TWI681360B - Rehabilitation monitoring system and method thereof for parkinson's disease - Google Patents

Abstract

A rehabilitation monitoring system and a method thereof for Parkinson’s disease are provided. The system includes a wearable apparatus, a computing apparatus and a display apparatus. The wearable apparatus is disposed with multiple sensors. The sensors sense motion attitudes of different body portions of a user. The computing apparatus evaluates a difference between the rehabilitation performed by the user and standard action. The display apparatus presents a simulated human model. The human model responds the current action of the user and provides indication of motion correction. The display apparatus also presents guide video. Accordingly, rehabilitation situation of patient can be monitored effectively, and achieving rate of patient for performing the action can be evaluated, so as to improve patient’s condition.

Description

Rehabilitation monitoring system and method applied to Parkinson's disease

The invention relates to a rehabilitation monitoring technology, and in particular to a rehabilitation monitoring system and method applied to Parkinson's disease.

Parkinson's disease is a chronic degenerative disease of the central nervous system. About 8 million people worldwide suffer from this disease. Its main symptoms include tremor, stiff limbs, deterioration of motor function, abnormal gait, and reduced speech volume. At present, in addition to drugs, surgical treatment and physical therapy, sports rehabilitation can also help patients recover and enhance muscle strength, joint flexibility, functional skills and endurance. For example, Lee Silverman Voice Treatment Big (LSVT BIG) is one of the preferred rehabilitation exercises for physicians.

LOUD BIG helps to improve the unique slow movements, stiff limbs, fine movements, and initial obstacles of patients with Parkinson's disease. It executes training on trunk rotation, balance ability, gait stability, and exercise execution speed to improve life quality. This rehabilitation method has been confirmed by research. If 4 times a week and 1 hour each time, a total of 16 hours of intensive training for a month, the therapeutic effect can be maintained for 6 months.

At present, the effectiveness of sports rehabilitation treatment for Parkinson's disease is based on a total of 16 evaluations by physicians every month, and physicians will combine multiple indicators for comprehensive scoring. However, these evaluation results are subjective judgments by physicians, and the two physicians may have different results. In addition, the scoring hierarchy currently evaluated is too simplified. Although there have been various experiments for measuring and recording dyskinesia or special conditions in the past, most of them can only be performed in clinical or laboratory. Although the rehabilitation situation can be evaluated through simulation, the results of such an assessment cannot truly represent the family living environment of the patient. It can be seen that the assessment of the rehabilitation situation in the prior art has not brought enough positive impact on the ultimate goal of rehabilitation treatment and improving the quality of life of patients.

Clinical physicians have three major problems in the rehabilitation process: (1) Does the patient return to the treatment process after returning home? (2) How long does each rehabilitation take? (3) How to track and analyze the rehabilitation process? In view of this, the present invention provides a rehabilitation monitoring system and method applied to Parkinson's disease, which can immediately determine whether the patient's rehabilitation exercise is standard, and its sensing data can also be used by the physician for diagnostic reference to make the rehabilitation exercise Can improve the condition more effectively.

The invention is applied to a rehabilitation monitoring system for Parkinson's disease, which includes a wearing device and a computing device. The wearable device includes several sensors, and these sensors are used to sense the movement postures of different body parts of the user. The computing device evaluates the difference between the user's rehabilitation movement and at least one standard movement based on the movement posture of these sensors. This rehabilitation exercise is about Parkinson's disease.

On the other hand, the present invention is applied to a rehabilitation monitoring method for Parkinson's disease, which includes the following steps. Sensing the movement posture of different body parts of the user. Based on the movement posture of these sensors, the difference between the user's rehabilitation exercise and the standard movement is evaluated. And this rehabilitation exercise is about Parkinson's disease.

Based on the above, in the rehabilitation monitoring system and method for Parkinson's disease according to the embodiments of the present invention, a wearable device is provided for the user to wear. The sensor on the wearable device can detect motion states such as acceleration, angular velocity, and magnetic force, and its setting position corresponds to the user's joints or other body parts, thereby obtaining the user's motion posture. Then, the sensed motion posture can be used to determine whether the user's motion conforms to the standard motion, so that the user can perform the rehabilitation exercise with the correct motion, and the obtained information can be used by the physician to track the rehabilitation state remotely.

In order to make the above-mentioned features and advantages of the present invention more obvious and understandable, the embodiments are specifically described below in conjunction with the accompanying drawings for detailed description as follows.

