CN105433931A - Processing device and method for describing waveform by light volume change - Google Patents

Abstract

The invention discloses a processing device and method for a light volume change description waveform. The processing device includes a light volume change description waveform (PPG) signal acquisition unit that acquires a PPG signal, and during the acquisition of the PPG signal, An operation information acquisition unit acquires motion information, outputs the PPG signal and motion information to a first adaptive digital filtering unit, filters out interference signals of motion artifacts from the PPG signal, and then filters the The divided PPG signal is output to a second adaptive digital filtering unit to capture the periodic signal in the second PPG signal and improve the signal-to-noise ratio of the periodic signal as a basis for reading an accurate heartbeat signal. Therefore, the PPG signal processing device of the present invention can be applied to a wearable heartbeat detection device to provide correct heartbeat information.

Description

Device and method for processing light volume change description waveform

technical field

The present invention relates to a processing device and method for describing waveforms of light volume changes, in particular to a processing device and method for describing waveforms of light volume changes applied to wearable heartbeat detection devices.

Background technique

Wearable electronic devices usually provide the function of monitoring the user's movement (such as the step counting function), or provide the function of detecting and recording the physiological characteristics of the human body (such as heartbeat, blood pressure or blood oxygen), so they are very popular among consumers. However, the heartbeat detection results of wearable electronic devices are still worse than those of general fixed sphygmomanometers. The signal generates an interfering signal.

Generally, the extracted physiological characteristic signal is converted from the time-domain waveform (as shown in FIG. 9A ) to the frequency-domain waveform (as shown in FIG. 9B ), and then the periodic signal in the frequency domain is used as the basis for measuring the heartbeat frequency. If the correct heartbeat frequency is measured, it will be as shown in FIG. 9D . However, in addition to the heartbeat signal S _heart in the frequency domain signal, as shown in Figure 9B, it also contains low-frequency signals caused by hand swings and body shaking, or includes low-frequency signals caused by rapid hand swings and body shaking The high-frequency signal, when part of the energy of the low-frequency or high-frequency signal will be higher than the energy of the heartbeat signal. Since the frequency signal contains motion interference signal S _motion (or motion artifact; _{MotionArtifact} ), it will be misdetected as a heartbeat signal, so after the detected heartbeat signal is transferred from Shear to time domain signal, non-heartbeat will appear The signal S _motion is shown in FIG. 9C .

Therefore, it is necessary to further improve the accuracy of heartbeat detection by current wearable electronic devices.

Contents of the invention

In view of the fact that the detection of physiological signals by wearable electronic devices is susceptible to the interference of motion artifacts and reduces its detection accuracy, the main purpose of the present invention is to provide a processing device and method for describing a photovolume change description waveform (PPG), which helps to improve physiological Signal measurement accuracy.

The main technical means used to achieve the above purpose is to make the processing device of the light volume change description waveform (PPG) include:

A light volume change description waveform (PPG) signal acquisition unit is used to extract the first PPG signal;

A motion information extraction unit is used to retrieve a motion information;

A first adaptive digital filtering unit is connected to the PPG signal acquisition unit and the motion information acquisition unit to receive the first PPG signal and the motion information, and according to the motion information, the first PPG The motion artifact interference signal contained in the signal is eliminated, and the second photovolume change description waveform (PPG) signal is output;

A second adaptive digital filtering unit is connected to the first adaptive digital filtering unit to receive the second PPG signal, extract the periodic signal in the second PPG signal, and improve the periodicity output a physiological characteristic signal after the signal-to-noise ratio of the signal.

The main technical means used to achieve the above-mentioned purpose is to make the processing method of the light volume change description waveform (PPG) include:

(a) Obtaining a first photovolume description waveform (PPG) signal and motion information;

(b) canceling the motion artifact interference signal included in the first PPG signal according to the motion information, and outputting a second PPG signal; and

(c) extracting a periodic signal in the second PPG signal, and outputting a physiological characteristic signal after increasing the signal-to-noise ratio of the periodic signal.

