TWI894027B - Rehabilitation assistance system - Google Patents

Abstract

A rehabilitation assistance system includes a rehabilitation device, a sensing network, a sensing device and an interactive interface. The rehabilitation device is worn on an affected hand of a patient and is configured to drive the affected hand to perform elbow joint rehabilitation movements, metacarpophalangeal joint rehabilitation movements, and wrist joint rehabilitation movements. The sensing network includes a first inertial sensing module configured to measure a first inertial sensing signal. The sensing device includes a second inertial sensing module configured to measure a second inertial sensing signal, a physiological signal sensor configured to measure a physiological signal of the patient. The first inertial sensing module and the second inertial sensing module are further configured to measure a third inertial sensing signal. The interactive interface includes a memory for storing these inertial sensing signals and the physiological signal, and a processor configured to receive and send a rehabilitation instruction to the rehabilitation device according to a control instruction of the patient.

Description

Rehabilitation Assistance System

The present invention relates to an assistive system, and more particularly to a rehabilitation assistive system.

Stroke patients experience significant impacts on limb control, body function, walking balance, and quality of life. Currently, most clinical home rehabilitation facilities focus on single-joint movements. In practice, these boring and repetitive exercises often cause stroke patients to abandon their home rehabilitation halfway, thus losing optimal rehabilitation effectiveness. Furthermore, traditional home rehabilitation facilities are unable to automatically and fully collect the rehabilitation movements and physiological information of stroke patients during rehabilitation, making it difficult for caregivers to understand the entire rehabilitation process, and medical staff are unable to assess the rehabilitation status of stroke patients in real time.

The purpose of this invention is to provide a rehabilitation assistance system that integrates rehabilitation devices, a sensor network, sensor devices, and an interactive interface to assist stroke patients in performing elbow, metacarpophalangeal, and wrist rehabilitation on the affected hand. The system also offers two rehabilitation modes: self-directed mirror rehabilitation and remote home rehabilitation, allowing patients to choose the appropriate rehabilitation method. Furthermore, medical staff and family members can monitor the patient's physiological status in real time during rehabilitation through a rehabilitation network platform or mobile device application.

One aspect of the present invention is to provide a rehabilitation assistance system comprising a rehabilitation device, a sensing network, a sensing device, and an interactive interface. The rehabilitation device is worn on the operator's affected hand and is configured to guide the affected hand in performing elbow, metacarpophalangeal, and wrist rehabilitation exercises. The sensing network comprises a first inertia sensing module for measuring a first inertia sensing signal and a first wireless radio frequency transmission module. The sensing device comprises a second inertia sensing module for measuring a second inertia sensing signal, a physiological signal sensor for measuring the operator's physiological signals, and a second wireless radio frequency transmission module. The first and second inertial sensing modules are further configured to measure a third inertial sensing signal, which is then transmitted by the first and second wireless radio frequency transmission modules. The interactive interface includes a memory for storing the first, second, and third inertial sensing signals, as well as physiological signals, and a processor for receiving and transmitting rehabilitation commands to the rehabilitation device based on operator control commands.

In some embodiments, the rehabilitation device includes an elbow joint rehabilitation device, a metacarpophalangeal joint rehabilitation device, and a wrist joint rehabilitation device.

In some embodiments, the first inertial sensing signals include an upper arm acceleration signal, an upper arm angular velocity signal, an upper arm magnetic signal, a forearm acceleration signal, a forearm angular velocity signal, and a forearm magnetic signal. The processor is further configured to use a rehabilitation posture measurement algorithm to process the upper arm acceleration signal, the upper arm angular velocity signal, and the upper arm magnetic signal to obtain an upper arm rehabilitation posture angle, and to use a rehabilitation posture measurement algorithm to process the forearm acceleration signal, the forearm angular velocity signal, and the forearm magnetic signal to obtain a forearm rehabilitation posture angle.

In some embodiments, the processor is further configured to process the upper arm rehabilitation posture angle and the forearm rehabilitation posture angle using a joint angle measurement algorithm to calculate the elbow joint angle, wherein the elbow joint angle is obtained by subtracting the upper arm rehabilitation posture angle from the forearm rehabilitation posture angle.

In some embodiments, the second inertial sensing signals include phalange acceleration signals, phalange angular velocity signals, phalange magnetic signals, back of hand acceleration signals, back of hand angular velocity signals, and back of hand magnetic signals. The processor is further configured to use a rehabilitation posture measurement algorithm to process the phalange acceleration signals, phalange angular velocity signals, and phalange magnetic signals to obtain a phalange rehabilitation posture angle, and to use a rehabilitation posture measurement algorithm to process the finger and back of hand acceleration signals, back of hand angular velocity signals, and back of hand magnetic signals to obtain a back of hand rehabilitation posture angle.

In some embodiments, the processor is further configured to process the phalangeal rehabilitation posture angle and the hand back rehabilitation posture angle using a joint angle measurement algorithm to calculate the metacarpophalangeal joint angle, wherein the metacarpophalangeal joint angle is obtained by subtracting the hand back rehabilitation posture angle from the phalangeal rehabilitation posture angle.

In some embodiments, the processor is further configured to process the forearm rehabilitation posture angle and the hand back rehabilitation posture angle using a joint angle measurement algorithm to calculate the wrist joint angle, wherein the wrist joint angle is obtained by subtracting the forearm rehabilitation posture angle from the hand back rehabilitation posture angle.