FIG. 1 is a schematic diagram of a rehabilitation monitoring system 1 according to an embodiment of the invention. Referring to FIG. 1, the rehabilitation monitoring system 1 includes at least but not limited to the wearable device 10, the computing device 30 and the display device 40.

The wearable device 10 can be worn by the user's upper body, lower body, limbs, or any body part, and its main body may be in the form of a jacket, pants, coat, or the like. In this embodiment, the wearable device is at least equipped with but not limited to one or more sensors 110 and a communication transmitter 130.

The sensor 110 may be an accelerometer, a gyroscope, a magnetometer, or a combination of three or more-axis sensing modules described above, and is used to sense acceleration, angular velocity, magnetic force, and other sensing data. Thus, the motion state of the set position is obtained, and then the user's motion posture is obtained. It is worth noting that a plurality of sensors 110 are respectively disposed on the main body of the wearable device 10. After the user puts on the wearable device 10, the sensors 110 correspond to, for example, the user's two-handed forearm, two-handed upper arm, spine, two-legged thigh, two-legged calf and other body parts, and can correspond to the four limbs, Joints in the neck and/or back. It should be noted that the number and position of the sensors 110 can be adjusted according to needs, and if the setting position can effectively represent the user's movement status (for example, two hands abduction, one foot forward bending, thoracolumbar flexion, etc.) This is the preferred location.

In addition, these sensors 110 may be respectively connected to a microcontroller. The microcontroller may use a direction cosine matrix (DCM) based on the acceleration signal, angular velocity signal and magnetometer signal obtained by the sensor 110, or Algorithms such as Madgwick calculate the posture Euler angle (pitch, roll, yaw) as the motion posture corresponding to the body part (for example, the angle between shoulder and elbow, hip joint, etc.) value). In some embodiments, the sensor 110 may have a built-in basic controller to directly derive the motion gesture.

The communication transmitter 130 may be a wireless communication transmitter such as Bluetooth, Wi-Fi, infrared, etc., or a Universal Serial Bus (USB), Thunderbolt, Universal Asynchronous Receiver/Transmitter , UART) and other wired transmission interfaces, and used to send data related to the movement postures of different body parts to the outside world (ie, external devices).

The computing device 30 may be an electronic device such as a desktop computer, a notebook computer, a smartphone, a tablet computer, etc., which has at least a processor, a receiver corresponding to the communication transmitter 130, and a memory to obtain data from the wearable device 10 The action posture-related data is used to analyze and evaluate the action posture, the details of which will be described in subsequent embodiments.

The display device 40 is connected to the computing device 30, and may be a liquid crystal display (LCD), a light emitting diode (LED) display, an organic light emitting diode (Organic Light Emitting Diode, OLED) display, etc. Various types of displays. The computing device 30 can control the display device 40 to present a picture, the details of which will be described in subsequent embodiments.

In order to facilitate understanding of the operation process of the embodiment of the present invention, a number of embodiments will be described in detail below to describe the monitoring process for the rehabilitation exercise of Parkinson's disease in the embodiment of the present invention. Hereinafter, the methods described in the embodiments of the present invention will be described with various devices, components, and modules in the rehabilitation monitoring system 1. The various processes of the method can be adjusted according to the implementation situation, and it is not limited to this.

2 is a flowchart of a rehabilitation monitoring method according to an embodiment of the invention. Please refer to FIG. 2, the sensor 110 will sense the movement posture of different body parts of the user (step S210 ). In this embodiment, different sensors 110 are installed on the main body of the wearable device 10 to correspond to different body parts of the user, and the movement or physical state such as acceleration, angular velocity, magnetic force, etc. can be obtained in real time, and actions can be obtained through algorithms such as DCM Posture-related data (for example, Euler angles), these data can be used as representative data of the motion posture of each body part.

Next, the communication transmitter 130 transmits the motion posture-related data to the computing device 30. The computing device 30 can evaluate the difference between the user's rehabilitation exercise and the standard movement according to the movement posture sensed by the sensor 110 (step S230). Specifically, taking the LSVT BIG Parkinson's disease rehabilitation exercise as an example, it includes seven exercises (for example, Floor to Ceiling), Forward Step and Reach, Forward Step and Reach, Rear Span and Reach ( Backward Step and Reach), etc., and each rehabilitation exercise also includes different actions (for example, step after sitting, step before right, etc.). The patient's achievement rate of these actions is an important data for evaluating the rehabilitation process.