It can be seen from the above description that the present invention mainly uses an operation information extraction unit to extract motion information during the acquisition of PPG signals. Since the PPG signals extracted from the human body will contain interference signals with motion artifacts, the first The adaptive digital filtering unit filters most of the motion artifact interference signals from the PPG signal according to the motion information, and then outputs the filtered PPG signal to a second adaptive digital filtering unit to extract Taking the periodic signal in the second PPG signal and improving the signal-to-noise ratio of the periodic signal is used as the basis for reading out the accurate heartbeat signal. Therefore, the PPG signal processing device of the present invention can be applied to a wearable heartbeat detection device to provide correct heartbeat information.

Description of drawings

FIG. 1 is a functional block diagram of the first preferred embodiment of the PPG signal processing device of the present invention.

FIG. 2 is a schematic diagram of the application of the present invention to a wearable electronic device.

3A to 3G are output signal waveform diagrams of some functional blocks in FIG. 1 .

FIG. 4A is a partial functional block diagram of the second preferred embodiment of the PPG signal processing device of the present invention.

FIG. 4B is another partial functional block diagram of the second preferred embodiment of the PPG signal processing device of the present invention.

FIG. 5A is a functional block diagram of the first adaptive digital filtering unit in FIG. 1 of the present invention.

FIG. 5B is a functional block diagram of the first adaptive digital filtering unit in FIG. 4A of the present invention.

FIG. 6 is a functional block diagram of the second adaptive digital filtering unit in FIG. 1 of the present invention.

FIG. 7A is a waveform diagram converted from FIG. 3A and FIG. 3D into a frequency domain.

FIG. 7B is a frequency-domain waveform diagram converted from FIG. 3A and FIG. 3G .

FIG. 7C is a frequency-domain waveform diagram converted from FIG. 3A , FIG. 3D and FIG. 3G .

FIG. 8 is a time domain waveform diagram of the heartbeat frequency obtained by converting the frequency domain waveform diagram of FIG. 3G in FIG. 7C .

FIG. 9A is a time-domain waveform diagram of measuring a physiological characteristic signal of a human body.

FIG. 9B is a waveform diagram converted from FIG. 9A into a frequency domain.

FIG. 9C is a time-domain waveform diagram of the heartbeat frequency obtained according to FIG. 9B .

FIG. 9D is a time-domain wave diagram of a normal heartbeat frequency.

Among them, reference signs:

10PPG signal extraction unit 11 first bandpass filter

12 first normalizer 20 motion information acquisition unit

20a Three-axis power sensor 21 Second DC level adjustment unit

21a second normalizer 22 delay circuit

30 The first adaptive digital filter unit

301 first finite impulse response digital filter unit

302 subtractor 303 weight adjustment unit

31 First error convergence coefficient automatic adjustment unit 32 Extreme value removal unit

33 second bandpass filter 34 third normalizer

40 second adaptive digital filtering unit

401 second finite impulse response digital filter unit

402 subtractor 403 weight adjustment unit

41 The second error convergence coefficient automatic adjustment unit

50 wrist 51 blood vessels

60 Wearable Electronic Devices

detailed description

The present invention is mainly aimed at a light volume change description waveform (PPG) signal that reflects the physiological signal of a human body, and a processing device and method thereof. The following examples illustrate the PPG signal processing device and method of the present invention in detail technical content.

First please refer to Fig. 1, which is a functional block diagram of a preferred embodiment of the PPG signal processing device of the present invention, which includes a PPG signal acquisition unit 10, a motion information acquisition unit 20, a first adaptability Digital filter unit 30 and a second adaptive digital filter unit 40; wherein the first adaptive digital filter unit 30 is electrically connected to the PPG signal acquisition unit 10 and the motion information acquisition unit 20, the second adaptive The adaptive digital filtering unit 40 is electrically connected to the first adaptive digital filtering unit 30 .

Please refer to FIG. 2, if the above-mentioned PPG signal acquisition unit 10 is applied to a wearable electronic device 60 such as an electronic watch, light-emitting elements such as infrared light elements, green light elements, red light elements or laser elements can be used. The blood vessel 51 of the wrist 50 is irradiated to obtain a first PPG signal PPG corresponding to the contraction of the blood vessel 51 (as shown in FIG. 3A ). However, the human body activity is not static when the wrist is detected, so the first PPG signal PPG contains interference signals with motion artifacts, that is, as shown in FIG. 7A, when the first PPG signal PPG in FIG. 3A is fast Fourier transformed (FFT ) to a frequency-domain waveform diagram, the frequency-domain waveform contains two obvious peaks, which are respectively the heartbeat signal S _heart and the interference signal S _motion of motion artifacts.