In some embodiments, the processor is further configured to receive at least one control instruction from a remote controller and send at least one rehabilitation instruction to the rehabilitation device according to the control instruction.

In some embodiments, the processor is further configured to process the physiological signal using a physiological emergency stop mechanism algorithm, and control the rehabilitation device to stop moving when it is determined that the physiological parameter of the physiological signal exceeds the normal physiological parameter range.

In some embodiments, the control instructions include an instruction for setting an elbow joint rehabilitation angle, an instruction for setting a metacarpophalangeal joint rehabilitation angle, and an instruction for setting a wrist joint rehabilitation angle.

In some embodiments, the processor is further configured to store the first inertial sensing signals, the second inertial sensing signals, the third inertial sensing signals, and the physiological signals in a cloud database.

The following detailed description discusses embodiments of the present invention. It will be appreciated that the embodiments provide numerous applicable concepts that can be implemented in a wide variety of specific contexts. The embodiments discussed and disclosed are for illustrative purposes only and are not intended to limit the scope of the present invention.

It should be understood that although the terms "first," "second," etc. may be used in the present disclosure to describe various elements, these terms should not limit these elements. These terms are only used to distinguish one element from another.

FIG1 is a functional block diagram of a rehabilitation assistance system 100 according to an embodiment of the present invention. The rehabilitation assistance system 100 is suitable for use by a user performing rehabilitation and includes a rehabilitation device 110, a sensor network 120, a sensor device 130, and an interactive interface 140. The interactive interface 140 further includes a memory 142 and a processor 144.

The rehabilitation device 110 is worn on the affected hand of a patient (hereinafter referred to as the operator of the rehabilitation device 110 ) to perform rehabilitation exercises. In one embodiment of the present invention, if the operator's affected hand is the left hand, the rehabilitation device 110 is worn on the operator's left hand to perform rehabilitation exercises for the affected part of the left hand. Specifically, the rehabilitation device 110 is used to move the operator's left elbow joint for left elbow rehabilitation exercises, move the operator's left metacarpophalangeal joint for left metacarpophalangeal joint rehabilitation exercises, and move the operator's left wrist joint for left wrist rehabilitation exercises. In another embodiment of the present invention, if the operator's affected hand is the right hand, the rehabilitation device 110 is worn on the operator's right hand to perform rehabilitation exercises for the affected part of the right hand. Specifically, the rehabilitation device 110 is used to drive the operator's right elbow joint to perform right elbow joint rehabilitation exercises, drive the operator's right metacarpophalangeal joint to perform right metacarpophalangeal joint rehabilitation exercises, and drive the operator's right wrist joint to perform right wrist joint rehabilitation exercises.

The rehabilitation device includes an elbow joint rehabilitation device, a metacarpophalangeal joint rehabilitation device, and a wrist joint rehabilitation device. In one embodiment of the present invention, the entire device, including the elbow joint rehabilitation device, the metacarpophalangeal joint rehabilitation device, and the wrist joint rehabilitation device, can be placed on a movable chair, making the entire device conveniently movable, allowing rehabilitation to be performed at any location according to the operator's preference, providing the operator with a more comfortable rehabilitation environment.

FIG2 is a schematic diagram of an elbow joint rehabilitation device 111 using the rehabilitation assistance system 100 according to an embodiment of the present invention. The elbow joint rehabilitation device 111 further includes a forearm mechanical structure 111-1, an upper arm mechanical structure 111-2, a high-torque DC reduction motor 111-3, and an incremental rotary encoder 111-4. In one embodiment of the present invention, when an operator uses an elbow joint rehabilitation device 111 for rehabilitation, the operator's affected arm can be fixed via the forearm mechanical structure 111-1 and the upper arm mechanical structure 111-2, driving the high-torque DC reduction motor 111-3 to perform elbow flexion/extension. Furthermore, the incremental rotary encoder 111-4 can calculate the elbow joint drive angle by measuring the square wave pulse signal generated by the elbow joint rotation, and feedback control the high-torque DC reduction motor 111-3 to achieve the correct elbow joint rehabilitation angle. It should be noted that, considering the human elbow joint motion angle and the extreme motion angle of the elbow joint rehabilitation device 111, the motion angle range of the elbow joint rehabilitation device 111 is set to 105° to 0° of flexion/extension. This means that when the operator uses the elbow joint rehabilitation device 111 for rehabilitation, the elbow joint motion angle range is 105° to 0° of flexion/extension.

FIG3 is a schematic diagram of a metacarpophalangeal joint rehabilitation device 112 using the rehabilitation assistance system 100 according to an embodiment of the present invention. The metacarpophalangeal joint rehabilitation device 112 further includes a 3D printed metacarpophalangeal joint mechanism 112 - 1 , a thin film potentiometer 112 - 2 , and a pneumatic cylinder 112 - 3 . In one embodiment of the present invention, when an operator uses the metacarpophalangeal joint rehabilitation device 112 for rehabilitation, the 3D-printed metacarpophalangeal joint mechanism 112-1 can be used to fix the operator's affected metacarpophalangeal joint and drive the pneumatic cylinder 112-3 to perform metacarpophalangeal joint bending. The thin film potentiometer 112-2 is used to measure the travel distance of the pneumatic cylinder 112-3 and further convert it into a metacarpophalangeal joint rehabilitation angle, and feedback control the pneumatic cylinder 112-3 to achieve the correct metacarpophalangeal joint rehabilitation angle. It should be noted that, considering the human metacarpophalangeal joint motion angle and the extreme motion angle of the metacarpophalangeal joint rehabilitation device 112, the range of the motion angle of the metacarpophalangeal joint rehabilitation device 112 is set to bend from 60° to 0°, which means that when the operator uses the metacarpophalangeal joint rehabilitation device 112 for rehabilitation, the range of the metacarpophalangeal joint motion angle is bend from 60° to 0°.

