A method, device and system for determining compensation in rehabilitation training

Abstract

The present invention discloses a method for determining compensation in rehabilitation training, comprising: executing a pre-set task; detecting and obtaining the weight loss data, double plantar pressure feedback data and surface electromyography data of the overhead rail user according to the executed task; and judging the user's status according to the weight loss data, double plantar pressure feedback data and surface electromyography data of the overhead rail user. The present invention also proposes a device and system for determining compensation in rehabilitation training. Through the present invention, the degree of user compensation can be objectively assessed, and the "whether or not compensation" and "degree of compensation" can be presented to the user and the person responsible for the user's rehabilitation training in an intuitive form, prompting the user to avoid using compensation strategies during rehabilitation training and strengthening the user's rehabilitation initiative.

Description

Technical Field

[0001] The present invention relates to the field of medical rehabilitation training, and in particular to a method, device and system for determining compensation in rehabilitation training. Background Art

[0002] After a user suffers severe spinal cord injury in the lower thoracic or lumbar regions due to various reasons, sensory and motor dysfunction below the injury level may occur. These dysfunctions can directly affect the function of some of the user's trunk muscles and all of their lower limb muscles.

[0003] For this type of user, the general clinical manifestations are: weakness of the lower trunk muscles, which makes it difficult for the user to maintain an independent sitting position and unable to keep the trunk stable when standing; weakness of the hip muscles, among which weakness of the gluteus maximus causes the user to be unable to stand straight forward and backward, and weakness of the gluteus medius causes the user to be unstable when standing left and right; weakness of both lower limbs causes the user to be unable to maintain a stable posture and walk.

[0004] To address the above situation, rehabilitation clinical treatment often combines weight-reducing devices, walkers, and knee-ankle-foot orthoses to provide users with repeated functional walking training. However, during training, users often consciously or unconsciously use the following compensatory strategies:

[0005] (1) When standing, use both upper limbs to support the walker upwards, increasing trunk stability while reducing the weight on both lower limbs and compensating for the weak gluteus maximus;

[0006] (2) When taking a step, use both upper limbs to support the walker upwards, reducing the weight on the lower limbs, reducing the friction on the soles of the feet, and reducing the difficulty of "hip flexion stepping";

[0007] (3) When taking a step, use the contraction of the trunk muscles instead of "hip flexion" to take a step.

[0008] From the above compensatory strategies, it can be seen that "compensation" in rehabilitation training for users with severe spinal cord injuries in the lower thoracic and lumbar segments actually means: "reducing the effective load on the lower limbs", "insufficient activation of target muscles", and "overactivation of non-target muscles". The use of compensatory strategies has greatly reduced the difficulty of rehabilitation training for users and lost the original core of rehabilitation training. In addition, many studies have shown that the lower limb motor function of users with severe spinal cord injuries can be improved after long-term and rigorous active motor function rehabilitation training. Therefore, during long-term rehabilitation training, users should fully mobilize their own initiative, increase control over the injured limb, minimize "compensatory" activities, and ensure the quality of daily rehabilitation training.

[0009] However, in actual clinical rehabilitation treatment, whether or not users with severe lower thoracic and lumbar spinal cord injuries experience "compensation" and the degree of "compensation" are primarily determined by medical staff's subjective experience. This assessment is inconsistent across different medical staff, and objective assessment methods are lacking. Furthermore, existing rehabilitation equipment cannot provide users or medical staff with real-time, accurate feedback on "compensation" phenomena.

[0010] At present, there is no complete set of rehabilitation assessment methods and assessment equipment in clinical practice to correct the "compensation strategy" in walking rehabilitation training for users with severe spinal cord injuries in the lower thoracic and lumbar segments. When users are training, all compensatory movements require medical staff to observe and judge the users. The general judgment method is: if the user is found to be overexerting both upper limbs during standing or walking, it can be determined that the user is using both upper limbs to compensate for weight loss; if the user is found to be twisting the trunk with force during walking, and the weight-bearing upper limb is using force to support the walker, it can be determined that the user is using trunk muscles to compensate for walking while performing weight loss compensation.

