Passive motion monitoring device and rehabilitation examination system

Abstract

The utility model is applicable to the technical field of medical instruments, and provides a passive motion monitoring device and a rehabilitation examination system.The passive motion monitoring device comprises a wearable carrier, an identification module, a sensor group and a processor, and the sensor group is arranged on the wearable carrier and electrically connected with the processor; wherein the recognition module is used for recognizing a user instruction and determining a working mode of passive exercise training according to the user instruction, and the working mode comprises a target action completed within a set activity range; the sensor group is used for collecting motion data and muscle force data of the patient completing the target motion within the set activity range according to the working mode; the processor is used for monitoring passive exercise training of the patient according to the exercise data and the muscle force data. The passive motion monitoring device can objectively quantify various data used for evaluating the rehabilitation condition of the detected object, avoids subjective perception errors, and enables the rehabilitation evaluation result to be more accurate.

Description

Technical Field

[0001] The utility model belongs to the technical field of medical equipment, and in particular relates to a passive motion monitoring device and a rehabilitation examination system. Background Art

[0002] During the rehabilitation assessment process, there are many steps that require palpation or manual examination by rehabilitation doctors or therapists, such as measuring passive joint range of motion, checking muscle tension and assessing muscle strength.

[0003] Among them, the measurement of passive joint range of motion requires the hand to sense the end sensation of joint movement to determine the range of motion; at the same time, the joint angle at this time also needs to be measured. The examination of muscle tension requires the perception of muscle elasticity, the range of motion and resistance to movement during the patient's passive limb movement. When implementing manual muscle strength testing, the rehabilitation doctor or therapist can make the patient take different test positions according to the function of the patient's muscles or muscle groups, and make the tested muscles perform standard test movements under the state of weight loss, anti-gravity or anti-resistance, observe the muscle's ability to complete the test movement, and judge the muscle's contraction strength.

[0004] Currently, rehabilitation doctors or therapists typically rely on experience to perceive various data used for rehabilitation assessment when performing palpation or manual examination. Data based on experience is prone to subjective perception errors, resulting in inaccurate rehabilitation assessment results. Utility Model Content

[0005] In view of this, the present invention provides a passive motion monitoring device and a rehabilitation examination system. When a doctor performs manual muscle strength testing on a patient, the passive motion monitoring device can monitor the patient's motion data and muscle strength data during passive training. The motion data and muscle strength data monitored by the passive motion monitoring device are objective quantitative data collected by the sensor. The objective quantitative data can avoid subjective perception errors when the doctor performs rehabilitation assessment on the patient, making the rehabilitation assessment results more accurate.

[0006] The first aspect of the present invention provides a passive motion monitoring device for monitoring a patient's passive motion training, the device comprising a wearable carrier, an identification module, a sensor group, and a processor, wherein the sensor group is disposed on the wearable carrier and electrically connected to the processor, wherein:

[0007] The wearable carrier includes a glove, and the glove includes a body and a fingertip;

[0008] The recognition module includes a voice recognition device, which is provided on the wearable carrier and is electrically connected to the processor;

[0009] The sensor group is used to collect motion data and muscle strength data of the patient completing a target movement within a set range of activity according to the working mode. The sensor group is arranged on the body and / or the finger cuff; the sensor group includes at least one pressure sensor, which is arranged at at least one position on the palm of the body or the finger cuff, and the pressure sensor is used to record the muscle strength data. The sensor group includes at least one inertial sensor, which is arranged at at least one position on the palm of the body, the back of the hand, and the finger cuff, and the inertial sensor is used to record the patient's motion data;

[0010] The processor is used to monitor the patient's passive motion training based on the motion data and the muscle strength data, and the processor is a microprocessor.

[0011] In a possible implementation, the recognition module includes a gesture recognition device, which is disposed on the wearable carrier and is electrically connected to the processor.

[0012] In a possible implementation, the inertial sensor is a nine-axis inertial measurement sensor.

[0013] A second aspect of the present invention provides a rehabilitation examination system, comprising the passive motion monitoring device described in the first aspect.