Referring to Figures 2 and 3 , in one embodiment of the present invention, a wrist joint rehabilitation device utilizing the rehabilitation assistance system 100 can be implemented by combining the elbow joint rehabilitation device 111 shown in Figure 2 with the metacarpophalangeal joint rehabilitation device 112 shown in Figure 3 . The wrist joint rehabilitation device includes a forearm mechanical structure 111-1, a 3D-printed metacarpophalangeal joint mechanism 112-1, a high-torque DC reduction motor, and an incremental rotary encoder. It should be noted that the high torque DC reduction motor of the wrist joint rehabilitation device is not the high torque DC reduction motor 111-3 shown in FIG2 , but another high torque DC reduction motor (not shown in FIG2 ). In other words, the high torque DC reduction motor 111-3 of the elbow joint rehabilitation device 111 and the high torque DC reduction motor of the wrist joint rehabilitation device are two different high torque DC reduction motors that exist simultaneously in the rehabilitation assistance system 100. speed motor; in addition, the incremental rotary encoder of the wrist joint rehabilitation device is not the incremental rotary encoder 111-4 shown in FIG2 , but another incremental rotary encoder (not shown in FIG2 ). In other words, the incremental rotary encoder 111-4 of the elbow joint rehabilitation device 111 and the incremental rotary encoder of the wrist joint rehabilitation device are two different incremental rotary encoders that exist simultaneously in the rehabilitation assistance system 100. In one embodiment of the present invention, when an operator uses a wrist joint rehabilitation device for rehabilitation, the forearm mechanical structure 111-1 and the 3D-printed metacarpophalangeal joint mechanism 112-1 can be used to fix the operator's affected arm and back of the hand and drive a high-torque DC deceleration motor to perform wrist flexion/extension. The incremental rotary encoder can calculate the wrist joint drive angle by measuring the square wave pulse signal generated during wrist joint rotation, and feedback control the high-torque DC deceleration motor to achieve the correct wrist joint rehabilitation angle. It should be noted that, taking into account the human wrist joint motion angle and the extreme motion angle of the wrist joint rehabilitation device, the motion angle range of the wrist joint rehabilitation device is set to 80° to 0° of flexion/extension. This means that when the operator uses the wrist joint rehabilitation device for rehabilitation, the wrist joint motion angle range is 80° to 0° of flexion/extension.

In some embodiments, the rehabilitation device 110 is further provided with an emergency stop switch. If the operator feels unwell or the rehabilitation device 110 malfunctions during rehabilitation, the emergency stop switch can be used to immediately stop the operation of the rehabilitation device 110.

The sensing network 120 can be installed on the operator's healthy hand (i.e., the non-affected hand). In one embodiment of the present invention, the sensing network 120 can be installed on the operator's upper arm and forearm in the form of a strap, and the tightness of the strap around the upper arm and forearm can be adjusted appropriately. In some embodiments, the strap can be secured to the upper arm and forearm using a Velcro strap or a buckle. The sensing network 120 includes a first inertia sensing module (not shown) and a first wireless radio frequency transmission module (not shown). The first inertia sensing module is used to measure elbow joint rehabilitation movements to obtain the operator's first inertia sensing signal, and the first wireless radio frequency transmission module is used to transmit the first inertia sensing signal measured by the first inertia sensing module. In some embodiments, the first inertia sensing module includes, but is not limited to, an accelerometer, a gyroscope, or a magnetometer. The first inertia sensing signal further includes upper arm acceleration and forearm acceleration signals measured by the accelerometer, upper arm angular velocity and forearm angular velocity signals measured by the gyroscope, and/or upper arm magnetic force and forearm magnetic force signals measured by the magnetometer.

The sensing device 130 can be placed on the operator's unaffected hand. In the embodiment shown in FIG4 , the sensing device 130 is a sensing glove. The sensing device 130 includes a second inertia sensing module 131, a physiological signal sensor 132, and a second wireless radio frequency transmission module. The second inertia sensing module 131 is used to measure the operator's metacarpophalangeal joint rehabilitation movements to obtain a second inertia sensing signal. The physiological signal sensor 132 is used to measure the operator's physiological signals (including the operator's skin temperature, heart rate, and/or blood oxygen concentration). The second wireless radio frequency transmission module is used to transmit the second inertia sensing signal measured by the second inertia sensing module 131 and the operator's physiological signals measured by the physiological signal sensor 132. In some embodiments, the second inertia sensing module 131 includes, but is not limited to, an accelerometer, a gyroscope, or a magnetometer. The second inertia sensing signal further includes phalange acceleration signals and hand back acceleration signals measured by the accelerometer, phalange angular velocity signals and hand back angular velocity signals measured by the gyroscope, and/or phalange magnetic signals and hand back magnetic signals measured by the magnetometer.