[0011] In addition, due to the characteristics of the user's injury, there is no obvious feeling or movement below the injury plane. Therefore, without the assistance of others, the user cannot immediately know the status below the spinal cord injury plane, "whether to use force" and "whether the force method is correct". At this stage, the means for users to obtain the above information still rely on the observation and reminders of medical staff. It is not difficult to see from the above clinical solutions that when users with severe spinal cord injuries in the lower thoracic and lumbar segments undergo walking rehabilitation training, the main means of correcting the "compensation" phenomenon is to judge based on the medical staff's own experience, and there is no corresponding equipment for objective judgment and feedback. Summary of the Invention

[0012] To solve the problems existing in the prior art, the present invention proposes a method for determining compensation in rehabilitation training, comprising:

[0013] Execute pre-set tasks;

[0014] According to the tasks performed, the weight loss data, double plantar pressure feedback data and surface electromyography data of the SkyRail users are detected and obtained;

[0015] The user's status is determined based on the SkyRail user's weight loss data, double foot pressure feedback data and surface electromyography data.

[0016] The pre-set tasks include: hanging baseline assessment, weight-reduced standing assessment and / or weight-reduced walking assessment.

[0017] The weight loss data of the Skyrail user is the data of the weight loss of the user after the user uses the Skyrail weight loss walking device;

[0018] The surface electromyography data is the surface electromyography data of the user collected by a surface electromyography acquisition device;

[0019] The dual plantar pressure feedback data is dual plantar pressure data detected by the plantar pressure sensor and fed back in real time.

[0020] The method of judging the user's status based on the weight loss data, the pressure feedback data of both feet and the surface electromyography data of the SkyTrain user is as follows:

[0021] Determine the weight reduction of the Skyrail weight-loss walking device according to the obtained user weight, and obtain the Skyrail user's weight reduction data;

[0022] According to the pressure feedback data of both soles of the feet, the actual weight bearing data of both lower limbs are calculated;

[0023] The user's upper limb support compensation amount is calculated based on the user's weight, the weight loss data of the SkyRail user, and the actual weight bearing data of the lower limbs;

[0024] According to the obtained compensation amount of the user's upper limb support, it is judged whether the user is in a compensated state or a non-compensated state;

[0025] When the user is in a compensated state or an uncompensated state, the user's muscle state is judged based on surface electromyography data.

[0026] The amount of support compensation for the user's upper limbs is calculated based on the user's weight, the weight loss data of the SkyRail user, and the actual weight bearing data of the lower limbs, specifically:

[0027] User's upper limb support compensation (%) = [(user's weight - SkyTrack user weight loss data - actual lower limb weight data) / user's weight] * 100%;

[0028] Among them, the actual weight-bearing data of both lower limbs = the weight-bearing data of the left lower limb + the weight-bearing data of the right lower limb.

[0029] Wherein, when the preset task is a suspended baseline assessment, the user's upper limb support compensation amount is 0, and the user is determined to be in a non-compensated state.

[0030] Among them, when the user is in an uncompensated state, the user's muscle state is judged based on surface electromyography data;

[0031] If the surface electromyography channel electromyography voltage value of the surface electromyography data is less than or equal to 10μv, the user relaxes the whole body;

[0032] If the surface electromyography channel electromyography voltage value of the surface electromyography data is greater than 10μv, the user is in a state of tension, muscle spasm or movement.

[0033] Among them, when the preset task is weight loss standing assessment or weight loss walking assessment, if the user's upper limb support compensation amount is greater than 0, it is determined that the user is in a compensated state.

[0034] Wherein, the pre-set task is weight-loss standing assessment or weight-loss walking assessment, and when the user is in a compensatory state, the user's muscle state is judged based on surface electromyography data;

[0035] If the surface EMG channel voltage value representing the gluteus maximus, gluteus medius, and quadriceps femoris in the surface EMG data is continuously greater than 15 μV, it means that the gluteus maximus, gluteus medius, and quadriceps femoris are actively contracting and exerting force;

[0036] If the surface electromyography channel electromyography voltage values representing the rectus abdominis, transverse abdominal muscles, and erector spinae muscles in the surface electromyography data continue to rise, it indicates that the trunk muscles are exerting force.

[0037] The method further includes: recording the weight loss data, surface electromyography data and double plantar pressure feedback data of the sky rail user obtained by the detection;

[0038] The weight loss data of the sky rail user, the pressure feedback data of both feet and the surface electromyography data are output to the electronic audio-visual feedback device.