As shown in Figure 1, when the first PPG signal PPG is used to detect specific physiological signals (such as heartbeat) of the human body, since the human heartbeat signal has a specific frequency range, the PPG signal acquisition unit 10 can first The output first PPG signal PPG is output to a first band-pass filter 11, and the first band-pass filter 11 will filter out the noise outside the frequency range of the heartbeat signal from the first PPG signal PPG, and then pass the band-pass filter The filtered first PPG signal PPG_F (as shown in FIG. 3B ) is then output to a first normalizer 12, and the first PPG signal PPG_C after adjusting the scale range of the band-pass filtered first PPG signal PPG_F (as shown in FIG. 3C ), and then output to the first adaptive digital filtering unit 30 . In addition, the first normalizer 12 can also use a signal adjustment element such as a first DC level adjustment unit to adjust the DC level of the band-pass filtered first PPG signal PPG_F.

As shown in FIG. 1, the above-mentioned motion information extraction unit 20 is used to capture the motion information of the wrist, especially to simultaneously capture the motion information M during the period of capturing the first PPG signal PPG. The motion information extraction unit 20 is output to a second DC level adjustment unit 21 and a delay circuit 22 to adjust the DC level and delay for a period of time before outputting to the first adaptive digital filter unit 30 . In this embodiment, as shown in FIG. 4A , the motion information acquisition unit 20 uses a three-axis dynamic sensor 20a, so the motion information M includes the motion information X of the first axis, the second axis, and the third axis. , Y, Z. In addition, the first-axis, second-axis, and third-axis calculation information X, Y, and Z output by the three-axis power sensor 20a can be preferably sequentially output to a second DC level adjustment unit 21 and a The delay circuit 22 adjusts the DC level of the scale range and delays for a period of time before outputting to the first adaptive digital filter unit 30 . In addition, the second DC level adjustment unit 21 and a delay circuit 22 can be replaced by a second normalizer 21a, that is, as shown in FIG. 4B, the first axis, second The operation information X, Y, and Z of the axis and the third axis can preferably be respectively output to the second normalizer 21 a in order to adjust its scale range, and then output to the first adaptive digital filter unit 30 .

The first adaptive digital filtering unit 30 shown in FIG. 1 obtains the first PPG signal PPG_C that has been band-pass filtered and adjusted with the DC level or scale range, and the motion after the DC level or scale range adjustment. Information M_C, the first adaptive digital filter unit can eliminate most of the motion artifact interference signals contained in the first PPG signal PPG_C according to the motion information M_C, and output a second PPG signal Error_C. In this embodiment, the first adaptive digital filtering unit 30 may preferably use the least square algorithm, and its cost function is: Error_C(k)=PPG_C(k)-m(k); where Error_C(k) is the current error value; PPG_C(k) is the current first PPG signal; m(k) is the value of the current motion information after digital filtering. The least square algorithm can minimize the error value of the first adaptive digital filter unit, so as to eliminate most of the motion artifact interference signals in the first PPG signal.

And this first adaptability digital filtering unit 30 realizes the framework of above-mentioned least square algorithm, as shown in Figure 1 and Figure 5A, it comprises a first finite impulse response digital filtering unit 301, a subtractor 302 and a weight adjustment Unit 303. Wherein the first finite impulse response digital filter unit 301 is connected to the motion information extraction unit 20, digitally filters the motion information m received in sequence and outputs it to the subtractor 302, and the subtractor 302 outputs the first A PPG signal PPG_C is subtracted from the digitally filtered motion information M_C to obtain the error value Error_C. Since the weight adjustment unit 303 is connected to the first finite impulse response digital filter unit 301 and the subtractor 302, the error value after subtraction between the first PPG signal PPG_C and the digitally filtered motion information M_C can be obtained. Error_C to adjust the weight W of the first FIR digital filtering unit 301 for each digital filtering until the error value is minimized and then output the second PPG signal Error_C, as shown in FIG. 3D . Please also refer to FIG. 7A, which is the conversion of the second PPG signal Error_C in FIG. 3D to the frequency domain waveform. Compared with the same conversion to the frequency domain waveform in FIG. 3A, it can be seen that the interference signal S _motion (1) of the motion artifact has been Effectively suppressed, the highest peak in the waveform is the heartbeat signal S _heart (1).