The first inertia sensing module in the sensing network 120 and the second inertia sensing module 131 in the sensing device 130 are further configured to measure wrist rehabilitation movements to obtain a third inertia sensing signal of the operator. This third inertia sensing signal is transmitted by the first and second wireless RF transmission modules. The third inertia sensing signal further includes forearm acceleration signals and hand back acceleration signals measured by an accelerometer, forearm angular velocity signals and hand back angular velocity signals measured by a gyroscope, and/or forearm magnetic force signals and hand back magnetic force signals measured by a magnetometer.

The interactive interface 140 is coupled to the rehabilitation device 110, the sensing network 120, and the sensing device 130, and is configured to receive and display a first inertial sensing signal measured by the first inertial sensing module, a second inertial sensing signal measured by the second inertial sensing module 131, a third inertial sensing signal measured by the first inertial sensing module and the second inertial sensing module 131, and a physiological signal measured by the physiological signal sensor 132.

The interactive interface 140 includes a memory 142, which is configured to store a first inertial sensing signal, a second inertial sensing signal, a third inertial sensing signal, and physiological signals, namely, an upper arm acceleration signal, an upper arm angular velocity signal, an upper arm magnetic signal, a forearm acceleration signal, a forearm angular velocity signal, a forearm magnetic signal, a phalange acceleration signal, a phalange angular velocity signal, a phalange magnetic signal, a back of hand acceleration signal, a back of hand angular velocity signal, a back of hand magnetic signal, an elbow joint angle, a wrist joint angle, a metacarpophalangeal joint angle, skin temperature, heart rate, blood oxygen concentration, etc., but is not limited thereto. The memory 142 may be a high-speed random access memory and may also include non-volatile memory, such as a hard drive, a plug-in hard drive, a smart media card (SMC), a secure digital (SD) card, a flash memory card, at least one magnetic disk memory device, a flash memory device, or other non-volatile solid-state memory device.

The interactive interface 140 includes a processor 144 configured to receive control commands from an operator and send rehabilitation commands to the rehabilitation device 110 based on the received control commands. In one embodiment of the present invention, the control commands include, but are not limited to, commands for setting elbow joint rehabilitation angles, commands for setting metacarpophalangeal joint rehabilitation angles, and/or commands for setting wrist joint rehabilitation angles. The processor 144 can be, but is not limited to, a central processing unit (CPU), a graphics processing unit (GPU), a microcontroller unit (MCU), a microprocessor, a system-on-chip (SoC), a digital signal processor (DSP), an application-specific integrated circuit (ASIC), a programmable logic controller (PLC), or a combination of the foregoing.

After the first wireless radio frequency transmission module receives the upper arm acceleration signal, upper arm angular velocity signal, upper arm magnetic force signal, forearm acceleration signal, forearm angular velocity signal, and forearm magnetic force signal measured by the first inertia sensing module, the processor 144 processes the upper arm acceleration signal, the upper arm angular velocity signal, and the upper arm magnetic force signal using a rehabilitation posture measurement algorithm to obtain the upper arm rehabilitation posture angle. Furthermore, the processor 144 also processes the forearm acceleration signal, the forearm angular velocity signal, and the forearm magnetic force signal using the rehabilitation posture measurement algorithm to obtain the forearm rehabilitation posture angle. It should be noted that the rehabilitation posture measurement algorithm is based on, but not limited to, an extended Kalman filter (EKF), an unscented Kalman filter (UKF), a particle filter (PF), or a cubature Kalman filter (CKF).

After obtaining the upper arm rehabilitation posture angle and the forearm rehabilitation posture angle, the processor 144 processes the upper arm rehabilitation posture angle and the forearm rehabilitation posture angle using a joint angle measurement algorithm to calculate the elbow joint angle. Specifically, the processor 144 processes the upper arm rehabilitation posture angle and the forearm rehabilitation posture angle using the joint angle measurement algorithm by subtracting the upper arm rehabilitation posture angle from the forearm rehabilitation posture angle to calculate the elbow joint angle.

After the second wireless radio frequency transmission module receives the phalange acceleration signal, phalange angular velocity signal, phalange magnetic signal, back of hand acceleration signal, back of hand angular velocity signal, and back of hand magnetic signal measured by the second inertia sensing module 131, the processor 144 processes the phalange acceleration signal, phalange angular velocity signal, and phalange magnetic signal using a rehabilitation posture measurement algorithm to obtain the phalange rehabilitation posture angle. Furthermore, the processor 144 also processes the back of hand acceleration signal, back of hand angular velocity signal, and back of hand magnetic signal using a rehabilitation posture measurement algorithm to obtain the back of hand rehabilitation posture angle.

After obtaining the phalangeal rehabilitation posture angles and the back of the hand rehabilitation posture angles, the processor 144 processes these phalangeal rehabilitation posture angles and the back of the hand rehabilitation posture angles using a joint angle measurement algorithm to calculate the metacarpophalangeal joint angle. Specifically, the processor 144 processes these phalangeal rehabilitation posture angles and the back of the hand rehabilitation posture angles using the joint angle measurement algorithm by subtracting the back of the hand rehabilitation posture angle from the phalangeal rehabilitation posture angle to calculate the metacarpophalangeal joint angle.

After obtaining the forearm rehabilitation posture angle and the back of the hand rehabilitation posture angle, the processor 144 processes the forearm rehabilitation posture angle and the back of the hand rehabilitation posture angle using a joint angle measurement algorithm to calculate the wrist joint angle. Specifically, the processor 144 processes the forearm rehabilitation posture angle and the back of the hand rehabilitation posture angle using the joint angle measurement algorithm by subtracting the forearm rehabilitation posture angle from the back of the hand rehabilitation posture angle to calculate the wrist joint angle.

