CN113744837A - Early-middle-stage Parkinson's home motion body feeling rehabilitation training system - Google Patents
Early-middle-stage Parkinson's home motion body feeling rehabilitation training system Download PDFInfo
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Abstract
The invention provides an early and middle-term Parkinson's home motion body feeling rehabilitation training system, and belongs to the technical field of medical rehabilitation products. The system comprises: the rehabilitation mat is used for collecting gait motion data of the patient and guiding the patient to relieve the frozen gait according to the rhythm; the motion sensing equipment is used for collecting the limb motion data of the patient; the display device is used for displaying the virtual game rehabilitation scene and the rehabilitation evaluation data; the smart phone app is used for recording effective motion data and rehabilitation evaluation data; and the processing terminal is used for fusing limb movement data and gait movement data of the patient, performing virtual scene movement rehabilitation training and guiding specified actions by using the limb movement fusion data, and performing rehabilitation evaluation and assisting in recovering frozen gait. The system can quantify the early and middle-stage Parkinson rehabilitation exercise indexes in the state that no sensor is bound to the human body, double interactive training can be realized, the rehabilitation training is more practical and efficient, and the blank of the early and middle-stage Parkinson household exercise somatosensory rehabilitation training is filled.
Description
Technical Field
The invention relates to the technical field of medical rehabilitation products, in particular to an early-middle-term Parkinson home motion body feeling rehabilitation training system.
Background
At present, 570 million Parkinson patients exist in the world, the number of the patients in China is about 270 million, 10 million patients are newly developed every year, and China becomes the first major country of Parkinson. The middle-aged and old people with the Parkinson disease more than 50 years old are more and more serious with aging problems, and the number of Parkinson disease patients is predicted to be increased to about 500 ten thousand by 2030, and the number of the Parkinson disease patients accounts for more than half of the whole world. Providing an effective rehabilitation therapy for this large population of parkinson patients is an urgent task to be solved.
Parkinson can not be cured, the traditional method relies on drug control and operation for treatment, but the existing rehabilitation and exercise therapy is emphasized, axial symptoms such as gait disorder, posture balance disorder, language and/or swallowing disorder and the like mostly exist in early and middle-stage Parkinson patients, and the drugs have little curative effect on the symptoms, but are very beneficial to rehabilitation and exercise. Therefore, rehabilitation exercise training plays an important role in improving axial symptoms, reducing the risk of falling and maintaining healthy body functions of patients. The existing early and middle period Parkinson home rehabilitation training is mainly based on oral guidance of doctors and autonomous home training of patients, and is lack of real-time motion detection and feedback, so that the rehabilitation training efficiency is low, the effect is not obvious, and the compliance rate of the patients is low.
The prior art provides a wearable device (CN106913341A) for gait training and monitoring evaluation of a Parkinson patient, which assists the patient in gait rehabilitation training by generating suggestive guide light or rhythmic sound when the Parkinson patient walks, thereby helping to improve the frozen gait of the patient and guiding the patient to walk better, but the device needs to be worn, and the patient feels bound and uncomfortable.
In addition, a multifunctional rotary balance training system is also reported in the prior art, and the system mainly develops potential functions of vestibular function, vision, posture reflex, muscle strength, action coordination, proprioception and core muscle group control rarely used in normal daily life activities through all-directional and multi-angle training of the standing position and the sitting position balance function of a human body, but the device is only provided with single rotary rehabilitation training action, so that the whole simulation training is too simple and boring.
In summary, although the existing early and middle stage parkinson home rehabilitation training product realizes the interactive training process, there are many disadvantages in the application: firstly, the feedback and guidance cannot be made aiming at the emergent gait disorder; secondly, interactive training is lacked, interaction between patients or between patients and family cannot be realized, the patient compliance rate is low, and the patient compliance rate is single and boring. And the wearable motion sensor is bound to the human body.
Disclosure of Invention
In view of the analysis, the invention aims to provide an early-middle-stage Parkinson home motion somatosensory rehabilitation training system, and solves the problems that the existing early-middle-stage Parkinson home rehabilitation lacks real-time scientific guidance, quantitative evaluation standard and feedback, the rehabilitation scene is not real, interaction is lacked, and a motion sensor is bound to a human body.