[0014] Compared with the prior art, the present invention has the following advantages:

[0015] The passive motion monitoring device in the present invention can be used to monitor the patient's passive motion training, and the passive motion monitoring device can be provided with an identification module, a processor, and a sensor group. Among them, the identification module is used to identify user instructions and determine the working mode of passive motion training according to the user instructions; the sensor group can collect the patient's motion data and muscle strength data of the target action completed within the set range of activity according to the working mode determined by the identification module; the processor can monitor the patient's passive motion training based on the motion data and muscle strength data. When a doctor uses the passive motion monitoring device in this application to perform a passive examination on a patient, the sensor group selects to collect the patient's motion data and muscle strength data according to the working mode selected by the doctor. The patient's motion data and muscle strength data are objective and quantified sensor data; evaluating the patient's rehabilitation process based on objective and quantified sensor data can avoid subjective perception errors and make the rehabilitation assessment results more accurate. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] In order to more clearly illustrate the technical solutions of the present invention, the following briefly introduces the drawings required for use in the embodiments or descriptions of the prior art.

[0017] Figure 1This is a schematic diagram of a passive motion monitoring device provided by the present utility model;

[0018] Figure 2 This is a structural diagram of another passive motion monitoring device provided by the present invention;

[0019] In the figure, 1-pressure sensor and inertial sensor, 2-pressure sensor, 3-inertial sensor. DETAILED DESCRIPTION

[0020] In the following description, specific details such as specific system structures and techniques are provided for purposes of illustration, not limitation, to facilitate a thorough understanding of the present invention. However, it will be apparent to those skilled in the art that the present invention may be implemented in other embodiments without these specific details. In other cases, detailed descriptions of well-known systems, devices, circuits, and methods are omitted to avoid obscuring the description of the present invention with unnecessary detail.

[0021] Passive exercise is a type of movement that relies entirely on external force. Patients often need to perform passive exercise training during rehabilitation. For example, rehabilitation doctors and therapists monitor patients' passive exercise training during rehabilitation assessments, allowing them to conduct rehabilitation assessments based on the data from these training sessions.

[0022] For example, during the rehabilitation assessment process, it is necessary to measure the passive range of motion of the joints, check muscle tone, and assess muscle strength. During the passive range of motion measurement, muscle tone, and muscle strength assessment, a rehabilitation doctor or therapist is generally required to perform palpation or manual examination.

[0023] Currently, rehabilitation doctors or therapists typically perform rehabilitation assessments based on their subjective perception when performing palpation or manual examinations. However, this assessment relies heavily on experience and personal perception. Inexperienced doctors, or those with reduced perception due to physical conditions, can easily lead to inaccurate assessment results.

[0024] Currently, the data used in rehabilitation assessments is empirical data, which can easily lead to inaccurate rehabilitation assessment results. If the various passive training monitoring data used to evaluate the rehabilitation status of the subject can be objectively quantified when the rehabilitation doctor or therapist performs palpation or manual examination, the accuracy of the rehabilitation assessment results can be improved. Based on this, the present invention provides a passive motion monitoring device. A rehabilitation doctor or therapist can use this passive motion monitoring device when performing palpation or manual examination to obtain objectively quantified passive training monitoring data.

[0025] The technical solution of the present utility model is described below through specific embodiments.

[0026] The utility model provides a passive motion monitoring device. The passive motion monitoring device may include a wearable carrier, an identification module, a sensor group, and a processor. The sensor group may be arranged on the wearable carrier and electrically connected to the processor, wherein: the identification module may be used to identify user instructions and determine a working mode of passive motion training according to the user instructions. The working mode includes a target action to be completed within a set range of activity; the sensor group may be used to collect motion data and muscle strength data of the patient completing the target action within the set range of activity according to the working mode; the processor may be used to monitor the patient's passive motion training based on the motion data and muscle strength data.

[0027] The above-mentioned wearable carrier is a device that can be worn on the hand. Exemplarily, the wearable carrier may include at least one of a glove, a finger ring, and a wristband. Among them, the glove may include a body and a fingertip, and the sensor group may be provided on the body and / or the fingertip. In addition, other devices that can be fixed on the hand, such as scarves, cloth strips, cloth bags and the like should also be included in the wearable carrier described in this application. In order to facilitate the description of the passive monitoring device in this application, this application mostly uses the wearable carrier as a glove to illustrate the passive monitoring device.