After the physiological signal sensor 132 of the sensing device 130 measures the operator's skin temperature, heart rate, blood oxygen concentration, and other physiological signals, the processor 144 then inserts these physiological signals into the physiological emergency stop mechanism algorithm to determine the operator's physiological condition during rehabilitation. This serves as the basis for the physiological emergency stop control mechanism of the rehabilitation device 110. During the rehabilitation process of the operator using the rehabilitation device 110, if the physiological signal sensor 132 detects an abnormal physiological signal, the processor 144 will issue a stop signal to control the rehabilitation device 110 to stop operation. Specifically, the processor 144 is further configured to utilize a physiological emergency stop mechanism algorithm to process the physiological signal measured by the physiological signal sensor 132, and when it is determined that the physiological parameter of the measured physiological signal exceeds the normal physiological parameter range (i.e., the physiological parameter is greater than the upper limit of the normal physiological parameter range or less than the lower limit of the normal physiological parameter range), the rehabilitation device 110 is controlled to stop operating.

In one embodiment of the present invention, processor 144 uses skin temperature, heart rate, and blood oxygen concentration as input signals for a physiological emergency stop mechanism algorithm. The physiological emergency stop mechanism algorithm uses a machine learning or deep learning neural network model to determine whether one or more of these physiological signals are abnormal (i.e., whether the physiological parameters of the physiological signals exceed the normal physiological parameter range). If processor 144 determines that one or more of these physiological signals are abnormal, it controls rehabilitation device 110 to stop operating. It should be noted that the physiological emergency stop mechanism algorithm can be implemented using a machine learning or deep learning neural network model architecture, but is not limited to this.

FIG5 is a schematic diagram illustrating a scenario in which an operator performs rehabilitation using a rehabilitation device 110 , a sensing network 120 , and a sensing device 130 according to an embodiment of the present invention. In the embodiment shown in FIG5 , the operator's affected hand is the left hand, so the rehabilitation device 110 (including the elbow joint rehabilitation device 111 shown in FIG2 , the metacarpophalangeal joint rehabilitation device 112 shown in FIG3 , and the wrist joint rehabilitation device implemented by combining FIG2 and FIG3 ) can be worn on the operator's left hand. In contrast, the operator's healthy hand is the right hand, so the sensing glove can be worn on the operator's right hand (in the embodiment shown in FIG5 , the sensing device 130 is a sensing glove). The sensing network 120 can be set in the form of a strap on the upper arm and forearm of the operator's healthy hand (i.e., the right upper arm and forearm). The strap can be fixed to the operator's right upper arm and forearm by Velcro or a button.

In the embodiment shown in FIG. 5 , when an operator uses the elbow joint rehabilitation device 111 for rehabilitation, the forearm mechanical structure 111-1 and the upper arm mechanical structure 111-2 can secure the operator's left arm and drive the high-torque DC reduction motor 111-3 to flex and extend the left elbow joint. The incremental rotary encoder 111-4 can calculate the left elbow joint drive angle by measuring the square wave pulse signal generated by the left elbow joint rotation, and feedback control the high-torque DC reduction motor 111-3 to achieve the correct elbow joint rehabilitation angle.

In the embodiment shown in FIG5 , when the operator uses the metacarpophalangeal joint rehabilitation device 112 for rehabilitation, the 3D-printed metacarpophalangeal joint mechanism 112-1 can be used to fix the operator's left metacarpophalangeal joint and drive the pneumatic cylinder 112-3 to perform the left metacarpophalangeal joint bending. The thin film potentiometer 112-2 is used to measure the travel distance of the pneumatic cylinder 112-3 and further convert it into the left metacarpophalangeal joint rehabilitation angle, and feedback control the pneumatic cylinder 112-3 to achieve the correct metacarpophalangeal joint rehabilitation angle.

In the embodiment shown in FIG. 5 , when an operator uses the wrist joint rehabilitation device for rehabilitation, the forearm mechanical structure 111-1 and the 3D-printed metacarpophalangeal joint mechanism 112-1 can be used to secure the operator's left arm and hand and drive a high-torque DC reduction motor (which is different from the high-torque DC reduction motor 111-3 in the elbow joint rehabilitation device 111 and is also present in the rehabilitation assistance system 100). The left wrist joint is flexed/extended, and the incremental rotary encoder (different from the incremental rotary encoder 111-4 of the elbow joint rehabilitation device 111 and another incremental rotary encoder simultaneously present in the rehabilitation assistance system 100) can calculate the left wrist joint driving angle by measuring the square wave pulse signal generated when the left wrist joint rotates, and feedback control the high-torque DC deceleration motor to achieve the correct wrist joint rehabilitation angle.

In some embodiments, the rehabilitation assistance system 100 provides the operator with two rehabilitation modes: autonomous mirror rehabilitation mode and remote home rehabilitation mode, which are described below using the embodiment shown in FIG. 5 .

