function, respiratory function, and combinations thereof.

41. The apparatus of claim 36, wherein the processor further comprises a time series transform for converting the physiological digital signal into frequency signals comprising respiratory and heart rate harmonics and distinguishing the respiratory and heart rate harmonics by selectively comparing signals from different locations of the patient's torso, and wherein the apparatus comprises a microcomputer for calculating the frequency spectrum from the digital signal and extracting signals related to the patient's physiology by identifying peaks of the frequency spectrum corresponding to selected physiological parameters.

42. A passive physiological monitoring device for monitoring the physiology of a patient, comprising:

a plurality of sensors that passively detect data at a plurality of locations on the body of a patient, each of the plurality of sensors including a piezoelectric sensor for detecting acoustic and mechanical signals from the body of the patient and converting the detected data into voltage measurements, wherein the plurality of sensors includes at least one pair of sensors for detecting data from the patient;

a converter in communication with each of said plurality of sensors for converting said sensed data into signals;

a computing device in communication with said converter for receiving and computing said signals and for outputting computed data; and

a display for displaying said calculated data in real time.

43. The apparatus of claim 42, wherein at least one of the plurality of sensors is located on a substrate, the substrate being furniture.

44. The apparatus of claim 42, wherein at least one of the plurality of sensors is located on a substrate selected from the group consisting of a portion of clothing, a corbel, a bed, a stretcher, a neck collar, body armor, a uniform, an extraction device, a training apparatus, a mat, a seat, and a seatback.

45. The apparatus of claim 42 further comprising a patient support surface incorporating an array of sensors for measuring acoustic and mechanical signals from the patient and from adjacent areas with each of the sensors when the patient is positioned on the patient support surface.

46. The apparatus of claim 42, wherein the plurality of sensors are positioned at different locations on a patient support surface, and the computing device calculates blood pressure data by determining a time difference between respective signals from the sensors,

and/or wherein the plurality of sensors includes at least one sensor positioned proximate to an extremity of the patient for isolating cardiac energy from respiration.

47. The device of claim 42, wherein the plurality of sensors are configured to measure pulse wave velocity at a plurality of locations on the patient and/or the plurality of sensors are configured to measure pulse wave transit time at a plurality of locations on the patient.

48. The apparatus of claim 36, further comprising a patient support surface incorporating a sensor array for measuring acoustic and mechanical signals from the patient while the patient is positioned on the patient support surface.

49. The apparatus of claim 46, wherein the plurality of sensors comprises at least three sensors at three different locations on the patient's body.

50. The apparatus according to claim 42, wherein the computing device correlates signals detected by the sensors to isolate physiological signals.

51. The apparatus according to claim 42, wherein a first sensor is placed at a first location and a second sensor is placed at a second location, and wherein the computing device determines the pulse wave velocity from a physiological signal time difference between the first and second sensors.

52. The apparatus of claim 42, wherein each of the sensors is configured to detect physiological data from the patient and to detect external patient motion at different locations on the patient's torso, and the computing device to distinguish a physiological data signal and a signal due to external motion by correlation.

53. A device for passively monitoring patient physiology, comprising:

a first sensor adapted to be connected to the patient;

a second sensor adapted to be connected to the patient at a location remote from the first sensor;

the first and second sensors are adapted to detect physiological signals and ambient noise and vibrations;

a processor for comparing the physiological signals and ambient noise and vibration from the first sensor with the physiological signals and ambient noise and vibration of the second sensor for separating selected physiological signals from the ambient noise and vibration.

54. The apparatus according to claim 53, wherein the processor is further adapted to measure a pulse wave transit time between the first and second sensors; and

converting the pulse wave transit time into blood pressure data of systolic pressure and diastolic pressure and displaying the blood pressure data.

55. A device for passively monitoring patient physiology, the device comprising:

a first piezoelectric sensor adapted to engage the patient by connecting the patient and a patient support surface comprising the first piezoelectric sensor;

a second piezoelectric sensor in a position to detect ambient noise other than physiological signals from the patient;

a third piezoelectric sensor adapted to engage the patient at a location remote from the first sensor;

the first and second sensors are adapted to detect physiological signals and ambient noise, and the second sensor is adapted to detect ambient noise;

a processor for separating the physiological signal from the ambient noise detected by the second sensor by subtracting the ambient noise detected by the second sensor from the signals detected by the first and third sensors;

the processor is further adapted to compare the physiological signals and ambient noise from the first sensor with the physiological signals and ambient noise from the third sensor for isolating selected ones of the physiological signals; and

a display for displaying the selected ones of the physiological signals.