[0028] The passive monitoring device can have different working modes, and different working modes can be used to monitor different passive training. Exemplarily, the above working modes may include the measurement of passive joint range of motion, the examination of muscle tension and the assessment of muscle strength. Different passive trainings may have different passive movements, and therefore, each working mode may include a target movement completed within a set range of movement. The target movement is an action that the patient passively completes with the help of a rehabilitation doctor or therapist. When performing passive training, the rehabilitation doctor or therapist can issue user instructions to the passive monitoring device, and based on the user instructions, the passive monitoring device can determine the corresponding working mode.

[0029] The recognition module can identify user commands by identifying key commands, voice commands, gesture commands, etc. User commands and working modes may have a corresponding association relationship, and the recognition module can determine the working mode corresponding to the user command based on the association relationship between the user command and the working mode.

[0030] In one possible implementation, the recognition module may include a speech recognition device. The speech recognition device may be a device with an embedded speech recognition algorithm. The speech recognition device may include a speech recognition chip and other auxiliary circuitry, capable of communicating with the processor. The speech recognition device may be mounted on a wearable carrier and electrically connected to the processor. During a passive examination, a physician may issue voice commands. The speech recognition device uses embedded speech recognition technology to recognize the captured speech, thereby identifying the physician's voice commands and determining the associated operating mode. In one possible implementation, the wearable carrier may also include a microphone, which may be used to capture speech information. For example, a rehabilitation physician or therapist may determine the desired operating mode based on the patient's condition and then state the desired operating mode. The microphone may capture the physician's or therapist's speech information and transmit the speech information to the speech recognition device. The speech recognition device may then use its embedded speech recognition algorithm to recognize the captured speech information and determine the operating mode corresponding to the voice command. The speech recognition algorithm used in this utility model is prior art and will not be described in detail here.

[0031] In one possible implementation, the recognition module may be a gesture recognition device. The gesture recognition device may be a module embedded with a gesture recognition algorithm. The gesture recognition device may be mounted on a wearable carrier and electrically connected to a processor. During a passive examination, a physician may issue commands through gestures. The gesture recognition device uses embedded gesture recognition technology to recognize the captured gestures, thereby identifying the physician's gesture commands and determining the corresponding operating mode. In one possible implementation, the glove may also include a camera that can be used to capture gesture information. For example, a rehabilitation physician or therapist may determine the desired operating mode based on the patient's condition and then perform the gesture corresponding to that operating mode. The camera can capture the physician's or therapist's gesture information and transmit it to the gesture recognition device. The gesture recognition device can then use its built-in gesture recognition algorithm to recognize the gesture information captured by the camera, thereby determining the corresponding operating mode. The gesture recognition algorithm used in this utility model is prior art and will not be described in detail here.

[0032] The above-mentioned sensor group may include at least one inertial sensor, which may be arranged at at least one position in the palm, back of the hand and fingertip of the glove body, and the inertial sensor may be used to record the patient's motion data. An inertial sensor is a sensor that mainly detects and measures acceleration, tilt, impact, vibration, rotation and multi-degree-of-freedom (DoF) motion. Inertial sensors may include accelerometers (or acceleration sensors) and angular velocity sensors (gyroscopes) and their single-, dual- and tri-axis combined inertial measurement units (IMUs) and attitude and heading reference systems (AHRSs). The inertial sensor in the present invention may be an acceleration sensor or a gyroscope or an inertial measurement unit (IMU) sensor.

[0033] A rehabilitation doctor or therapist can use a passive motion monitoring device to drive the joints of the subject to perform passive motion, thereby measuring the passive joint range of motion. When measuring the passive joint range of motion, the inertial sensor can collect activity data of the glove itself, such as angular velocity, acceleration, rotation, and posture, etc. The activity data can characterize the range of motion and angle of motion of the passive joint. Exemplarily, a nine-axis inertial measurement sensor can be used as the above-mentioned inertial sensor. The nine-axis inertial measurement sensor may include a three-axis gyroscope, a three-axis acceleration sensor, and a three-axis magnetic induction sensor. In the present utility model, the inertial sensor calculates the activity trajectory, range, angle, etc. based on the collected sensor data, which are all existing technologies and will not be described here.