In the autonomous mirror rehabilitation mode, the sensing network 120 and the sensing device 130 (i.e., the sensing glove) are worn on the operator's right hand (healthy hand), while the rehabilitation device 110 is worn on the operator's left hand (affected hand). The changing angle of the right elbow joint measured by the sensing network 120 is transmitted to the interactive interface 140 via the first wireless radio frequency transmission module. The interactive interface 140 then transmits an autonomous mirror rehabilitation motion signal to the high-torque DC reduction motor 111-3 in the elbow joint rehabilitation device 111 of the rehabilitation device 110, thereby driving the elbow joint rehabilitation device 111. The elbow joint rehabilitation device 111 will drive the operator's left elbow to perform a mirror elbow rehabilitation motion as the angle thereof changes. It should be noted that the set elbow rehabilitation angle of the set elbow rehabilitation angle command sent to the rehabilitation device 110 can be, for example, 105°, 70°, 30°, or 0°, but is not limited thereto. The changing angle of the right metacarpophalangeal joint measured by the sensing glove is transmitted to the interactive interface 140 via the second wireless radio frequency transmission module. The interactive interface 140 then transmits an autonomous mirror rehabilitation motion signal to the pneumatic cylinder 112-3 in the metacarpophalangeal joint rehabilitation device 112 of the rehabilitation device 110 to drive the metacarpophalangeal joint rehabilitation device 112. The metacarpophalangeal joint rehabilitation device 112 will drive the operator's left metacarpophalangeal joint to perform a mirrored left metacarpophalangeal joint rehabilitation motion as the angle changes caused by the driving. It should be noted that the set metacarpophalangeal joint rehabilitation angle of the set metacarpophalangeal joint rehabilitation angle command sent to the rehabilitation device 110 can be, for example, 60°, 42°, 28°, or 0°, but is not limited to these. The angle change of the right wrist joint measured by the sensing network 120 and the sensing glove is transmitted to the interactive interface 140 via the first wireless radio frequency transmission module and the second wireless radio frequency transmission module. The interactive interface 140 then transmits the autonomous mirror rehabilitation motion signal to the high torque DC deceleration motor in the wrist joint rehabilitation device of the rehabilitation device 110 (which is different from and exists simultaneously with the high torque DC deceleration motor 111-3 in the elbow joint rehabilitation device 111). Another high-torque DC deceleration motor in the rehabilitation assist system 100 is used to drive the wrist joint rehabilitation device, and the wrist joint rehabilitation device will drive the operator's left wrist to perform mirror wrist joint rehabilitation movements as the angle generated by the wrist joint rehabilitation device is driven. It should be noted that the set wrist joint rehabilitation angle of the set wrist joint rehabilitation angle command sent to the rehabilitation device 110 can be, for example, 80°, 65°, 30° or 0°, but is not limited to these.

In remote home rehabilitation mode, the sensing network 120 and sensing device 130 (i.e., sensing glove) are worn on the upper limb (left or right hand) of the medical staff performing remote operations, while the rehabilitation device 110 is worn on the operator's affected hand (left or right hand). It should be noted that the hand on which the medical staff wears the sensing network 120 and sensing device 130 and the hand on which the operator wears the rehabilitation device 110 can be the same side or different sides. The rehabilitation angle of the elbow joint set by the medical staff through the sensing network 120 is transmitted to the interactive interface 140 of the medical staff through the first wireless radio frequency transmission module. The rehabilitation network platform transmits the set rehabilitation angle of the elbow joint to the interactive interface 140 of the operator. The interactive interface 140 of the operator transmits the rehabilitation angle of the elbow joint to the high torque DC in the elbow joint rehabilitation device 111. The deceleration motor 111-3 drives the elbow joint rehabilitation device 111, and the elbow joint rehabilitation device 111 will drive the operator's affected hand to perform remote elbow joint rehabilitation movements as the angle generated by the drive changes. It should be noted that the set elbow joint rehabilitation angle of the set elbow joint rehabilitation angle instruction sent to the rehabilitation device 110 can be, for example, 105°, 70°, 30° or 0°, but is not limited to this. The rehabilitation angle of the metacarpophalangeal joint set by the sensing device 130 on the medical staff side is transmitted to the interactive interface 140 on the medical staff side via the second wireless radio frequency transmission module. The rehabilitation network platform transmits the set rehabilitation angle of the metacarpophalangeal joint to the interactive interface 140 on the operator side. The interactive interface 140 on the operator side then transmits the rehabilitation angle of the metacarpophalangeal joint to the air flow control unit in the metacarpophalangeal joint rehabilitation device 112. The cylinder 112-3 drives the metacarpophalangeal joint rehabilitation device 112, and the metacarpophalangeal joint rehabilitation device 112 will drive the operator's affected hand to perform remote metacarpophalangeal joint rehabilitation movements as the angle generated by the driving changes. It should be noted that the set metacarpophalangeal joint rehabilitation angle of the set metacarpophalangeal joint rehabilitation angle command sent to the rehabilitation device 110 can be, for example, 60°, 42°, 28° or 0°, but is not limited to this. The rehabilitation angle of the wrist joint set by the sensing network 120 and the sensing device 130 on the medical staff side is transmitted to the interactive interface 140 on the medical staff side via the first wireless radio frequency transmission module and the second wireless radio frequency transmission module. The set rehabilitation angle of the wrist joint is transmitted to the interactive interface 140 on the operator side via the rehabilitation network platform. The interactive interface 140 on the operator side then transmits the rehabilitation angle of the wrist joint to the high torque DC deceleration motor in the wrist joint rehabilitation device (connected to the elbow joint rehabilitation device 1). 11 and another high-torque DC deceleration motor 111-3 (different from and simultaneously existing in the rehabilitation assistance system 100) to drive the wrist joint rehabilitation device, and the wrist joint rehabilitation device will drive the operator's affected hand to perform remote wrist joint rehabilitation movements as the angle generated by the wrist joint rehabilitation device is changed. It should be noted that the set wrist joint rehabilitation angle of the set wrist joint rehabilitation angle command sent to the rehabilitation device 110 can be, for example, 80°, 65°, 30° or 0°, but is not limited to this.