56. An apparatus for passively monitoring patient physiology, comprising:

a plurality of sensors, each of the sensors capable of simultaneously detecting a plurality of physiological parameters of a patient and adapted to be placed at different locations on the patient's torso;

a converter in communication with the sensor for converting the detected physiological parameter into a digital signal; and

a processor in communication with the converter for receiving the digital signal and extracting a signal related to one or more selected physiological parameters of the patient.

57. The apparatus according to claim 56, wherein said sensor is incorporated into a stretcher covered by said array of sensors.

58. The apparatus of claim 56, wherein the sensor is disposed in a pad.

59. The apparatus of claim 56, wherein the plurality of physiological parameters comprise a respiration rate and a heart rate.

60. The device of claim 56, wherein each of the sensors is capable of simultaneously detecting acoustic and mechanical signals from a physiological parameter of the patient.

61. The device according to claim 56, further comprising a monitor in communication with the processor for displaying the physiological signal in real time.

62. An apparatus for passively monitoring patient physiology in a vibrating environment, comprising:

a sensor adapted to be coupled to the patient, the sensor comprising a piezoelectric film;

the sensor is adapted to detect mechanical energy of the patient, the mechanical energy including energy related to the patient's physiology and energy caused by a vibration environment;

a converter for converting the detected mechanical energy into a signal; and

a processor for extracting a signal corresponding to the physiology of the patient, for isolating a signal related to a selected physiological parameter of the patient, and for outputting a signal representative of the selected physiological parameter of the patient.

63. The device of claim 62, wherein the piezoelectric film comprises a polyvinylidene fluoride film.

64. The apparatus of claim 62, wherein the vibrating environment comprises a medical transporter.

65. The apparatus of claim 62, wherein the vibratory environment comprises a helicopter.

66. The apparatus of claim 65, wherein the selected physiological parameter is selected from the group consisting of a respiration rate and a pulse rate.

67. The apparatus of claim 62, wherein the vibrating environment comprises an ambulance.

68. The apparatus of claim 62, wherein the sensor is positioned along a patient support surface.

69. The apparatus according to claim 62, wherein said sensor is adapted to be placed on said patient.

70. The apparatus of claim 62, wherein the sensor is about 20 centimeters by 25 centimeters in size and encased in a protective sheath.

71. The apparatus according to claim 62, wherein the sensor is adapted to detect mechanical energy of the patient through one or more layers of clothing.

72. An apparatus according to claim 62, wherein the sensor is adapted to detect mechanical energy of the patient through one or more layers of bedding.

73. The apparatus of claim 62, wherein the sensor comprises a plurality of the piezoelectric membranes arranged in an array.

74. The device of claim 62, further comprising a backing having the piezoelectric film therein.

75. An apparatus for passively monitoring patient physiology in an environment, comprising:

a first sensor adapted to be connected to the patient;

both the first sensor and the second sensor are adapted to detect a physiological parameter of the patient and a condition of an environment surrounding the patient;

a converter for converting the detected physiological parameter and environmental condition into a signal; and

a processor for correlating signals from the first and second sensors to extract signals related to the patient physiology.

76. The apparatus according to claim 75, wherein the first and second sensors comprise passive sensors for detecting mechanical activity of the patient's torso.

77. The apparatus of claim 76, wherein the sensor comprises a piezoelectric sensor.

78. The device of claim 75, wherein each of the first and second sensors comprises a piezoelectric film.

79. The device of claim 76, wherein each of the sensors comprises a polyvinylidene fluoride membrane.

80. The device of claim 78, wherein a contact surface is disposed between said membrane and said patient for facilitating the transfer of a physiological parameter from said patient to said membrane.

81. The apparatus of claim 80, wherein the contact surface is selected from the group consisting of gel, water, air, foam, rubber, and plastic.

82. The device according to claim 75, wherein the sensor is adapted to detect noise and vibrations in the patient's surroundings.

83. The apparatus of claim 75, further comprising:

a third sensor adapted to be placed at a location isolated from the patient for detecting the environmental condition without detecting the physiological parameter of the patient; and also

The processor is further adapted to reduce environmental interference in the signals generated by the first and second sensors by subtracting the signal generated by the third sensor from the signals generated by the first and second sensors.

84. The apparatus of claim 75, further comprising:

calculating an energy spectrum from the signal; and

extracting a signal related to the patient physiology by identifying peaks in the energy spectrum corresponding to physiological parameters of the patient.

85. A device for passively monitoring patient physiology, comprising:

a plurality of sensors positioned along a patient support surface, each of the sensors being capable of passively detecting a physiological parameter of the patient and a condition of an environment surrounding the patient;

a processor for correlating signals between the sensors to extract signals related to the patient physiology.