The updating function of the above-mentioned first finite impulse response digital filter 301 is:

m(k+1)=m(k)+w(k)×M_C(k); where m(k+1) is the digitally filtered value of the motion information captured next time, and w(k) is The current weight value of the first FIR digital filter unit, M_C(k), is the current motion information. This weight value is calculated by the following formula:

w(k+1)=w(k)+2×μ×Error_C(k)×X_C(k); wherein w(k+1) is the next weight value of the first finite impulse response digital filter unit, μ is the error convergence coefficient.

Please refer to FIG. 4A and FIG. 5B again, the present embodiment is a motion information acquisition unit using a three-axis dynamic sensor 20a, and the three-axis dynamic sensor 20a is connected with three first finite impulse response digital filter units 301, And the current error value of the first adaptive digital filtering unit 30a is:

Error_C(k)=PPG_C(k)-y_0(k)-y_1(k)-y_2(k), and the update functions of each of the first finite impulse response digital filter units 301 are as follows:

y_0(k+1)=y_0(k)+w_0(k)×X_C(k);

y_1(k+1)=y_1(k)+w_1(k)×Y_C(k);

y_2(k+1)=y_2(k)+w_2(k)×Z_C(k); where:

X_C(k) is the current movement information of the first axis;

y_0(k+1) is the value after digital filtering of the first axis motion information next time;

Y_C(k) is the current movement information of the second axis;

y_1(k+1) is the digitally filtered value of the second axis motion information next time;

Z_C(k) is the current movement information of the third axis;

y_2(k+1) is the digitally filtered value of the next piece of motion information of the third axis.

In addition, in order to enable the error convergence coefficient of the first adaptive digital filter unit 30 to be dynamically adjusted and speed up the speed of error minimization, as shown in FIG. 1 , a first error convergence coefficient automatic adjustment unit 31 may be further included, It includes the following steps to dynamically generate the error convergence coefficient:

(a) obtaining its vector value from the first PPG signal;

(b) converting the first PPG signal into a matrix, and obtaining the inner product of the matrix and the transposed matrix to obtain the strength of the first PPG signal;

(c) setting a first-in-first-out buffer;

(d) continuously obtaining the product of step (b) from the FIFO buffer; and

(e) Selecting the value greater than 0 and the reciprocal of the maximum value in the buffer as the error convergence coefficient; wherein the maximum value is the maximum product in the first-in-first-out buffer.

As shown in FIG. 1 again, although a second PPG signal Error_C output by the above-mentioned first adaptive digital filtering unit 20 can filter out most of the interference signals of motion artifacts, there are still other interference signals, so further The second PPG signal Error_C is sequentially output to an extreme value removal unit 32, a second bandpass filter 33, and a third normalizer 34, and a critical value is set by the extreme value removal unit 32, and the time In the second PPG signal Error_C under the domain, the abnormal value whose energy is greater than the critical value is eliminated, and then the noise (as shown in Figure 3E) outside the frequency range of the heartbeat signal is filtered by the second bandpass filter 33, and finally through the third The normalizer 34 normalizes the energy of the second PPG signal so that its energy is distributed between 1 and −1, as shown in FIG. 3E , so as to increase the working dynamic range of the system, as shown in FIG. 3F .