The purpose of the invention is mainly realized by the following technical scheme:
the utility model provides a rehabilitation training system is felt to early and middle stage parkinson's house motion body, includes:
the rehabilitation cushion is used for collecting gait motion data of the patient and sending the gait motion data to the somatosensory equipment, and guiding the patient to relieve the frozen gait in a rhythm manner;
the motion sensing equipment is used for collecting the limb motion data of the patient and sending the data to the processing terminal;
the display device is used for connecting the rehabilitation cushion and the somatosensory device and displaying the virtual game rehabilitation scene and the rehabilitation evaluation data;
the smart phone app is used for recording effective motion data and rehabilitation evaluation data;
the processing terminal is used for carrying out fusion processing on the obtained limb movement data and the gait movement data of the patient to obtain limb movement fusion data; and performing virtual scene motion rehabilitation training and guiding appointed actions by using the four-limb motion fusion data, performing rehabilitation evaluation and assisting in recovering the frozen gait.
The invention has the following beneficial effects: the invention provides an early and middle-stage Parkinson's home motion body feeling rehabilitation training system, which can quantify early and middle-stage Parkinson's rehabilitation motion indexes under the state that a human body is bound by no sensor, realizes double-person interactive training, enables the whole home motion rehabilitation training to be more practical, efficient, diversified and interesting, and enables a patient to obtain the sense value feeling to be continuously increased in the training process, so that the rehabilitation training is insisted for a long time, and the blank of the early and middle-stage Parkinson's home motion body feeling rehabilitation training is filled.
Drawings
The drawings are only for purposes of illustrating particular embodiments and are not to be construed as limiting the invention, wherein like reference numerals are used to designate like parts throughout.
FIG. 1 is a hardware connection diagram of an early-middle-stage Parkinson's home motion body feeling rehabilitation training system in an embodiment of the invention;
FIG. 2 is a data flow diagram of an early-mid-stage Parkinson's home motion somatosensory rehabilitation training system in an embodiment of the invention;
FIG. 3 is a schematic view of a rehabilitation pad body according to an embodiment of the present invention;
FIG. 4 is an index diagram of 25 joint data acquired by a Kinect sensor in the embodiment of the invention;
FIG. 5 is a schematic diagram of normative movement of limbs according to an embodiment of the present invention;
FIG. 6 is a virtual reality grass batting chess playing game training scenario in an embodiment of the present invention;
FIG. 7 is a framework for smartphone app functionality in an embodiment of the invention;
in the figure: 1-a rehabilitation mat, 2-a somatosensory device, 3-a display device, 4-a smart phone app and 5-a processing terminal; the LED lamp comprises a 1-1 top PU layer, a 1-2 pressure sensing layer, a 1-3 hydraulic vibration layer, a 1-4LED lamp strip, a 1-5 anti-skidding bottom layer, a 1-6 wireless charging device, a 1-7 storage battery, a 1-8 power switch and a 1-9 wireless communication module.
Detailed Description
The accompanying drawings, which are incorporated in and constitute a part of this application, illustrate preferred embodiments of the invention and together with the description, serve to explain the principles of the invention and not to limit the scope of the invention.
The invention discloses a specific embodiment of an early-middle-stage Parkinson's home motion body feeling rehabilitation training system, which comprises the following components in percentage by weight as shown in fig. 1: the rehabilitation mat comprises a rehabilitation mat 1, a body sensing device 2, a display device 3, a smart phone app 4 and a processing terminal 5. The rehabilitation mat 1 is connected with the body sensing device 2 through wireless communication, and the rehabilitation mat 1 and the body sensing device 2 are respectively connected with the processing terminal 5. The patient stands on the rehabilitation mat, the somatosensory device and the pressure sensing layer respectively collect limb movement data and gait movement data of the patient in real time, and after the collected data are processed by the processing terminal, the obtained limb movement fusion data are used for performing movement training by comparing with target movement in a virtual rehabilitation scene; on the other hand, patient rehabilitation evaluation is performed; in addition, the obtained gait motion fusion data is used to assist in restoring the frozen gait of the patient. The smartphone app will record the motion data and rehabilitation assessments.