In order to assist the patient to clearly know whether his movement conforms to the standard movement of rehabilitation exercise, the embodiment of the present invention may provide an interface to simulate the posture of the human body. The computing device 30 may simulate the user's character model based on a system such as a rendering engine for two-dimensional or three-dimensional images, a computer animation, a game engine (for example, Unity, Havok, Chrome Engine, etc.) (step S231). This character model is a pre-set 2D or 3D humanoid object. For example, FIG. 3 is a schematic diagram illustrating a three-dimensional character model HM according to an embodiment. Please refer to FIG. 3, each indicating point IL of the character model HM corresponds to each sensor 110 of the wearable device 10. In addition, these indicator points IL are joints or auxiliary reference points used to describe the anatomical plane and the angle of motion.

The computing device 30 can present a screen through which the character model HM moves synchronously according to the motion posture of those sensors through the display device 40 (step S233). The arithmetic device 30 can first correct the character model HM. For example, the patient maintains the following fixed postures: feet close together, hands naturally laid down, torso straight (ie, standing upright), and correction is completed after 5 seconds. In the Unity environment, limb normalization is performed with the child object, and the reading value of the sensor 110 is received with the parent object to perform limb movement simulation. After the calibration is completed, the child object will rotate synchronously with the parent object, and the user can start the rehabilitation exercise.

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可代表使用者的肢體及軀幹。而二維或三維空間中兩向量之間的夾角可基於向量內積公式得出。不同夾角可作為評估動作姿態的特徵角度θ。例如，左肩外展、右肩外展、胸腰屈曲伸直、胸腰旋轉、左肩屈曲伸直、右肩屈曲伸直、左肘屈曲伸直、右肘屈曲伸直、左髖外展、右髖外展、左髖屈曲伸直、右髖屈曲伸直、左膝屈曲、右膝屈曲、左髖外轉、右髖外轉、水平左肩外展、水平右肩外展等特徵角度。 During the rehabilitation exercise, the exercise device 30 can evaluate the exercise ability. The computing device 30 can calculate the specific motion feature angle according to the motion posture related data. Specifically, FIG. 4 is a schematic diagram illustrating the definition of vectors on the character model HM according to an embodiment. Please refer to Figure 4, these vectors

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Can represent the user's limbs and torso. The angle between two vectors in two-dimensional or three-dimensional space can be obtained based on the vector inner product formula. Different angles can be used as the characteristic angle θ to evaluate the action posture. For example, left shoulder abduction, right shoulder abduction, thoracolumbar flexion and extension, chest and waist rotation, left shoulder flexion and extension, right shoulder flexion and extension, left elbow flexion and extension, right elbow flexion and extension, left hip abduction, right Hip abduction, left hip flexion and extension, right hip flexion and extension, left knee flexion, right knee flexion, left hip abduction, right hip abduction, horizontal left shoulder abduction, horizontal right shoulder abduction and other characteristic angles.

The computing device 30 records the corresponding spatial positions and characteristic angles of different body parts under different standard movements in different rehabilitation exercises, and the computing device 30 can compare the corresponding spatial positions and/or characteristic angles of the data detected by the sensor 110 with The standard movement corresponds to the difference between the spatial position and/or the characteristic angle (eg, distance difference, included angle, etc.), thereby evaluating the difference between the rehabilitation exercise performed by the user and the standard movement.

In an embodiment, the computing device 30 can display a screen of whether the corresponding body part on the character model HM conforms to the standard motion through the display device 40 according to the difference (step S235). Taking FIG. 3 as an example, when the difference between the spatial position corresponding to the detection data of the sensor 110 and the standard motion is less than the first threshold, it means that the user’s current motion gesture achievement degree exceeds 75%; and If the difference is between the first and second thresholds, it means that the degree of achievement of the current gesture is between 50% and 75%; and if the difference is greater than the second threshold, it means that the degree of achievement is not Fifty percent. The corresponding indication point IL on the character model HM serves as a warning light, and the computing device 30 controls the change of the warning light according to the difference between the motion posture of each joint part and the standard motion. For example, the computing device 30 may present, for example, green (indicating that the achievement rate exceeds 75%) and yellow (indicating that the achievement degree is 50% to 75%), red (less than 50%) and other different visual expressions to help users understand whether their body parts meet standard movements or reach.