Next, output the normalized second PPG signal PPG_N to the second adaptive digital filter unit 40 , and output a physiological characteristic signal after improving the signal-to-noise ratio (SNR) of the periodic signal therein. Please refer to FIG. 1 and FIG. 6, in this embodiment, the second adaptive digital filtering unit 40 includes a second finite impulse response digital filtering unit 401, a subtractor 402 and a weight adjustment unit 403; The second finite impulse response digital filtering unit 401 receives the normalized second PPG signal PPG_N through a time delay unit 404 to receive the delayed second PPG signal, and digitally filters the second PPG signal output to the subtractor 402, and the subtractor 402 subtracts the normalized second PPG signal PPG_N received this time from the normalized second PPG signal PPG_N Δ times before this time to output an error value Error_P. The error value Error_P is input to the weight adjustment unit 403, so as to adjust the weight value W_P of the next digital filtering of the second finite impulse response digital filter unit 401 according to the error value; The output signal after digital filtering by the impulse response digital filtering unit 401 is the periodic signal; that is, as shown in FIG. 7B, the periodic signal in FIG. 3G is converted into a frequency domain waveform, and the highest peak of the waveform is still the heartbeat signal S _heart (2) Referring to Fig. 7C again, after comparing the frequency domain waveforms of Fig. 3D conversion in Fig. 7A, it is found that the peak value of the periodic signal S _heart (2) in Fig. 3G in the frequency domain waveform is higher than that in Fig. The peak value of the frequency domain waveform is higher than S _d ; therefore, after the normalized second PPG signal Error_C is processed by the second adaptive digital filter unit 40, the signal-to-noise ratio of the periodic signal S _heart (2) can indeed be reduced to (SNR) improved.

In this embodiment, the periodic signal output by the second finite impulse response digital filter unit 401 is: PPG_P(k+1)=PPG_P(k)+w_P(k)×PPG_N(k-Δ); : PPG_P(k+1) is the value of the periodic signal after digital filtering next time; PPG_P(k) is the value of the current periodic signal after digital filtering; w_P(k) is the digital filtering of the finite impulse response this time The weight value of the unit; PPG_N(k-Δ) is the second PPG signal Δ times before this time. And the weight value of this second adaptive digital filtering unit is: w_P(k+1)=w_P(k)+2×μ×Error_P(k)×PPG_N(k-Δ); wherein w_P(k+1) is the weight value of the finite impulse response digital filter unit next time; μ is the error convergence coefficient; and Error_P(k) is the current error value. The error value of the second adaptive digital filtering unit is: Error_P(k)=PPG_N(k)−PPG_P(k); where PPG_N(k) is the current second PPG signal. Therefore, when the error is close to 0, the periodic signal output by the second finite impulse response digital filter unit is close to the actual physiological characteristic signal (heartbeat frequency), so the heartbeat frequency can be calculated according to the periodic signal.

As shown in Figure 1, in order to make the error convergence coefficient of the second adaptive digital filtering unit 30 dynamically adjustable, to speed up the speed of error minimization, it can also further include a second error convergence coefficient automatic adjustment unit 41, It consists of the following steps:

(a) obtaining its vector value from the second PPG signal;

(b) converting the second PPG signal into a matrix, and inner producting the matrix with a transposed matrix to obtain the strength of the second PPG signal;

(c) setting a first-in-first-out buffer;

(d) continuously obtaining the product of step (b) from the FIFO buffer;

(e) Selecting the reciprocal value greater than 0 and the maximum value in the buffer as the error convergence coefficient; wherein the maximum value is the maximum product in the first-in-first-out buffer.

If you want to use the periodic signal in Figure 3G to calculate the number of heartbeats, the frequency-domain waveform shown in Figure 7B will be obtained after Fast FFT Transformation (FFT) (the X-axis is represented by an index, and the Y-axis is represented by an FFT After energy spectrum), calculate the number of heartbeats per minute F _heart = index × (fs/n) × 60 according to the frequency domain waveform, where fs is the sampling frequency, and n is the number of FFT points. Please refer to FIG. 8, which is the waveform diagram of the calculated heartbeat frequency in the time domain. Compared with the waveform diagram of the heartbeat disturbed by motion artifacts in FIG. 9C, it can be seen that the heartbeat frequency measurement of the present invention is no longer affected by motion. Artifact interference.

It can be seen from the above description that the present invention mainly uses an operation information extraction unit to extract motion information during the acquisition of PPG signals. Since the PPG signals extracted from the human body will contain interference signals with motion artifacts, the first The adaptive digital filtering unit filters most of the motion artifact interference signals from the PPG signal according to the motion information, and then outputs the filtered PPG signal to a second adaptive digital filtering unit to extract Taking the periodic signal in the second PPG signal and improving the signal-to-noise ratio of the periodic signal is used as the basis for reading out the accurate heartbeat signal. Therefore, the PPG signal processing device of the present invention can be applied to a wearable heartbeat detection device to provide correct heartbeat information.