In this embodiment, the specific functions of the components are as follows:
the motion sensing equipment is used for providing a rehabilitation exercise game and collecting the limb movement data of the patient;
the rehabilitation mat is used for collecting gait motion data of the patient and guiding the patient to relieve the frozen gait. As shown in fig. 3, the rehabilitation mat comprises: the device comprises a top PU layer 1-1, a pressure sensing layer 1-2, a hydraulic vibration layer 1-3, an LED lamp strip 1-4, an anti-skid bottom layer 1-5, a wireless charging device 1-6, a storage battery 1-7, a power switch 1-8 and a wireless communication module 1-9. The top PU layer 1-1, the pressure sensing layer 1-2, the hydraulic vibration layer 1-3 and the anti-skid bottom layer 1-5 are sequentially stacked from top to bottom, the pressure sensing layer 1-2 is used for collecting gait motion data of a patient, and the gait motion data comprises the weight of the patient, the staying time of the sole, the staying position and the pressure area; the hydraulic vibration layer 1-3 is used for providing rhythmic vibration to guide the patient to regularly step; the LED lamp strip is arranged on the top PU layer 1-1 and used for providing regular flickering to guide a patient to regularly mark. The rehabilitation mat is powered by the storage batteries 1-7, charged by the wireless charging devices 1-6 and connected with the processing terminal 5 through the wireless communication module.
In one embodiment of the present invention, the top PU layer is divided into a left portion and a right portion, and the LED strip is disposed around the outer contour of the left portion and the right portion. The pressure sensing layer 1-2 comprises pressure sensors and pressure sensing processing modules which are uniformly distributed, the pressure sensors are used for acquiring real-time pressure data of each position of the rehabilitation pad, and the pressure sensing processing modules are used for analyzing the real-time pressure data to obtain the weight, sole retention time, retention position and pressure area data of a patient and sending the data to the processing terminal.
In the training system, a kinect sensor is adopted by the somatosensory equipment to collect limb moving images of a patient, the kinect sensor is connected with a skeletal tracking algorithm through an API (application programming interface) interface, 20 main joint position data of the patient are acquired in real time, and a time sequence of each joint position of the patient is obtained and used as limb moving data.
Specifically, the Kinect somatosensory equipment identifies four limbs of a human body and tracks movement, and then real-time data acquisition is achieved. The spatial and depth resolution of images recorded by the Kinect somatosensory device is 640 x 480 pixels. "Kinect for Windows Software Development Kit (SDK)", which provides an Application Programming Interface (API) for Kinect hardware. The implementation of the API interfaces with the Kinect sensor and its skeletal tracking software to provide data for 20 major joint positions (x, y and z axes) at a rate of 30 frames per second.
In one embodiment of the present invention, the processing terminal includes:
and the data receiving module is used for receiving the motion data sent by the somatosensory equipment and the pressure sensing processing module, preprocessing the motion data and sending the preprocessed data to the data fusion module. When the data receiving module is used for data preprocessing, the time sequence of each joint position of the patient is filtered by a low-pass Butterworth filter with the cut-off frequency of 5 Hz.
And the data fusion module is used for fusing the received limb movement data of the patient and the gait movement data of the patient to obtain limb movement fusion data. When data fusion is carried out, firstly, coordinates of two parts of motion data are unified, and then weighted average processing is carried out on data of the overlapping parts of the acquisition ranges of the motion sensing device and the rehabilitation pad.
The virtual rehabilitation scene motion training module is used for providing various virtual rehabilitation motion scenes beneficial to recovery of a patient, mapping the four-limb motion fusion data into the motion scenes, and grading the training behaviors of the patient in the virtual rehabilitation scenes. The training mode of the virtual rehabilitation scene motion training module can be divided into three types:
the first method is that a patient selects a designated motion, joint angle data in the motion is obtained, the difference between the actual motion joint angle and the target motion joint angle is compared, and table searching and scoring are carried out according to the difference; figure 5 gives a schematic diagram of part of the action.
The second is that the patient selects the recreational game with the appointed difficulty, the game is played according to the action guide, the number of completed tasks and the completion time are recorded, and the score is given; the recreational game is a limb movement game comprising a plurality of tasks.
The third is that the designated action is combined with the amusement game and the weighted result of the two scores is used as the total score.
The rehabilitation evaluation module is used for extracting motion indexes according to the four-limb motion fusion data and carrying out rehabilitation evaluation; the motion index comprises the speeds of the 20 main joints, the instantaneous phases of the speeds and the instantaneous phase changes of the speeds.