[0034] The above-mentioned sensor group may also include at least one pressure sensor (Pressure Transducer), which may be provided at at least one position in the palm, back of the hand and fingertip of the glove body, and the pressure sensor may be used to record muscle strength data in passive examinations. A pressure sensor is a device or apparatus that can sense pressure signals and convert pressure signals into usable output electrical signals according to certain rules. When conducting rehabilitation assessments on the subject being tested, the rehabilitation doctor or therapist may wear a passive motion monitoring device and then use the passive motion monitoring device for palpation or manual examination. During palpation or manual examination, the rehabilitation doctor or therapist applies force to the body part of the subject being tested through the glove, so that the body part of the subject being tested may generate a reaction force, and the pressure sensor may monitor the reaction force generated by the subject being tested, that is, the muscle strength or resistance of the subject being tested.

[0035] Figure 1 It is a schematic diagram of a passive motion monitoring device provided by the utility model. Figure 1The left side of the figure is a schematic diagram of the back of the hand of the passive motion monitoring device. Figure 1 The right side of the figure is a schematic diagram of the palm surface of the passive motion monitoring device. Figure 1 In the figure, 1 is a pressure sensor and an inertial sensor, 2 is a pressure sensor, and 3 is an inertial sensor. Figure 1 As shown, Figure 1 In the figure, 1 corresponds to the positions of the glove's fingertips, 2 corresponds to the palm of the hand, and 3 corresponds to the back of the hand. This means that pressure sensors can be embedded in both the fingertips and the palm of the hand of the passive motion monitoring device. Pressure sensors can be embedded in both the fingertips, palm of the hand, and back of the hand of the passive motion monitoring device. Figure 1 This is only an example of a passive motion monitoring device. Those skilled in the art should understand that pressure sensors or inertial sensors may also be provided at other locations of the cuff of the passive motion monitoring device.

[0036] The processor is the core of computing and control, serving as the execution unit for information processing and program execution. It can be a microprocessor. A microprocessor is a central processing unit comprised of one or a few large-scale integrated circuits. These circuits perform the functions of control components and arithmetic logic components. The microprocessor can fetch and execute instructions, as well as exchange information with external memory and logic components.

[0037] In one possible implementation, the processor may include an analysis module, which may be electrically connected to the sensor group. The analysis module may be used to determine the patient's activity trajectory based on motion data, and to determine the patient's passive activity range based on muscle strength data. The analysis module may be used to determine the patient's activity range based on hand pressure data. The analysis module may determine the activity range of the passive joint based on the received sensor data. When analyzing the joint activity range and activity angle, the analysis module may determine the relative position of the bone axis based on the modeling action, eliminating the interference of the thickness of the palm of the rehabilitation doctor or therapist and the thickness of the patient's muscle fat layer; and determine the motion trajectory of the bone axis based on the relative position of the bone axis in combination with the IMU trajectory. The joint skeleton model may also be called to analyze the joint activity angle range based on the motion trajectory of the bone axis. The determination of the activity trajectory based on motion data and the determination of the passive activity range based on muscle strength data in the present utility model belong to the prior art and will not be elaborated here.

[0038] In one possible implementation, the processor may include a motion monitoring module, which may be electrically connected to the sensor assembly and configured to monitor whether the motion data meets the requirements of the target motion. For example, when measuring passive joint range of motion, a rehabilitation physician or therapist may use a passive motion monitoring device to induce the tested joint to perform passive motion according to certain rules. Based on the motion data collected from the inertial sensor, the processor may determine whether the passive motion of the tested joint meets the requirements of the target motion, that is, whether the position motion data meets the corresponding operating mode. If the motion data does not meet the requirements of the target motion, the processor may send a prompt to the voice output module, which may then broadcast the prompt in voice. Specifically, the processor may have built-in standard motion parameters for different motion modes, such as motion trajectory, pressure range, and angle range. When a significant difference is detected between the current motion parameters and the built-in motion parameters for that mode, a reminder signal is issued to prompt the operator to confirm whether the motion mode is correct. However, this reminder does not interrupt the current measurement process; it only serves as a reminder.