86. The apparatus according to claim 85, wherein the sensor is adapted to detect noise and vibration from the patient's surroundings.

87. The apparatus according to claim 85, wherein the sensor is adapted to detect mechanical energy of the patient.

88. The apparatus according to claim 85, wherein the sensor comprises a plurality of piezoelectric membranes disposed in an array along the patient support surface.

89. A device for passively monitoring patient physiology in a vibrating environment, comprising:

a plurality of independent sensors adapted to be connected to the patient at different locations on the patient's torso;

the sensor is adapted to detect mechanical energy of the patient's body due to physiological causes and mechanical energy of the patient's body due to environmental vibrations at each of the locations;

a converter for converting the detected mechanical energy into a plurality of signals; and

a processor for correlating the signals between the sensors to extract signals related to the patient physiology.

90. The device of claim 89, wherein each sensor of the plurality of sensors comprises a piezoelectric film.

91. The device of claim 89, wherein each of the sensors comprises a polyvinylidene fluoride membrane.

92. The device according to claim 89, wherein said sensor is adapted to detect mechanical energy of said patient related to cardiac and respiratory functions.

93. An apparatus adapted to passively monitor patient physiology in a vibrating environment, comprising:

at least two sensors, each said sensor capable of passively detecting patient physiological parameters at different locations of a patient's torso and vibrations from the patient's surroundings;

a converter in communication with the sensor for converting the sensed physiological parameter and environmental vibrations into digital signals; and

a processor in communication with the converter for processing the digital signals to extract signals related to the patient physiology by correlating the signals between the sensors.

94. The apparatus according to claim 93, wherein said sensor comprises a passive sensor for detecting mechanical energy of the patient's body and generating an electrical signal responsive to said mechanical energy.

95. The device of claim 93, wherein each of the sensors comprises a piezoelectric film.

96. The device of claim 95, wherein each of the sensors comprises a polyvinylidene fluoride membrane.

97. The apparatus of claim 95, further comprising a liner incorporating said piezoelectric film.

98. The device of claim 93, further comprising a monitor in communication with the processor for displaying the physiological data in real time.

99. The apparatus of claim 93, wherein the processor is in wireless communication with the converter.

100. The apparatus of claim 93, wherein the sensor is positioned along a patient support surface.

101. The apparatus of claim 100, wherein the patient support surface comprises a medical transporter.

102. The apparatus of claim 93, wherein the sensor is placed in hospital bedding.

103. The apparatus of claim 93, wherein the processor further calculates an energy spectrum from the digital signal and extracts a signal related to the patient physiology by identifying peaks in the energy spectrum corresponding to selected physiological parameters.

104. The device of claim 93, further comprising a pad incorporating the sensor, a contact surface within the pad being made of a material selected from the group consisting of gel, water, air, foam, rubber, and plastic.

105. The apparatus of claim 93, wherein the processor extracts signals related to cardiac and respiratory activity of the patient.

106. An apparatus for passively monitoring patient physiology, comprising:

a plurality of sensors positioned along a patient support surface, each of the sensors being capable of passively detecting physiological parameters of the patient at different locations on the patient's torso and ambient noise and vibration due to the patient's ambient environment;

a converter in communication with the sensor for converting the sensed physiological parameter and ambient noise and vibration into digital signals;

a processor in communication with the converter for receiving and correlating the digital signals to extract signals related to the patient's physiology; and

a monitor in communication with the processor for displaying the physiological signal in real time.

107. The apparatus according to claim 106, wherein said sensor comprises a passive sensor for detecting mechanical energy of the patient's body and generating an electrical signal responsive to said activity.

108. The apparatus of claim 106, wherein each of said sensors comprises a piezoelectric film.

109. The apparatus according to claim 106, wherein the patient support surface is furniture.

110. The apparatus according to claim 106 wherein the patient support surface is selected from the group consisting of a stretcher, a bed, a stretcher, a table, a cushion, a seat, and a seatback.

111. The apparatus according to claim 106, wherein the patient support surface is a gurney.

112. The device of claim 106, wherein the sensor is configured to measure pulse wave transit time between a plurality of locations on the patient's torso.

113. An apparatus for passively monitoring patient physiology, comprising:

a plurality of sensors for passively detecting mechanical energy at a plurality of different locations on a patient's body;

a transducer in communication with said sensor for converting said sensed mechanical energy into a plurality of digital signals reflecting movement of said patient's body at each of said locations; and

a processor in communication with the converter for processing the digital signals to extract signals related to at least one selected physiological parameter of the patient and to derive output signals representative of the selected physiological parameter, the processor correlating the digital signals between the plurality of sensors to attenuate signals caused by ambient environmental conditions.