[0039] The present invention also provides a device for determining compensation during rehabilitation training, comprising:

[0040] An execution unit, used to execute pre-set tasks;

[0041] A detection unit is used to detect and obtain the weight loss data, double plantar pressure feedback data and surface electromyography data of the sky rail user according to the tasks performed;

[0042] The judgment unit is used to judge the user's status based on the weight loss data of the sky rail user, the pressure feedback data of both feet and the surface electromyography data.

[0043] The pre-set tasks include: hanging baseline assessment, weight-reduced standing assessment and / or weight-reduced walking assessment.

[0044] The weight loss data of the Skyrail user is the data of the weight loss of the user after the user uses the Skyrail weight loss walking device;

[0045] The surface electromyography data is the surface electromyography data of the user collected by a surface electromyography acquisition device;

[0046] The dual plantar pressure feedback data is dual plantar pressure data detected by the plantar pressure sensor and fed back in real time.

[0047] The method of judging the user's status based on the weight loss data, the pressure feedback data of both feet and the surface electromyography data of the SkyTrain user is as follows:

[0048] Determine the weight reduction of the Skyrail weight-loss walking device according to the obtained user weight, and obtain the Skyrail user's weight reduction data;

[0049] According to the pressure feedback data of both soles of the feet, the actual weight bearing data of both lower limbs are calculated;

[0050] The user's upper limb support compensation amount is calculated based on the user's weight, the weight loss data of the SkyRail user, and the actual weight bearing data of the lower limbs;

[0051] According to the obtained compensation amount of the user's upper limb support, it is judged whether the user is in a compensated state or a non-compensated state;

[0052] When the user is in a compensated state or an uncompensated state, the user's muscle state is judged based on surface electromyography data.

[0053] The amount of support compensation for the user's upper limbs is calculated based on the user's weight, the weight loss data of the SkyRail user, and the actual weight bearing data of the lower limbs, specifically:

[0054] User's upper limb support compensation (%) = [(user's weight - SkyTrack user weight loss data - actual lower limb weight data) / user's weight] * 100%;

[0055] Among them, the actual weight-bearing data of both lower limbs = the weight-bearing data of the left lower limb + the weight-bearing data of the right lower limb.

[0056] Wherein, when the preset task is a suspended baseline assessment, the user's upper limb support compensation amount is 0, and the user is determined to be in a non-compensated state.

[0057] Among them, when the user is in an uncompensated state, the user's muscle state is judged based on surface electromyography data;

[0058] If the surface electromyography channel electromyography voltage value of the surface electromyography data is less than or equal to 10μv, the user relaxes the whole body;

[0059] If the surface electromyography channel electromyography voltage value of the surface electromyography data is greater than 10μv, the user is in a state of tension, muscle spasm or movement.

[0060] Among them, when the preset task is weight loss standing assessment or weight loss walking assessment, if the user's upper limb support compensation amount is greater than 0, it is determined that the user is in a compensated state.

[0061] Wherein, the pre-set task is weight-loss standing assessment or weight-loss walking assessment, and when the user is in a compensatory state, the user's muscle state is judged based on surface electromyography data;

[0062] If the surface EMG channel voltage value representing the gluteus maximus, gluteus medius, and quadriceps femoris in the surface EMG data is continuously greater than 15 μV, it means that the gluteus maximus, gluteus medius, and quadriceps femoris are actively contracting and exerting force;

[0063] If the surface electromyography channel electromyography voltage values representing the rectus abdominis, transverse abdominal muscles, and erector spinae muscles in the surface electromyography data continue to rise, it indicates that the trunk muscles are exerting force.

[0064] The device further comprises: a recording unit for recording the weight loss data, surface electromyography data and double plantar pressure feedback data of the sky rail user obtained by detection;

[0065] The output unit is used to output the weight loss data of the sky rail user, the pressure feedback data of both feet and the surface electromyography data to the electronic audio-visual feedback device.

[0066] The present invention also proposes a system for determining compensation in rehabilitation training, comprising: a system host, a sky-rail weight-reducing walking device, a plantar pressure sensor, and a surface electromyography acquisition device;

[0067] The system host executes pre-set tasks;

[0068] The system host detects and obtains the weight loss data, double foot pressure feedback data and surface electromyography data of the sky rail user according to the tasks performed;

[0069] The system host determines the user's status based on the user's weight loss data, double foot pressure feedback data and surface electromyography data.

[0070] The pre-set tasks include: hanging baseline assessment, weight-reduced standing assessment and / or weight-reduced walking assessment.