[0039] In one possible implementation, the passive motion monitoring device can play the passive motion training monitoring results by voice, or use voice prompts for the target movements of the passive training. In one possible implementation, the above-mentioned passive motion monitoring device may further include an audio output module connected to the processor. The audio output module may be used to receive voice output information sent by the processor and perform voice playback. The voice output module may be a speaker. For example, the processor may calculate the range of motion and the angle of motion of the passive joint based on the data from the pressure sensor and the data from the inertial sensor, and send the range of motion and the angle of motion of the passive joint to the speaker, which may play the range of motion and the angle of motion of the passive joint, so that the rehabilitation doctor or therapist can directly hear the passive motion training monitoring results during the examination.

[0040] Exemplarily, the above-mentioned working modes may include the measurement of passive joint range of motion, the inspection of muscle tension and the assessment of muscle strength. Each working mode may also include: a measurement target, the sensor signal used and a target action. For example, when the working mode is muscle strength detection, the measurement target may be the arm muscle of the object being detected, the sensor signal used may be the sensor signal of the fingertip sensor, and the target action may be to touch the arm muscle with the fingertip. When the working mode is the inspection of muscle tension, the measurement target may be the arm of the object being detected, the sensor signal used may be the sensor signal of the palm sensor, and the target action may be to press the arm with the palm. When the working mode is the measurement of passive joint range of motion, the measurement target may be the elbow joint of the object being detected, the sensor signal used may be the sensor signal of the inertial sensor and the sensor signal of the pressure sensor, and the target action may be to hold the arm with a glove to drive the elbow joint for passive movement.

[0041] The processor can store information on multiple working modes, so that the processor can collect corresponding sensor signals according to the working mode selected by the user, and process the sensor signals according to the stored processing algorithm to obtain passive motion training monitoring results.

[0042] In a possible implementation, the above-mentioned passive monitoring device may also be provided with a memory, which may be used to store motion data and muscle strength data. The memory may be electrically connected to the processor. The present invention does not limit the specific type of memory. Exemplarily, the memory may be a random access memory (RAM). The random access memory may exchange data directly with the processor. The motion data and muscle strength data may be sensor data. After the processor receives the sensor data, the sensor data may be stored in the memory. When the sensor data is needed to calculate the passive motion training monitoring results, the sensor data may be read from the memory. The passive motion training monitoring result data calculated by the processor, such as the range of motion and angle of motion of the passive active joint, may also be stored in the memory.

[0043] In one possible implementation, the passive monitoring device may further include a power module for providing power. For example, the power module may be connected to a processor to provide power to the processor, thereby providing a charge level when the processor performs analysis and monitoring.

[0044] When using a passive motion monitoring device for passive training, rehabilitation doctors or therapists use it to check muscle tone and assess muscle strength. When checking muscle tone, the doctor or therapist applies force to the subject's body part with the palm of their hand. The palm pressure sensor detects the patient's resistance to the applied force. When assessing muscle strength, the doctor or therapist uses the subject's fingers to test muscle strength. The fingertip pressure sensors detect muscle force, thereby objectively and quantifying the perceived muscle elasticity.

[0045] During passive training, the passive motion monitoring device can be used to assess the range of motion of joints. During this assessment, a doctor can wear gloves and move the subject's joints to test their range of motion. During rehabilitation assessments, a doctor can hold the subject's wrist and move their arm in different directions to test the range of motion of the elbow joint.

[0046] When assessing the range of motion of a joint, a doctor can wear a passive motion monitoring device and then move the joint. The movement trajectory of the glove can reflect the range of motion of the joint. Therefore, in the present invention, the sensing data of the inertial sensor can reflect the movement trajectory of the joint.

[0047] When using the passive motion monitoring device of the present invention for passive training, a rehabilitation doctor or therapist can use the passive motion monitoring device to measure the passive joint range of motion. When using the passive motion monitoring device to measure the passive joint range of motion, the inertial sensor can be calibrated first. After calibration, when the doctor uses both hands to perform a passive motion examination or a passive joint range of motion examination on the patient, the inertial sensor can sense the range of motion and trajectory of the doctor's hands. Based on the sensing data of the inertial sensor, the actual range of motion of the patient's body parts during the passive examination can be quantified, so that rehabilitation assessment can be performed based on the sensing data.