And the emergency guiding module is used for comparing the difference value of the gait motion and the target motion data in the four-limb motion fusion data in real time, sending an emergency signal to the rehabilitation pad when the difference value is greater than a preset threshold value or stopping the gait motion, and guiding the patient to step by using the same-frequency vibration/flicker of the hydraulic vibration layer and the LED lamp strip.
In an embodiment of the present invention, the smart phone app mainly includes three functional modules:
the movement recording module is used for recording the frequency and the duration of the frozen gait and the corresponding gait movement data and providing a basis for rehabilitation training;
the health diary module is used for providing a memorandum for recording sleeping and medication conditions for a patient for the patient to conveniently review and understand the state of an illness;
and the account management module is used for verifying the login account, and the patient can check the motion data only by logging in the account.
One skilled in the art can extend the app functionality without departing from the spirit of the invention, for example, as shown in fig. 7, a health diary can record medication, switch period, automatically monitor sleep, etc. After the app is connected to the rehabilitation pad, the connection state and the equipment electric quantity can be displayed. The motion condition recorded by the motion recording module comprises game basic conditions and data monitoring, wherein the game basic conditions can be duration, points and the like, and the data monitoring can comprise standard actions, non-standard actions, gait monitoring information, tremor trend comparison and the like. The extension of the app functions over the detailed description and application scope should be understood to be within the scope of the present invention.
As shown in fig. 2, the training process of rehabilitation training using the above system is as follows:
firstly, the motion sensing device is fixed, the rehabilitation mat, the motion sensing device and the processing terminal are connected and initialized, and the patient stands on the rehabilitation mat.
In order to achieve the best data acquisition and rehabilitation training effects, the patient needs to stand on the rehabilitation cushion for movement in the whole course; the distance between the kinect somatosensory device and the rehabilitation mat is 2-3.5m, the distance is 1 m from the ground, and the lens is perpendicular to the ground and points to the patient. The rehabilitation mat is connected with the kinect motion sensing device in a wired mode, the rehabilitation mat is in wireless communication transmission with the kinect motion sensing device, and the kinect motion sensing device is in wireless communication data transmission with the processing terminal; the processing terminal is a cloud processor.
Secondly, training begins, in the whole rehabilitation training process, data of the rehabilitation training system are transmitted as shown in fig. 2, high-precision data are obtained and data fusion is achieved, the fused data are mapped to a virtual rehabilitation training scene on one hand, and data which meet rehabilitation indexes are uploaded to a database to be stored on the other hand.
More specifically, the Kinect somatosensory equipment identifies four limbs of a human body and tracks the movement, and then real-time data acquisition is achieved. The spatial and depth resolution of images recorded by the Kinect somatosensory device is 640 x 480 pixels. "Kinect for Windows Software Development Kit (SDK)", which provides an Application Programming Interface (API) for Kinect hardware. The implementation of the API interfaces with the Kinect sensor and its skeletal tracking software to provide data for 20 major joint positions (x, y and z axes) at a rate of 30 frames per second.
The Kinect somatosensory equipment and the pressure sensing layer acquire data in real time and send the data to the processing terminal in real time: the collected data mainly comprises two aspects: the first is the human limb movement information collected by the Kinect sensor, which includes real-time three-dimensional coordinates of 20 joint points including points 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 13, 14, 17, 18, 20, 21, 22, 23, and 24 on fig. 4. The pressure sensing layer detects sole motion data, including weight, sole dwell time, dwell position, pressure area data.
After the processing terminal processes the acquired data, the obtained limb movement fusion data is used for performing movement training by comparing with target movement in a virtual rehabilitation scene; on the other hand, patient rehabilitation evaluation is performed; in addition, the obtained gait motion fusion data is used for the emergency guiding module to assist in recovering the frozen gait of the patient. The smartphone app will receive and record the athletic data and rehabilitation assessments via wireless communication.
For virtual rehabilitation scene motion training: the virtual rehabilitation scene motion scene is displayed through the display device, different game scenes and clear action guide are set through the virtual rehabilitation scene motion training module, so that the patient can achieve good operation feeling of immersive virtual reality, and the patient can be helped to perform rehabilitation training better. In the training process, the difficulty level of the virtual game can be adaptively adjusted, and after the emergency guide module in the processing terminal monitors the freezing gait, information can be sent to start the hydraulic vibration layer and the LED lamp strip in the rehabilitation pad, so that the hydraulic vibration layer and the LED lamp strip vibrate at the same frequency and flicker to guide a patient to step, and the partial data is stored in the smart phone app.