114. The device of claim 113, wherein the sensor is configured to detect mechanical energy due to a physiological condition of a patient and vibrations from an environmental condition surrounding the patient.

115. The apparatus according to claim 113, wherein the processor processes the digital signal to extract a signal related to the patient's cardiac activity.

116. The apparatus according to claim 113, wherein the processor processes the digital signal to extract a signal related to respiratory activity of the patient.

117. The apparatus according to claim 113, wherein the processor processes the digital signals to extract signals relating to cardiac and respiratory activity of the patient.

118. The device of claim 113, wherein the processor correlates signals between the plurality of sensors to attenuate signals related to ambient vibrations.

119. The device of claim 113, wherein the plurality of sensors comprises a plurality of piezoelectric membranes.

120. The apparatus of claim 119, further comprising a pad incorporating the membrane, the pad configured to be placed against a torso of a patient.

121. An apparatus for passively monitoring patient physiology, comprising:

a plurality of sensors for passively detecting mechanical energy at a plurality of different locations on a patient's body, at least one of the sensors adapted for placement in a region of the patient's limb;

a converter in communication with the sensor for converting the sensed mechanical energy into a plurality of digital signals; and

a processor in communication with the transducer for extracting signals due to the patient's heart activity by selectively ignoring signals.

122. The apparatus according to claim 121, wherein the at least one sensor is adapted to be placed on the patient's foot.

123. The device of claim 121, wherein each sensor of the plurality of sensors comprises a piezoelectric film.

124. The device of claim 121, wherein each sensor of the plurality of sensors comprises a polyvinylidene fluoride membrane.

125. An apparatus for passively monitoring patient physiology, comprising:

a plurality of sensors for detecting mechanical energy at a plurality of different locations on the patient's body;

a processor in communication with the transducer for extracting signals due to heart activity of the patient by selectively comparing signals from the different locations on the patient's torso.

126. The device of claim 125, wherein each sensor of the plurality of sensors comprises a piezoelectric film.

127. The device of claim 125, wherein each sensor of the plurality of sensors comprises a polyvinylidene fluoride membrane.

128. The device of claim 125, wherein the processor further converts the digital signal to a frequency signal comprising respiratory and heart rate harmonics and distinguishes between heart rate and respiratory harmonics by selectively comparing signals from the different locations on the patient's torso.

129. The apparatus of claim 125, wherein:

the plurality of sensors includes at least two sensors for detecting physiological parameters of different parts of the patient's body; and

the processor is in communication with the converter for determining a pulse wave velocity from a time difference between corresponding signals from the at least two sensors and converting the pulse wave velocity into a signal corresponding to blood pressure data.

130. The apparatus according to claim 129 wherein the at least two sensors comprise a first sensor disposed at a first location along the patient support surface and a second sensor disposed at a second location along the patient support surface remote from the first location.

131. The apparatus according to claim 129, wherein said processor converts said pulse wave velocity into signals corresponding to systolic and diastolic pressure data.

132. The apparatus according to claim 129, wherein said at least two sensors include at least three sensors for detecting physiological parameters of the patient at least three different parts of the patient's body, and said processor determines the pulse wave velocity from the time difference between the signals from said at least three sensors.

133. An apparatus for passively monitoring patient physiology, comprising:

at least two sensors, each sensor comprising a piezoelectric film for sensing a physiological parameter of a patient at a different part of the patient's body;

a converter in communication with the sensor for converting the sensed physiological parameter to a digital signal; and

a processor in communication with the transducer for determining a pulse wave transit time from a time difference between corresponding signals from the sensor and converting the pulse wave transit time into a signal corresponding to blood pressure data.

134. The apparatus of claim 133 wherein the at least two sensors include a first sensor positioned at a first location along the patient support surface and a second sensor positioned at a second location along the patient support surface remote from the first location.

135. The apparatus according to claim 133, wherein said processor converts said pulse wave transit time into signals corresponding to systolic and diastolic pressure data.

136. The apparatus according to claim 133, wherein said at least two sensors include at least three sensors for detecting physiological parameters of the patient at least three different parts of the patient's body, and said processor determines pulse wave transit time from time differences between signals from said at least three sensors.