[0048] The present invention uses a passive monitoring device that can be worn on the hand as a carrier for passive training monitoring. This device can be adapted to the clinical palpation and manual examination scenarios of rehabilitation doctors, and is in line with doctors' usage habits. When performing passive training monitoring based on the passive motion monitoring device in the present invention, various data in the passive training can be objectively quantified based on pressure sensors and inertial sensors. Based on the objectively quantified data, doctors can more clearly judge the patient's rehabilitation progress, thereby avoiding judgments based on subjective experience and improving the accuracy of rehabilitation assessments. At the same time, using the passive motion monitoring device in the present invention for rehabilitation examinations does not require additional personnel to assist in measurement, making it more convenient and efficient.

[0049] Figure 2This is a schematic diagram of the structure of a passive motion monitoring device provided by the present invention. Figure 2 As shown, the passive motion monitoring device can be provided with a pressure sensor and an IMU sensor.

[0050] use Figure 2 The specific operation process of the passive motion monitoring device for rehabilitation examination can be as follows:

[0051] The rehabilitation doctor or therapist puts on the passive motion monitoring device and turns on the power; the rehabilitation doctor or therapist can say the command "elbow passive joint range of motion check", and the microphone in the passive motion monitoring device can collect voice information and send the voice information to the voice recognition module. The voice recognition module can use the voice recognition algorithm to perform voice recognition, thereby recognizing the current voice command, and then the voice recognition module can send the recognized voice command to the microprocessor.

[0052] After receiving the voice command, the microprocessor can determine that the current working mode is a passive joint range of motion test based on the voice command. In this working mode, the angle range is measured; the IMU sensor information on the two passive motion monitoring devices is collected. The rehabilitation examination operations that need to be performed by the rehabilitation doctor or therapist include performing modeling movements and performing examination movements, wherein performing the modeling movement may include: using the thumb and middle finger of one of the passive motion monitoring devices to circle the fixed arm; and then using the thumb and middle finger of the other passive motion monitoring device to circle the moving arm. Performing the examination movement may include: placing both hands on the fixed arm and the moving arm at the position in the modeling movement, and gently moving the joints.

[0053] The microprocessor can send the rehabilitation check operation to the audio processing module, which then prompts the rehabilitation check operation through the speaker. If the passive motion monitoring device is connected to a display screen, the microprocessor can also send the corresponding video of the rehabilitation check operation to the display screen, so that the display screen can play the rehabilitation check operation.

[0054] The doctor can wear a passive motion monitoring device on both hands. After wearing the passive motion monitoring device, the rehabilitation examination operation corresponding to the working mode can be performed; during the execution of the rehabilitation examination operation, the sensor can collect sensor data and send the sensor data to the microprocessor. The microprocessor can calculate the activity angle based on the received sensor data. The rehabilitation doctor or therapist can hold the patient's upper arm and lower arm with both hands respectively and slowly move the joints; during this process, the inertial sensor of the passive motion monitoring device will record the trajectory between the moving arm and the fixed arm, and the microprocessor can analyze the real-time activity angle based on the data recorded by the inertial sensor; at the same time, the microprocessor can identify the end feeling in the movement through the pressure sensor data, thereby clarifying the range of passive joint movement. The microprocessor can synchronously store the sensor data and the rehabilitation examination data calculated based on the sensor data in the memory to facilitate subsequent data review and analysis.

[0055] The microprocessor may include a detection module, which, during the passive examination process, can determine whether the collected sensor data conforms to the operating mode. If the collected sensor data does not conform to the operating mode, the microprocessor can send a prompt to the voice output module, thereby providing a voice prompt to the rehabilitation doctor or therapist. The rehabilitation doctor or therapist can adjust the rehabilitation examination process based on the voice prompt.

[0056] When the rehabilitation doctor or therapist says "end," the passive motion monitoring device's voice recognition module can perform voice recognition to identify the end instruction. The voice recognition module can then send the recognized end instruction to the microprocessor. Upon receiving the end instruction, the microprocessor can calculate the passive range of motion of the elbow joint.