And finally, carrying out training scoring and rehabilitation evaluation on the training process.
The training scoring mode is divided into two types, namely a score P1 for recording the completed standard action and a score P2 for completing the entertainment game; the other is to compare the normative training score P1 and the game-entertainment score P2 in the ratio of 6: and 4, carrying out uniform scoring in a mode of 4, and giving a total score after scene training is finished.
For rehabilitation evaluation, rehabilitation evaluation is performed according to medical standards by extracting motion indexes, wherein the extracted motion indexes can be angles of joints of four limbs and the like. In addition, the human motion fusion data can be screened, useful data (such as the frequency and duration of the occurrence of the frozen gait) can be uploaded to a database for storage, so that the data analysis during the rehabilitation period of the patient can be carried out, a rehabilitation plan can be made in a targeted manner, and the rehabilitation effect can be improved.
For example, fig. 6 shows a training scenario of a virtual reality grass hitting game. The grassland batting game is developed by a method of playing the gobang by two persons in a way of batting with the wooden ball, the playing of the gobang is a healthy entertainment and is beneficial to the body and mind of the middle-aged and the elderly, the activities of the limbs and the movement of the joints can be achieved by batting with the wooden ball, the muscle exercise purpose can be achieved, and meanwhile, the sentiment can be mastered. The patient may be completed with family or selected to match the player at the gaming end. Before the patient hits the ball, the display device generates a standard action to guide the hitting of the ball, and when the patient hits the ball, trial exercise data is collected and analyzed to serve as a score p1 for completing the standard action; at the end of the game, the patient completes the grass hitting game scoring p 2. The rehabilitation training system is felt to early and middle period parkinsonism house motion that this embodiment provided can quantify early and middle period parkinsonism rehabilitation motion index under the human state of no sensor constraint, realizes double interactive training for whole house motion rehabilitation training is practical more high-efficient, various interesting, makes the patient obtain the sense value sense and constantly increases in the training process, thereby insists on rehabilitation training for a long time.
In summary, the content of the present specification should not be construed as a limitation to the present invention, and any changes made according to the design concept of the present invention are within the protection scope of the present invention.
Claims (10)
1. The utility model provides a rehabilitation training system is felt to early and middle stage parkinson's house motion body, its characterized in that includes:
the rehabilitation mat (1) is used for collecting gait motion data of a patient and sending the gait motion data to the somatosensory equipment, and guiding the patient to relieve the frozen gait in a rhythm manner;
the motion sensing device (2) is used for collecting the limb motion data of the patient and sending the data to the processing terminal;
the display device (3) is used for connecting the rehabilitation pad and the somatosensory device and displaying the virtual game rehabilitation scene and rehabilitation evaluation data;
the smart phone app (4) is used for recording effective motion data and rehabilitation evaluation data;
the processing terminal (5) is used for carrying out fusion processing on the obtained limb movement data and the gait movement data of the patient to obtain limb movement fusion data; and performing virtual scene motion rehabilitation training and guiding appointed actions by using the four-limb motion fusion data, performing rehabilitation evaluation and assisting in recovering the frozen gait.
2. The early-middle-stage Parkinson's home motion body feeling rehabilitation training system according to claim 1, wherein the rehabilitation mat comprises a top PU layer (1-1), a pressure sensing layer (1-2), a hydraulic vibration layer (1-3), an LED lamp strip (1-4), an anti-skid bottom layer (1-5), a wireless charging device (1-6), a storage battery (1-7), a power switch (1-8) and a wireless communication module (1-9);
the top PU layer (1-1), the pressure sensing layer (1-2), the hydraulic vibration layer (1-3) and the anti-skid bottom layer (1-5) are sequentially stacked from top to bottom, the pressure sensing layer (1-2) is used for collecting gait motion data of a patient, and the gait motion data comprises the weight, sole staying time, staying position and pressure area of the patient; the hydraulic vibration layer (1-3) is used for providing rhythmic vibration to guide the patient to regularly step; the LED lamp strip is arranged on the top PU layer (1-1) and used for providing regular flicker to guide a patient to regularly step;
the rehabilitation mat is powered by storage batteries (1-7), charged by a wireless charging device (1-6) and connected with a processing terminal (5) through a wireless communication module.