It should be noted that FIG. 3 is only an example for showing the difference from the standard action. In other embodiments, the computing device 30 can pass text through the display device 30 (eg, left shoulder forward, right elbow outward, etc.) ), graphics (for example, correct graphics, data curve graphs, data tree diagrams, etc.) and other forms, and may also play action correction prompt messages through speakers (ie, speakers). The values of standard actions can be set in advance and adjusted afterwards.

In addition, the flow of each action in the rehabilitation exercise includes start, execution, and end. Different actions and signal determination ranges may be different. For example, the criterion for step forward action determination is that the characteristic angle of shoulder abduction needs to be greater than 30 degrees, and the action is not determined until this angle is less than 30 degrees. For comparison and analysis, the computing device 30 can remove the specific percentages (eg, 10%, 25, 45, etc.) before and after the signal corresponding to each characteristic angle to compare the effects of different sampling ranges on posture interpretation.

In order to assist the patient in adopting correct movements during the rehabilitation exercise or to solve the problem of the patient forgetting the movement, the computing device 30 can also present a guide video of the standard movements through the display device 40 (when the person performs the rehabilitation exercise in the standard movements) Video recording). For example, FIG. 5 is a schematic diagram illustrating a guide movie and a character model according to an embodiment. Referring to FIG. 5, the screen presented by the display device 40 may combine the guide film GV and the character model HM corresponding to the sensing data obtained by the sensor 110, and the character model HM is presented in a mirror image. For example, if the patient steps out of the left foot, the character model HM also steps out of the left foot simultaneously. In this way, the patient can clearly get the content of the rehabilitation exercise, and can also instantly know the difference between his own movement and the standard movement.

In order to avoid that the screen of the display device 40 is too chaotic and affects the visual experience in the case of multi-person rehabilitation, please refer to FIG. 6 which is a schematic diagram illustrating a guide video and a plurality of character models. In the case of multi-person rehabilitation, the display device 40 only needs to play a single guide video GV, and the character models HM corresponding to different patients are allocated to different areas in the screen. It should be noted that the foregoing embodiments use videos to guide the movements. However, in some embodiments, the computing device 30 may also play motion instructions about the rehabilitation exercise through the speaker.

In addition to the data related to the motion posture obtained by the sensor 110, in addition to immediately reflecting whether the patient's posture is correct, the data can be further uploaded or sent to the computer device of the physician (taking the computing device 30 as an example, or other computing devices). The computing device 30 can count the change of each characteristic angle when the patient performs the same action multiple times, and can compare with the characteristic angle corresponding to the standard action, so as to assist the doctor to judge the progress or regression of the patient in the rehabilitation exercise.

For example, Table (1) is an example illustrating the measurement of the characteristic angle of the left and right shoulder abduction. Assuming that the corresponding characteristic angle of the standard movement is 70 degrees, the left shoulder abduction is from 59.01 degrees to 66.70 degrees, so there is a progress of about 13%; and the right shoulder abduction is from 72.86 degrees to 71.44 degrees, so there is a percentage The magnitude of the regression is about two. The average value and maximum value of the seven repetitive actions can also be compared with the corresponding characteristic angles of the standard actions as a reference for judging the achievement rate. Table 1) order 1 2 3 4 5 6 7 Left shoulder abduction 59.01 60.19 60.66 60.93 62.63 71.23 66.70 Right shoulder abduction 72.86 74.35 63.47 77.29 76.35 69.00 71.44

In addition, the computing device 30 can also obtain historical rehabilitation data, which is related to the movement postures detected by a user in the previous rehabilitation exercise (for example, three days ago, one month ago Attitude-related data). The computing device 30 can compare the currently sensed motion posture with historical rehabilitation data to obtain a comparison result before and after rehabilitation. In addition, the computing device 30 can also record the length of time each patient performs rehabilitation exercise as an assessment of the completion of rehabilitation exercise.

In summary, the embodiments of the present invention are applied to a rehabilitation monitoring system and method for Parkinson's disease, which provides an interactive interface so that patients can simulate a disease through the interface after wearing a wearable device equipped with a sensor The patient’s movements enable the patient to know in time whether the movements are correct or the achievement rate with the standard movements. The interface can also present guide videos to let patients understand the current actions performed. In addition, the statistics on the movement posture can help the doctor to diagnose the patient's achievement rate and status of rehabilitation exercise remotely after statistics.

Although the present invention has been disclosed as above with examples, it is not intended to limit the present invention. Any person with ordinary knowledge in the technical field can make some changes and modifications without departing from the spirit and scope of the present invention. The scope of protection of the present invention shall be subject to the scope defined in the appended patent application.