After measuring the operator's first inertial sensing signal (e.g., upper arm acceleration signal, upper arm angular velocity signal, upper arm magnetic signal, forearm acceleration signal, forearm angular velocity signal, forearm magnetic signal, etc.), second inertial sensing signal (e.g., phalangeal acceleration signal, phalangeal angular velocity signal, phalangeal magnetic signal, back of hand acceleration signal, back of hand angular velocity signal, back of hand magnetic signal, etc.), third inertial sensing signal (e.g., forearm acceleration signal, forearm angular velocity signal, forearm magnetic signal, back of hand acceleration signal, back of hand angular velocity signal, back of hand magnetic signal, etc.), and physiological signal (e.g., skin temperature, heart rate, blood oxygen concentration, etc.), the processor 144 stores these inertial sensing signals and physiological signals in a cloud database.

The rehabilitation assistance system 100 further includes a rehabilitation network platform configured to display real-time signals including upper arm acceleration signals, upper arm angular velocity signals, upper arm magnetic signals, forearm acceleration signals, forearm angular velocity signals, forearm magnetic signals, phalangeal acceleration signals, phalangeal angular velocity signals, phalangeal magnetic signals, hand back acceleration signals, hand back angular velocity signals, hand back magnetic signals, elbow joint angle, wrist joint angle, metacarpophalangeal joint angle, skin temperature, blood oxygen concentration, and heart rate. This allows medical staff and the operator's family to access a cloud database to monitor the operator's rehabilitation status in real time. Furthermore, the monitoring platform is configured to store the operator's historical rehabilitation records in the cloud database.

In one embodiment of the present invention, the rehabilitation assistance system 100 further includes an application that can be installed on a mobile device, allowing medical personnel and family members to use the application on their personal mobile devices to observe in real time the operator's upper arm acceleration signal, upper arm angular velocity signal, upper arm magnetic signal, forearm acceleration signal, forearm angular velocity signal, forearm magnetic signal, phalange acceleration signal, phalange angular velocity signal, phalange magnetic signal, back of hand acceleration signal, back of hand angular velocity signal, back of hand magnetic signal, elbow joint angle, wrist joint angle, metacarpophalangeal joint angle, skin temperature, blood oxygen concentration and heart rate signals while the operator performs rehabilitation movements. The operator can also view the operator's complete historical rehabilitation record. In some embodiments, the mobile device may be a smart phone, a smart bracelet, a tablet computer, etc., but is not limited thereto.

In summary, the rehabilitation assistance system of this invention combines rehabilitation devices, a sensor network, sensor devices, and an interactive interface to assist stroke patients in elbow, metacarpophalangeal, and wrist rehabilitation of their affected hand. It offers two rehabilitation modes: self-guided mirror rehabilitation and remote home rehabilitation, allowing patients to choose the most appropriate method. Furthermore, medical staff and family members can monitor the patient's physiological status in real time during rehabilitation through a rehabilitation network platform or mobile device application.

Although the present invention has been disclosed above by way of embodiments, these are not intended to limit the scope of the present invention. Any person skilled in the art may make various changes, substitutions, and modifications without departing from the spirit and scope of the present invention. Therefore, the scope of protection of the present invention shall be determined by the scope of the patent application appended hereto.

100: Rehabilitation Assist System 110: Rehabilitation Device 111: Elbow Joint Rehabilitation Device 111-1: Forearm Mechanical Structure 111-2: Upper Arm Mechanical Structure 111-3: High-Torque DC Gear Motor 111-4: Incremental Rotary Encoder 112: Metacarpophalangeal Joint Rehabilitation Device 112-1: 3D-Printed Metacarpophalangeal Joint Mechanism 112-2: Thin-Film Potentiometer 112-3: Pneumatic Cylinder 120: Sensing Network 130: Sensing Device 131: Second Inertia Sensing Module 132: Physiological Signal Sensor 140: Interactive Interface 142: Memory 144: Processor

To facilitate understanding of the above and other objects, features, advantages, and embodiments of the present invention, the accompanying drawings are provided as follows: Figure 1 is a functional block diagram of a rehabilitation assistance system according to an embodiment of the present invention; Figure 2 is a schematic diagram of an elbow joint rehabilitation device utilizing the rehabilitation assistance system according to an embodiment of the present invention; Figure 3 is a schematic diagram of a metacarpophalangeal joint rehabilitation device utilizing the rehabilitation assistance system according to an embodiment of the present invention; Figure 4 is a schematic diagram of a sensing device utilizing the rehabilitation assistance system according to an embodiment of the present invention; and Figure 5 is a schematic diagram of a user performing rehabilitation using the elbow joint rehabilitation device, metacarpophalangeal joint rehabilitation device, and sensing device according to an embodiment of the present invention.