3. The early-middle-stage Parkinson's home motion body feeling rehabilitation training system according to claim 2, wherein the top PU layer is divided into a left part and a right part, and the LED lamp strip is arranged around the outer contours of the left part and the right part.
4. The early-middle-stage Parkinson's home motion body feeling rehabilitation training system according to claim 2, wherein the pressure sensing layers (1-2) comprise pressure sensors and pressure sensing processing modules which are uniformly distributed, the pressure sensors are used for acquiring real-time pressure data of all positions of the rehabilitation mat, and the pressure sensing processing modules are used for analyzing the real-time pressure data to obtain the weight, sole retention time, retention positions and pressure area data of a patient and sending the data to the processing terminal.
5. The early-middle-stage Parkinson's home motion body feeling rehabilitation training system according to claim 1, wherein the body feeling device collects a patient limb motion image through a kinect sensor, the kinect sensor is connected with a skeleton tracking algorithm through an API (application program interface) interface, 20 main joint position data of the patient are obtained in real time, and a time sequence of each joint position of the patient is obtained and used as limb motion data.
6. The early-middle-stage Parkinson's home motion body feeling rehabilitation training system according to claim 4 or 5, wherein the processing terminal comprises:
the data receiving module is used for receiving the motion data sent by the somatosensory device and the pressure sensing processing module, preprocessing the motion data and sending the preprocessed data to the data fusion module;
the data fusion module is used for fusing the received limb movement data of the patient and the gait movement data of the patient to obtain limb movement fusion data;
the virtual rehabilitation scene motion training module is used for providing various virtual rehabilitation motion scenes beneficial to recovery of a patient, mapping the four-limb motion fusion data into the motion scenes and scoring the training behaviors of the patient in the virtual rehabilitation scenes;
the rehabilitation evaluation module is used for extracting motion indexes according to the four-limb motion fusion data and carrying out rehabilitation evaluation; the motion index comprises the speeds of 20 main joints, the instantaneous phases of the speeds and the instantaneous phase change of the speeds;
and the emergency guiding module is used for comparing the difference value of the gait motion and the target motion data in the four-limb motion fusion data in real time, sending an emergency signal to the rehabilitation pad when the difference value is greater than a preset threshold value or stopping the gait motion, and guiding the patient to step by using the same-frequency vibration/flicker of the hydraulic vibration layer and the LED lamp strip.
7. The system of claim 6, wherein the data receiving module is configured to pre-process the data, and the time series of each joint position of the patient is filtered by a low-pass Butterworth filter with a cut-off frequency of 5 Hz.
8. The early-middle-stage Parkinson's home motion body feeling rehabilitation training system according to claim 6, wherein when the data fusion module fuses received limb motion data and gait motion data of a patient, coordinates of the two parts of motion data are unified firstly, and then weighted average processing is performed on data of the part where the acquisition ranges of the body feeling device and the rehabilitation pad are overlapped.
9. The early-mid-stage parkinsonism-family motion body feeling rehabilitation training system according to claim 1, wherein the training modes of the virtual rehabilitation scene motion training module include three types:
the first method is that a patient selects a designated motion, joint angle data in the motion is obtained, the difference between the actual motion joint angle and the target motion joint angle is compared, and table searching and scoring are carried out according to the difference;
the second is that the patient selects the recreational game with the appointed difficulty, the game is played according to the action guide, the number of completed tasks and the completion time are recorded, and the score is given; the entertainment game is a limb movement game comprising a plurality of tasks;
the third is that the designated action is combined with the amusement game and the weighted result of the two scores is used as the total score.
10. The early-middle parkinson-home-motion-sensing rehabilitation training system of claim 1, wherein the smartphone app comprises three functional modules:
the movement recording module is used for recording the frequency and the duration of the frozen gait and the corresponding gait movement data and providing a basis for rehabilitation training;
the health diary module is used for providing a memorandum for recording sleeping and medication conditions for a patient for the patient to conveniently review and understand the state of an illness;
and the account management module is used for verifying the login account.
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