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‧‧‧向量 θ‧‧‧特徵角度1‧‧‧Rehabilitation monitoring system 10‧‧‧Wearing device 110‧‧‧Sensor 130‧‧‧Communication transmitter 30‧‧‧Calculation device 40‧‧‧Display device S210~S235‧‧‧Step HM‧‧ ‧Character model IL‧‧‧Guide point GV‧‧‧Guide film

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‧‧‧Vector θ‧‧‧Characteristic angle

FIG. 1 is a schematic diagram of a rehabilitation monitoring system according to an embodiment of the invention. 2 is a flowchart of a rehabilitation monitoring method according to an embodiment of the invention. FIG. 3 is a schematic diagram illustrating a three-dimensional character model according to an embodiment. FIG. 4 is a schematic diagram illustrating the definition of vectors on a character model according to an embodiment. FIG. 5 is a schematic diagram illustrating an embodiment of a guide film and a character model. 6 is a schematic diagram illustrating an embodiment of a guide film and plural character models.

S210~S235‧‧‧Step

Claims (6)

A rehabilitation monitoring system applied to Parkinson's disease, including: a wearable device, including: a plurality of sensors for sensing the movement posture of a user's different body parts; an arithmetic device, based on The movement postures of the sensors evaluate the difference between the user's rehabilitation exercise and at least one standard movement, wherein the rehabilitation exercise is related to Parkinson's disease, and the difference includes the movement posture of at least one joint part and the at least one A difference between a standard action; and a display device, the computing device constructs at least a two-dimensional character model of the user, presents the character model through the display device to move synchronously according to the motion posture of the sensors, and According to the difference, whether the corresponding body part on the character model conforms to the at least one standard action is displayed through the display device, wherein the computing device defines a plurality of vectors for the limb and torso of the character model respectively, and calculates the characteristics between the two Angle, the difference between the spatial position and the characteristic angle corresponding to the motion posture of the user's body part and the spatial position and the characteristic angle corresponding to the at least one standard motion, and the computing device through the display device in the A warning light is displayed on the joint part of the character model, and the change of the warning light on each of the at least one joint part is controlled according to the difference. The rehabilitation monitoring system for Parkinson's disease as described in item 1 of the patent application scope, wherein the computing device presents the guide video of the at least one standard action through the display device. The rehabilitation monitoring system for Parkinson's disease as described in item 1 of the patent application scope, wherein the computing device obtains at least one historical rehabilitation data, wherein the at least one historical rehabilitation data relates to the user's previous The motion posture detected by the rehabilitation exercise, and the computing device compares the currently sensed motion posture with the at least one historical rehabilitation data to obtain a comparison result before and after rehabilitation. A rehabilitation monitoring method applied to Parkinson's disease includes: sensing a user's movement posture of different body parts; and evaluating the difference between the user's rehabilitation exercise and at least one standard movement based on the movement posture, wherein In regard to Parkinson's disease, the difference in the rehabilitation exercise includes the difference between the movement posture of at least one joint part and the at least one standard movement, and the step of evaluating the difference includes: constructing at least a two-dimensional character model of the user Defining multiple vectors for the limbs and torso of the character model, and calculating the characteristic angle between the two vectors; comparing the spatial position and characteristic angle corresponding to the movement posture of the user's body part with the at least one standard movement The difference between the corresponding spatial position and characteristic angle; presenting the character model to move synchronously according to the action posture, and presenting warning lights on the joint parts of the character model; and According to the difference, whether the corresponding body part on the character model meets the at least one standard action is presented, wherein the change of the warning light on each of the at least one joint part is controlled according to the difference. The rehabilitation monitoring method applied to Parkinson's disease as described in item 4 of the patent application scope, wherein before the step of evaluating the difference between the rehabilitation exercise of the user and the at least one standard action, the method further includes: presenting the at least one standard Action guided videos. The rehabilitation monitoring method applied to Parkinson's disease as described in item 4 of the patent application scope, wherein the step of evaluating the difference between the user's rehabilitation exercise and the at least one standard action further includes: obtaining at least one historical rehabilitation Health data, wherein the at least one historical rehabilitation data relates to the motion posture detected by the user during the previous rehabilitation exercise; and comparing the currently sensed motion posture with the at least one historical rehabilitation data to obtain Compare the results before and after rehabilitation.

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