The above descriptions are only preferred embodiments of the present invention, and do not limit the present invention in any form. Although the present invention has been disclosed as above with preferred embodiments, it is not intended to limit the present invention, and any technology in the technical field Personnel, without departing from the scope of the technical solution of the present invention, when the technical content disclosed above can be used to make some changes or modifications to equivalent embodiments with equivalent changes, but any content that does not depart from the technical solution of the present invention, according to the present invention Any simple modifications, equivalent changes and modifications made to the above embodiments by the technical essence still belong to the scope of the technical solution of the present invention.

Claims (21)

1. light change in volume describes a blood processor for waveform, it is characterized in that, comprising:

One smooth change in volume describes waveshape signal acquisition unit, describes waveshape signal in order to capture the first smooth change in volume;

One movable information acquisition unit, in order to capture a movable information;

One first adaptive digital filtering unit, be electrically connected to this light change in volume and describe waveshape signal acquisition unit and this movable information acquisition unit, to receive this first smooth change in volume, waveshape signal and this movable information are described, and according to this movable information, this first smooth change in volume is described the motion artifacts interfering signal that waveshape signal comprises to be eliminated, and export the second smooth change in volume and describe waveshape signal;

One second adaptive digital filtering unit, be electrically connected to this first adaptive digital filtering unit, to receive this second smooth change in volume, waveshape signal is described, and capture this second smooth change in volume and describe cyclical signal in waveshape signal, and after improving the signal to noise ratio of this cyclical signal, export a physiology characteristic signal.

2. light change in volume as claimed in claim 1 describes the blood processor of waveform, and it is characterized in that, this first adaptive digital filtering unit includes:

One first FIR digital filter unit, is electrically connected to this movable information acquisition unit, exports after this movable information of received in sequence is given digital filtering;

One subtractor, connect this light change in volume and describe waveshape signal acquisition unit and this first FIR digital filter unit, this first smooth change in volume is described waveshape signal signal to be subtracted each other with this movable information after digital filtering, describe waveshape signal to export this second smooth change in volume; And

One weight adjustment unit, be connected to this first FIR digital filter unit and this subtractor, according to this first smooth change in volume describe waveshape signal subtracted each other with this movable information after digital filtering after error amount, adjust this first FIR digital filter unit in the weighted value of each digital filtering.

3. light change in volume as claimed in claim 2 describes the blood processor of waveform, it is characterized in that, this first adaptive digital filtering unit uses least square algorithm, and its cost function is:

E [Error_C (k) ²], wherein Error_C (k)=PPG_C (k)-m (k); Wherein:

The error amount that Error_C (k) is this;

PPG_C (k) describes waveshape signal for current first smooth change in volume; And

M (k) is the numerical value of current movable information after digital filtering.

4. light change in volume as claimed in claim 3 describes the blood processor of waveform, and the renewal function of this first finite impulse response digital filter is: m (k+1)=m (k)+w (k) × M_C (k); Wherein:

M (k+1) is the numerical value of this movable information after digital filtering next time captured;

W (k) is this weighted value of this first FIR digital filter unit; And

M_C (k) is current movable information.

5. light change in volume as claimed in claim 4 describes the blood processor of waveform, it is characterized in that, this movable information acquisition unit is three axle electrodynamic induction devices, this movable information includes the first axle, the second axle and three-axis moving information, and this three axles electrodynamic induction device is connected with three the first FIR digital filter unit; Wherein:

This error amount of this first adaptive digital filtering unit is:

Error_C(k)＝PPG_C(k)-y_0(k)-y_1(k)-y_2(k)；

Respectively the renewal function of this first finite impulse response digital filter is respectively:

y_0(k+1)＝y_0(k)+w_0(k)×X_C(k)；

y_1(k+1)＝y_1(k)+w_1(k)×Y_C(k)；

Y_2 (k+1)=y_2 (k)+w_2 (k) × Z_C (k); Wherein:

X_C (k) is current first axle movable information;

Y_0 (k+1) is the numerical value of this first axle movable information after digital filtering next time;

Y_C (k) is current second axle movable information;

Y_1 (k+1) is the numerical value of this second axle movable information after digital filtering next time;

Z_C (k) is current three-axis moving information;

Y_2 (k+1) is the numerical value of this three-axis moving information of next record after digital filtering.