[0057] The microprocessor may include an analysis module. The analysis module may determine the range of motion of the passive joint based on the sensor data. The microprocessor may have a built-in joint physiological model and a joint skeletal model. When checking the range of motion of the passive joint, the joint physiological model may be called to analyze the range of motion and angle of motion of the joint. When analyzing the range of motion and angle of motion of the joint, the microprocessor may determine the relative position of the bone axis based on the modeling action, eliminating the interference of the thickness of the palm of the rehabilitation doctor or therapist and the thickness of the patient's muscle fat layer; and determine the motion trajectory of the bone axis based on the relative position of the bone axis in combination with the IMU trajectory. The microprocessor may also call the joint skeletal model to analyze the range of joint motion angle based on the motion trajectory of the bone axis.

[0058] The microprocessor can send the calculated passive joint range of motion of the elbow joint to the audio output module, and the audio output module can send the passive joint range of motion of the elbow joint to the speaker, so that the passive joint range of motion of the elbow joint can be voice broadcasted through the speaker.

[0059] When using the above-mentioned passive motion monitoring device for rehabilitation examination, pressure sensors and inertial sensors can be used to quantify the sensory information into sensor signals, and the microprocessor can automatically calculate the passive motion training monitoring results based on the sensor signals, thereby reducing manual labor and improving the accuracy of rehabilitation assessment. The passive motion monitoring device in the present invention can also perform voice recognition and voice broadcasting, so that when the rehabilitation doctor or therapist is performing a rehabilitation examination, voice commands can be directly issued and the calculation results can be directly heard. The change of working mode and the viewing of calculation results do not require the interruption of the rehabilitation examination process, so there is no need for additional personnel to assist in the rehabilitation examination, making the rehabilitation examination more convenient and efficient.

[0060] An embodiment of the present application further provides a rehabilitation examination system, which may include the above-mentioned passive motion monitoring device.

[0061] In one possible implementation, the rehabilitation examination system can display passive motion training monitoring results and rehabilitation examination operations. In another possible implementation, the rehabilitation examination system also includes a display screen connected to the processor of the passive motion monitoring device, wherein the display screen can be used to receive and display display information sent by the microprocessor. For example, when the operating mode is passive joint range of motion measurement, the microprocessor can obtain a demonstration video of the passive joint range of motion measurement and then send the demonstration video to the display screen, which can display the demonstration video.

[0062] In a possible implementation, the rehabilitation examination system further includes a keyboard and a mouse, so that the doctor can manually select a working mode or manually perform data processing through the keyboard and the mouse.

[0063] The above embodiments are intended only to illustrate the technical solutions of the present invention and are not intended to limit the present invention. Although the present invention has been described in detail with reference to the above embodiments, those skilled in the art should understand that the technical solutions described in the above embodiments may be modified or some of the technical features thereof may be replaced by equivalents; and such modifications or replacements do not deviate from the spirit and scope of the technical solutions of the embodiments of the present invention and are therefore intended to be included within the scope of protection of the present invention.

Claims

1. A passive motion monitoring device for monitoring a patient's passive motion training, characterized in that: The device comprises a wearable carrier, an identification module, a sensor group and a processor, wherein the sensor group is arranged on the wearable carrier and is electrically connected to the processor, wherein: The wearable carrier comprises a glove, and the glove comprises a body and a fingertip; The recognition module includes a voice recognition device, the voice recognition device is arranged on the wearable carrier, and the voice recognition device is electrically connected to the processor; The sensor group is used to collect the motion data and muscle strength data of the patient completing the target action within the set activity range according to the working mode, and the sensor group is arranged on the body and / or the finger sleeve; the sensor group includes at least one pressure sensor, and the pressure sensor is arranged at at least one position of the palm of the body and the finger sleeve, and the pressure sensor is used to record the muscle strength data; the sensor group includes at least one inertial sensor, and the inertial sensor is arranged at at least one position of the palm, the back of the hand and the finger sleeve of the body, and the inertial sensor is used to record the motion data of the patient; The processor is used for monitoring the patient's passive motion training according to the motion data and the muscle strength data, and the processor is a microprocessor.

2. The device according to claim 1, characterized in that The recognition module includes a gesture recognition device, which is disposed on the wearable carrier and is electrically connected to the processor.

3. The device according to claim 1, characterized in that The inertial sensor is a nine-axis inertial measurement sensor.

4. A rehabilitation examination system, characterized in that: Comprising the passive motion monitoring device as described in any one of claims 1-3.

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