[0071] The weight loss data of the Skyrail user is the data of the weight loss of the user after the user uses the Skyrail weight loss walking device;

[0072] The surface electromyography data is the surface electromyography data of the user collected by a surface electromyography acquisition device;

[0073] The dual plantar pressure feedback data is dual plantar pressure data detected by the plantar pressure sensor and fed back in real time.

[0074] The method of judging the user's status based on the weight loss data, the pressure feedback data of both feet and the surface electromyography data of the SkyTrain user is as follows:

[0075] Determine the weight reduction of the Skyrail weight-loss walking device according to the obtained user weight, and obtain the Skyrail user's weight reduction data;

[0076] According to the pressure feedback data of both soles of the feet, the actual weight bearing data of both lower limbs are calculated;

[0077] The user's upper limb support compensation amount is calculated based on the user's weight, the weight loss data of the SkyRail user, and the actual weight bearing data of the lower limbs;

[0078] According to the obtained compensation amount of the user's upper limb support, it is judged whether the user is in a compensated state or a non-compensated state;

[0079] When the user is in a compensated state or an uncompensated state, the user's muscle state is judged based on surface electromyography data.

[0080] The amount of support compensation for the user's upper limbs is calculated based on the user's weight, the weight loss data of the SkyRail user, and the actual weight bearing data of the lower limbs, specifically:

[0081] User's upper limb support compensation (%) = [(user's weight - SkyTrack user weight loss data - actual lower limb weight data) / user's weight] * 100%;

[0082] Among them, the actual weight-bearing data of both lower limbs = the weight-bearing data of the left lower limb + the weight-bearing data of the right lower limb.

[0083] Wherein, when the preset task is a suspended baseline assessment, the user's upper limb support compensation amount is 0, and the user is determined to be in a non-compensated state.

[0084] Among them, when the user is in an uncompensated state, the user's muscle state is judged based on surface electromyography data;

[0085] If the surface electromyography channel electromyography voltage value of the surface electromyography data is less than or equal to 10μv, the user relaxes the whole body;

[0086] If the surface electromyography channel electromyography voltage value of the surface electromyography data is greater than 10μv, the user is in a state of tension, muscle spasm or movement.

[0087] Among them, when the preset task is weight loss standing assessment or weight loss walking assessment, if the user's upper limb support compensation amount is greater than 0, it is determined that the user is in a compensated state.

[0088] Wherein, the pre-set task is weight-loss standing assessment or weight-loss walking assessment, and when the user is in a compensatory state, the user's muscle state is judged based on surface electromyography data;

[0089] If the surface EMG channel voltage value representing the gluteus maximus, gluteus medius, and quadriceps femoris in the surface EMG data is continuously greater than 15 μV, it means that the gluteus maximus, gluteus medius, and quadriceps femoris are actively contracting and exerting force;

[0090] If the surface electromyography channel electromyography voltage values representing the rectus abdominis, transverse abdominal muscles, and erector spinae muscles in the surface electromyography data continue to rise, it indicates that the trunk muscles are exerting force.

[0091] The system host also records the weight loss data, surface electromyography data and double plantar pressure feedback data of the sky rail user obtained by the detection;

[0092] The system host outputs the weight loss data of the sky rail user, the pressure feedback data of both feet and the surface electromyography data to the electronic audio-visual feedback device.

[0093] The present invention also provides a system for determining compensation in rehabilitation training, the system comprising a processor and a memory storing a computer program, and when the computer program is run by the processor, the method for determining compensation in rehabilitation training is executed.

[0094] This invention quantitatively defines incorrect training methods for "compensation" during rehabilitation training and proposes a solution for assessing "compensation" during rehabilitation training. This allows users with severe sensorimotor impairments below the injury level to intuitively observe functional changes, identify correct rehabilitation training methods, and improve the efficiency of their rehabilitation training. It also partially addresses the drawbacks of relying on medical staff's personal experience to determine user "compensation," thereby improving the efficiency of rehabilitation diagnosis and treatment.

[0095] Through the present invention, the degree of user compensation can be objectively assessed, and the "whether or not compensation" and "degree of compensation" can be presented to the user and the person responsible for the user's rehabilitation training in an intuitive form, prompting the user to avoid using compensation strategies during rehabilitation training and strengthening the user's rehabilitation initiative. BRIEF DESCRIPTION OF THE DRAWINGS

[0096] Figure 1 This is a schematic structural diagram of a system for determining compensation in rehabilitation training according to the present invention;

[0097] Figure 2 A schematic flow chart of a method for determining compensation in rehabilitation training according to the present invention;

[0098] Figure 3 This is a schematic structural diagram of a device for determining compensation in rehabilitation training according to the present invention;

[0099] Figure 4 This is a schematic structural diagram of a system for determining compensation in rehabilitation training according to the present invention. DETAILED DESCRIPTION

[0100] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of the present invention.