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100: Rehabilitation Assistance System

110: Rehabilitation Device

120: Sensing Network

130: Sensing device

140:Interactive Interface

142: Memory

144: Processor

Claims (11)

A rehabilitation assist system, suitable for an operator performing rehabilitation, comprises: a rehabilitation device, worn on an affected hand of the operator, configured to drive the affected hand to perform an elbow joint rehabilitation movement, a metacarpophalangeal joint rehabilitation movement, and a wrist joint rehabilitation movement; a sensing network, comprising a first inertia sensing module and a first wireless radio frequency transmission module, wherein the first inertia sensing module is configured to measure the elbow joint rehabilitation movement to obtain at least one first inertia sensing signal of the operator, and the first wireless radio frequency transmission module is configured to send the at least one first inertia sensing signal; a sensing device, comprising a second inertia sensing module A group, a physiological signal sensor and a second wireless radio frequency transmission module, wherein the second inertia sensing module is configured to measure the metacarpophalangeal joint rehabilitation movement to obtain at least one second inertia sensing signal of the operator, the physiological signal sensor is configured to measure at least one physiological signal of the operator, and the second wireless radio frequency transmission module is configured to send the at least one second inertia sensing signal and the at least one physiological signal, wherein the first inertia sensing module and the second inertia sensing module are further configured to measure the wrist joint rehabilitation movement to obtain at least one third inertia sensing signal of the operator, and the at least one third inertia sensing signal is transmitted by the first inertia sensing module. a wireless radio frequency transmission module and the second wireless radio frequency transmission module; an interactive interface coupled to the rehabilitation device, the sensing network and the sensing device, the interactive interface configured to receive and display the at least one first inertial sensing signal, the at least one second inertial sensing signal, the at least one third inertial sensing signal and the at least one physiological signal, comprising: a memory configured to store the at least one first inertial sensing signal, the at least one second inertial sensing signal, the at least one third inertial sensing signal and the at least one physiological signal; and a processor configured to receive at least one first control instruction from the operator and process the at least one first control instruction according to the at least one first control instruction. The at least one first control instruction sends at least one rehabilitation instruction to the rehabilitation device, wherein the at least one second inertial sensing signal includes a phalange acceleration signal, a phalange angular velocity signal, a phalange magnetic signal, a back of hand acceleration signal, a back of hand angular velocity signal, and a back of hand magnetic signal. The processor is further configured to use a rehabilitation posture measurement algorithm to process the phalange acceleration signal, the phalange angular velocity signal, and the phalange magnetic signal to obtain a phalange rehabilitation posture angle, and to use the rehabilitation posture measurement algorithm to process the back of hand acceleration signal, the back of hand angular velocity signal, and the back of hand magnetic signal to obtain a back of hand rehabilitation posture angle. A rehabilitation assist system as described in claim 1, wherein the rehabilitation device includes an elbow joint rehabilitation device, a metacarpophalangeal joint rehabilitation device and a wrist joint rehabilitation device. A rehabilitation assistance system as described in claim 1, wherein the at least one first inertial sensing signal includes an upper arm acceleration signal, an upper arm angular velocity signal, an upper arm magnetic signal, a forearm acceleration signal, a forearm angular velocity signal and a forearm magnetic signal, and the processor is further configured to use a rehabilitation posture measurement algorithm to process the upper arm acceleration signal, the upper arm angular velocity signal and the upper arm magnetic signal to obtain an upper arm rehabilitation posture angle, and use the rehabilitation posture measurement algorithm to process the forearm acceleration signal, the forearm angular velocity signal and the forearm magnetic signal to obtain a forearm rehabilitation posture angle. A rehabilitation assistance system as described in claim 3, wherein the processor is further configured to utilize a joint angle measurement algorithm to process the upper arm rehabilitation posture angle and the forearm rehabilitation posture angle to calculate an elbow joint angle, wherein the elbow joint angle is obtained by subtracting the upper arm rehabilitation posture angle from the forearm rehabilitation posture angle. The rehabilitation assistance system as described in claim 3, wherein the processor is further configured to process the forearm rehabilitation posture angle using a joint angle measurement algorithm to calculate a wrist joint angle. A rehabilitation assistance system as described in claim 1, wherein the processor is further configured to utilize a joint angle measurement algorithm to process the phalangeal rehabilitation posture angle and the back of the hand rehabilitation posture angle to calculate a metacarpophalangeal joint angle, wherein the metacarpophalangeal joint angle is obtained by subtracting the back of the hand rehabilitation posture angle from the phalangeal rehabilitation posture angle. The rehabilitation assistance system as described in claim 1, wherein the processor is further configured to process the back of the hand rehabilitation posture angle using a joint angle measurement algorithm to calculate a wrist joint angle. The rehabilitation assistance system as described in claim 1, wherein the processor is further configured to receive at least one second control instruction from a remote controller and send the at least one rehabilitation instruction to the rehabilitation device according to the at least one second control instruction. The rehabilitation assistance system as described in claim 1, wherein the processor is further configured to process the physiological signal using a physiological emergency stop mechanism algorithm, and control the rehabilitation device to stop operating when it is determined that a physiological parameter of the physiological signal exceeds a normal physiological parameter range. The rehabilitation assistance system as described in claim 1, wherein the at least one first control instruction includes an instruction for setting an elbow joint rehabilitation angle, an instruction for setting a metacarpophalangeal joint rehabilitation angle, and an instruction for setting a wrist joint rehabilitation angle. The rehabilitation assistance system of claim 1, wherein the processor is further configured to store the at least one first inertial sensing signal, the at least one second inertial sensing signal, the at least one third inertial sensing signal, and the at least one physiological signal in a cloud database.