6. light change in volume as claimed in claim 4 describes the blood processor of waveform, and it is characterized in that, this weighted value is by following formulae discovery:

W (k+1)=w (k)+2 × μ × Error_C (k) × X_C (k); Wherein:

W (k+1) is the weighted value next time of this first FIR digital filter unit; And

μ is error convergence coefficient.

7. light change in volume as claimed in claim 6 describes the blood processor of waveform, it is characterized in that, this the first adaptive digital filtering unit includes the automatic adjustment unit of one first error convergence coefficient further, and it comprises the step of following this error convergence coefficient of dynamic generation:

A, describe waveshape signal by this first smooth change in volume and obtain its vector value;

B, this first smooth change in volume is described waveshape signal be converted to matrix, and obtain the inner product of this matrix and transposed matrix, to obtain the intensity that this first smooth change in volume describes waveshape signal;

C, set a first-in first-out type relief area;

D, in this first-in first-out type relief area, obtain continuously the product of step b;

E, selection is greater than 0 and the numerical value reciprocal of maximum is this error convergence coefficient in relief area; Wherein this maximum is the max product in this first-in first-out type relief area.

8. light change in volume as claimed in claim 1 describes the blood processor of waveform, and it is characterized in that, this second adaptive digital filtering unit includes:

One second FIR digital filter unit, this the first adaptive digital filtering unit is connected to through a time delay unit, describe waveshape signal to receive this second smooth change in volume, and this second smooth change in volume is described after waveshape signal gives digital filtering export this physiological feature signal;

One subtractor, connect this first adaptive digital filtering unit and this second FIR digital filter unit, sequentially this first smooth change in volume is described waveshape signal to describe waveshape signal with corresponding the second smooth change in volume through digital filtering and subtracted each other, to export an error amount; And

One weight adjustment unit, be connected to this second FIR digital filter unit and this subtractor, according to this second smooth change in volume describe waveshape signal and received wherein second smooth change in volume before this describe waveshape signal subtracted each other after error amount, adjust the weighted value of each digital filtering of this second FIR digital filter unit.

9. light change in volume as claimed in claim 8 describes the blood processor of waveform, it is characterized in that, this cyclical signal that this second FIR digital filter unit exports is:

PPG_P (k+1)=PPG_P (k)+w_P (k) × PPG_N (k-Δ); Wherein:

PPG_P (k+1) is the numerical value of this cyclical signal after digital filtering next time;

PPG_P (k) is the numerical value of current cyclical signal after digital filtering;

W_P (k) is the weighted value of this this FIR digital filter unit; And

Second smooth change in volume that PPG_N (k-Δ) is Δ before this time describes waveshape signal.

10. light change in volume as claimed in claim 9 describes the blood processor of waveform, and it is characterized in that, the weighted value of this second adaptive digital filtering unit is:

W_P (k+1)=w_P (k)+2 × μ × Error_P (k) × PPG_N (k-Δ); Wherein

W_P (k+1) is the weighted value of this FIR digital filter unit next time;

μ is this error convergence coefficient; And

Error_P (k) is this error amount.

11. light change in volume as claimed in claim 10 describe the blood processor of waveform, and the error amount of this second adaptive digital filtering unit is: Error_P (k)=PPG_N (k)-PPG_P (k); Wherein:

PPG_N (k) describes waveshape signal for current second smooth change in volume.

12. light change in volume as claimed in claim 11 describe the blood processor of waveform, it is characterized in that, this the first adaptive digital filtering unit includes the automatic adjustment unit of one first error convergence coefficient further, and it comprises following steps and produces dynamic error convergence coefficient:

A, describe waveshape signal by this first smooth change in volume and obtain its vector value;

B, this first smooth change in volume is described waveshape signal be converted to matrix, and the inner product to this matrix and a transposed matrix, to obtain the intensity that this first smooth change in volume describes waveshape signal;

C, set a first-in first-out type relief area;

D, in this first-in first-out type relief area, obtain continuously the product of step b;

E, select to be greater than 0 and the numerical value of the inverse of maximum in relief area is this error convergence coefficient; Wherein this maximum is the max product in this first-in first-out type relief area.