137. The device of claim 125, wherein:

the plurality of sensors includes at least three sensors for detecting physiological parameters of the patient at least three different portions of the patient's torso; and

the processor is in communication with the converter for extracting signals representative of the patient's heart rate at each of the different locations on the patient's torso, comparing the heart rate signals from the different locations on the patient's torso to determine a time interval between corresponding heart rate signals at the different locations on the patient's torso, calculating a pulse wave propagation rate through the patient's torso based on the time interval, and converting the pulse wave propagation rate into signals corresponding to blood pressure data.

138. The device of claim 137, wherein each of the sensors comprises a piezoelectric film.

139. The device of claim 137, wherein each sensor of the plurality of sensors comprises a polyvinylidene fluoride membrane.

140. The device of claim 137, wherein the blood pressure signals include systolic and diastolic blood pressure data.

141. The apparatus of claim 125, comprising:

the plurality of sensors are adapted to be connected to a patient at different locations on the patient's torso;

the sensor is adapted to detect a physiological activity of the patient;

the converter is adapted to convert the detected physiological activity into a signal; and

the processor is adapted to measure pulse wave transit times between the sensors and to convert the pulse wave transit times into blood pressure data.

142. The device of claim 141, wherein the blood pressure data includes systolic and diastolic blood pressure data.

143. The apparatus of claim 141, wherein the different locations are remote from each other.

144. The device of claim 141, wherein the sensor is adapted to detect physiological activity through one or more layers of clothing.

145. An apparatus according to claim 141, wherein said sensor is adapted to detect physiological activity through one or more layers of bedding.

146. The apparatus of claim 125, comprising:

the sensor is adapted to detect a physiological activity of the patient;

the processor is adapted to measure a pulse wave velocity with the sensor and to convert the pulse wave velocity into blood pressure data.

147. The device of claim 146, wherein the blood pressure data includes systolic and diastolic blood pressure data.

148. The apparatus of claim 146, wherein the different locations are remote from one another.

149. The apparatus according to claim 146, wherein the sensor is adapted to detect physiological activity through one or more layers of clothing.

150. An apparatus according to claim 146, wherein said sensor is adapted to detect physiological activity through one or more layers of bedding.

151. An apparatus for passively monitoring the physiology of a moving patient, comprising:

at least two sensors, each said sensor configured to detect patient mechanical energy due to a physiological parameter and patient mechanical energy due to external motion at different locations on the patient's torso;

a converter in communication with the sensor for converting the sensed mechanical energy into a digital signal; and

a processor in communication with the converter for processing the digital signals to distinguish between signals due to physiological parameters and signals due to external motion by correlating the signals between the sensors.

152. The device of claim 151, wherein each of the sensors comprises a piezoelectric film.

153. The device of claim 151, wherein each of the sensors comprises a polyvinylidene fluoride membrane.

154. The apparatus of claim 151, wherein the sensor is positioned along a patient support surface.

155. The device of claim 151, further comprising a pad incorporating the sensor.

156. A device for passively monitoring patient physiology in a helicopter environment, comprising:

a motion sensor adapted to be connected to the patient;

the motion sensor is adapted to detect mechanical energy of the patient, the mechanical energy including energy related to the patient physiology and energy related to a helicopter environment;

a converter for converting the detected mechanical energy into a signal; and

157. The apparatus of claim 156, wherein the sensor comprises a piezoelectric film.

158. The apparatus according to claim 156, further comprising a plurality of sensors adapted to be connected to the patient at different locations on the patient's torso and for detecting mechanical energy of the patient.

159. The apparatus of claim 1, wherein the at least two sensors comprise an array of sensors distributed over different locations on the patient support surface.

160. The apparatus of claim 159, wherein the array comprises a rectangular array.

161. The apparatus of claim 159, wherein the array comprises sensors distributed in adjacent rows and columns.

162. The apparatus according to claim 161 wherein the patient support surface is selected from the group consisting of a hospital bed and a stretcher.

163. The apparatus of claim 159, wherein the sensors are arranged in a pattern that covers substantially the entire area of the patient support surface.

164. The apparatus of claim 1, wherein each of the sensors is rectangular in shape.

165. The apparatus of claim 164, wherein each of the sensors has dimensions of about 20 centimeters by 25 centimeters.

166. The apparatus of claim 1, wherein the at least two sensors comprise a plurality of sensors placed at different locations along a length of the patient support surface.

167. The apparatus of claim 1, wherein the at least two sensors comprise a plurality of sensors placed at different locations along a lateral direction of the patient support surface.

168. The apparatus of claim 166, wherein the at least two sensors further comprise a plurality of sensors placed at different locations along a lateral direction of the patient support surface.

169. The device of claim 36, further comprising a pad incorporating a piezoelectric sensor.

170. The apparatus according to claim 42, wherein said computing device further computes blood pressure data in response to said pulse wave velocity.