[0101] In order to solve the above problems, the present invention proposes a system for determining compensation during rehabilitation training, which can (1) quantify the actual load-bearing situation of the lower limbs of users with severe spinal cord injuries in the lower thoracic and lumbar segments, (2) clarify whether the target muscles are actively contracted and whether the non-target muscles are overactivated during the user's rehabilitation training, and (3) simultaneously provide the user with real-time visual and auditory feedback, promptly clarify the user's various "compensation" situations, guide the user to perform correct rehabilitation training, and ensure the rehabilitation effect.

[0102] like Figure 1 As shown, a system for determining compensation in rehabilitation training of the present invention includes:

[0103] Rehabilitation training part: Skyrail weight-reducing walking device;

[0104] Auxiliary training part: walker, knee-ankle-foot orthosis;

[0105] Information feedback part: surface electromyography acquisition device, plantar pressure sensor, electronic visual and auditory feedback device;

[0106] The plantar pressure sensor includes the left and right feet, and is a double plantar pressure sensor.

[0107] The electronic audio-visual feedback device can be a display screen that can display and play pictures, audio and video, etc.

[0108] System host part: integrates the signal input and processing of each part, and outputs it to the electronic audio-visual feedback device.

[0109] All electronic devices communicate with the system host, which analyzes and synthesizes the information in real time and transmits the results to the electronic audio-visual feedback device, allowing medical staff to quantitatively understand the user's "degree of compensation" during training and "where compensation occurs." It also allows users to promptly understand their own "compensation issues," allowing them to make adjustments and correct any errors immediately.

[0110] The present invention also proposes a method for determining compensation in rehabilitation training, such as Figure 2 As shown, the following steps are included:

[0111] Step 1: The system host executes the pre-set tasks.

[0112] Pre-set tasks include: hanging baseline assessment, weight-reduced standing assessment, and weight-reduced walking assessment.

[0113] Step 2: Based on the tasks being performed, the system host detects and obtains the weight loss data, double foot pressure feedback data and surface electromyography data of the sky rail user.

[0114] Skyrail user weight loss data: refers to the user's weight loss data after using the Skyrail weight loss walking device.

[0115] For example, if a user weighs 50 kg and loses 20 kg by using the Skyrail weight-reducing walking device, then 20 kg is the weight loss data of the Skyrail user.

[0116] Surface EMG data: refers to the user's surface EMG data collected by a surface EMG acquisition device (surface EMG electrodes are placed on the bellies of the following muscles via self-adhesive electrode sheets: rectus abdominis, transverse abdominals, erector spinae, gluteus maximus, gluteus medius, and quadriceps femoris).

[0117] Dual plantar pressure feedback data: refers to the dual plantar pressure data detected by the plantar pressure sensor and instantly fed back by the plantar pressure sensor.

[0118] In this step, the system host also records the obtained weight loss data of the sky rail user, the pressure feedback data of both feet and the surface electromyography data.

[0119] The system host also outputs the weight loss data of the sky rail user, the pressure feedback data of both feet and the surface electromyography data to the electronic audio-visual feedback device.

[0120] Step 3: The system host determines the user's status based on the weight loss data of the sky rail user, the pressure feedback data of both feet and the surface electromyography data.

[0121] Specifically:

[0122] The system host determines the weight reduction of the overhead rail weight-reducing walking device according to the obtained user weight, and obtains the weight reduction data of the overhead rail user;

[0123] The system host calculates the actual weight bearing data of both lower limbs based on the pressure feedback data of both soles of the feet;

[0124] The system host calculates the user's upper limb support compensation amount based on the user's weight, the weight loss data of the sky rail user, and the actual weight load data of the lower limbs;

[0125] The system host determines whether the user is in a compensated state or a non-compensated state based on the obtained compensation amount of the user's upper limb support;

[0126] When the user is in a compensated state or an uncompensated state, the system host determines the user's muscle state based on surface electromyography data.

[0127] The technical solution of the present invention is further described below through different embodiments.