13. light change in volume as claimed in claim 11 describe the blood processor of waveform, it is characterized in that, this the second adaptive digital filtering unit includes the automatic adjustment unit of one second error convergence coefficient further, and it comprises following steps and produces dynamic error convergence coefficient:

A, describe waveshape signal by this second smooth change in volume and obtain its vector value;

B, this second smooth change in volume is described waveshape signal be converted to matrix, and the inner product to this matrix and a transposed matrix, to obtain the intensity that this second smooth change in volume describes waveshape signal;

C, set a first-in first-out type relief area

D, in this first-in first-out type relief area, obtain continuously the product of step b;

E, selection is greater than 0 and the numerical value of the inverse of maximum is this error convergence coefficient in relief area; Wherein this maximum is the max product in this first-in first-out type relief area.

14. describe the blood processor of waveform as the light change in volume as described in arbitrary in claim 1 to 13, it is characterized in that, this light change in volume describes waveshape signal acquisition unit and is sequentially connected to this first adaptive digital filtering unit through one first band filter and one first direct current level adjustment unit further, or is sequentially connected to this first adaptive digital filtering unit through this first band filter and one first normalization further.

15. describe the blood processor of waveform as the light change in volume as described in arbitrary in claim 1 to 13, it is characterized in that, this movable information acquisition unit is connected to this first adaptive digital filtering unit through one second direct current level adjustment unit and a delay circuit further, or is connected to this first adaptive digital filtering unit through one second normalizer further.

16. describe the blood processor of waveform as the light change in volume as described in arbitrary in claim 1 to 13, it is characterized in that, this first adaptive digital filtering unit sequentially goes extremum unit, one second band filter and one the 3rd normalizer to be connected to this second adaptive digital filtering unit through one further.

17. 1 kinds of light change in volume describe the processing method of waveform, it is characterized in that, comprising:

A, acquisition one first smooth change in volume describe waveshape signal and movable information;

B, according to this movable information, this first smooth change in volume is described waveshape signal and comprise motion artifacts interfering signal and eliminated, and export one second smooth change in volume and describe waveshape signal;

C, capture this second smooth change in volume and describe a cyclical signal in waveshape signal, and after improving the signal to noise ratio of this cyclical signal, export a physiology characteristic signal.

18. light change in volume as claimed in claim 17 describe the processing method of waveform, it is characterized in that, in this step b, use one first adaptive digital filter to eliminate the motion artifacts interfering signal that this first smooth change in volume describes waveshape signal.

19. light change in volume as claimed in claim 18 describe the processing method of waveform, it is characterized in that, use this first adaptive digital filter to eliminate in this step b motion artifacts interfering signal that this first smooth change in volume describes waveshape signal, comprises following steps:

B1, this movable information is given digital filtering after export;

B2, this first smooth change in volume is described waveshape signal subtracted each other with the corresponding movable information through digital filtering, describe waveshape signal to export this second smooth change in volume; And

B3, to describe according to this first smooth change in volume waveshape signal subtracted each other with the corresponding movable information through digital filtering after error amount, adjust this first adaptive digital filter in the weighted value of each digital filtering.

20. describe the processing method of waveform as the light change in volume as described in arbitrary in claim 17 to 19, it is characterized in that, the noise using this second smooth change in volume of this second adaptive digital filter numeral filtering to describe waveshape signal in this step c to comprise, describe this cyclical signal in waveshape signal to capture this second smooth change in volume, comprise following steps:

C1, this second smooth change in volume described after waveshape signal gives digital filtering export this physiological feature signal;

C2, this first smooth change in volume described waveshape signal and describe waveshape signal with corresponding the second smooth change in volume through digital filtering and subtracted each other, to export an error amount; And

C3, to describe according to this second smooth change in volume waveshape signal and wherein one second smooth change in volume received before this describe waveshape signal subtracted each other after error amount, adjust this second adaptive digital filter in the weighted value of each digital filtering.

21. light change in volume as claimed in claim 20 describe the processing method of waveform, it is characterized in that, respectively an error convergence coefficient of this first and second adaptive digital filter is dynamic error convergence coefficient.