[0128] Example 1: Suspended baseline assessment

[0129] In this embodiment, the task is that the overhead rail weight-reducing walking device completely suspends the user in the air, and the user relaxes his whole body with both feet off the ground.

[0130] Step 11: The system host performs the suspended baseline assessment task.

[0131] Step 12: Based on the performed suspended baseline assessment task, the system host detects and obtains the weight loss data, double plantar pressure feedback data and surface electromyography data of the sky rail user.

[0132] Skyrail User Weight Loss Data: This is the weight loss data for the user after using the Skyrail Weight Loss Walking Device. In this embodiment, since the user is suspended, the Skyrail User Weight Loss Data represents the user's weight. In this embodiment, since the user is suspended, the Skyrail User Weight Loss Data represents the user's 100% weight loss (body weight), expressed in kilograms.

[0133] Surface EMG data: This refers to baseline surface EMG data collected by a surface EMG acquisition device while the user is suspended in mid-air. Surface EMG electrodes are placed on the bellies of the following muscles using self-adhesive electrodes: rectus abdominis, transverse abdominis, erector spinae, gluteus maximus, gluteus medius, and quadriceps femoris. The surface EMG acquisition device outputs the EMG voltage detected on each channel to the system host.

[0134] Dual plantar pressure feedback data: The plantar pressure sensor detects the dual plantar pressure and immediately feeds back the dual plantar pressure data. In this embodiment, since the entire person is suspended, the plantar pressure sensor has no output and the dual plantar pressure feedback data is 0.

[0135] In this embodiment, the system host also records the weight loss data, surface electromyography data and double plantar pressure feedback data of the overhead rail user obtained by detection.

[0136] In this embodiment, the system host also outputs the weight loss data of the sky rail user, the pressure feedback data of both feet and the surface electromyography data to the electronic audio-visual feedback device.

[0137] Step 13: The system host determines the user's status based on the weight loss data of the overhead rail user, the pressure feedback data of both feet and the surface electromyography data.

[0138] Specifically:

[0139] Step 131: The system host determines the weight reduction of the overhead rail weight-reducing walking device according to the obtained user weight, and obtains the overhead rail user weight reduction data. In this embodiment, the overhead rail user weight reduction data is 100% of the user's weight.

[0140] Step 132: Calculate the actual weight bearing data of both lower limbs based on the pressure feedback data of both feet.

[0141] Specifically: the built-in pressure sensor in the pressure feedback device on the sole of the foot transmits pressure data to the system host, converts the pressure data into pressure data, and finally converts it into actual weight-bearing data of both lower limbs.

[0142] In this embodiment, since the weight loss data of the overhead rail user is 100% of the user's body weight, the pressure feedback data of both feet is 0, and the actual weight bearing data of both lower limbs is also 0.

[0143] There is no order between step 131 and step 132, and the system collects and processes the corresponding data in real time.

[0144] Step 133: Calculate the user's upper limb support compensation amount based on the user's weight, the weight loss data of the overhead rail user, and the actual weight bearing data of the lower limbs. The specific calculation formula is:

[0145] User's upper limb support compensation (%) = [(user's weight - SkyTrack user weight loss data - actual lower limb weight data) / user's weight] * 100%;

[0146] Among them, the user's weight is obtained when the entire person is suspended by the overhead rail weight-reducing walking device and input into the system host; the actual weight-bearing data of the user's lower limbs = left lower limb weight-bearing data + right lower limb weight-bearing data.

[0147] From the above settings, it can be seen that when the weight of the overhead rail is reduced to a certain extent and the user supports the walker, the compensation amount of the user's upper limb support is obtained.

[0148] In this embodiment, the calculated compensation amount of the user's upper limb support is 0.

[0149] Step 134: When the weight loss data of the SkyRail user is the user's weight and the compensation amount of the user's upper limb support is 0, the system host determines that the user is in a non-compensated state;

[0150] Step 135: When the user is in a non-compensated state, the user's muscle state is determined based on the surface electromyography data.

[0151] If the surface electromyography channel electromyography voltage value of the surface electromyography data is less than or equal to 10μv, the user relaxes the whole body;

[0152] If the surface electromyography channel electromyography voltage value of the surface electromyography data is greater than 10μv, the user is in a state of tension, muscle spasm or movement.

[0153] Example 2: Weight Loss Standing Assessment

[0154] In this embodiment, medical personnel set weight loss settings based on the user's functional level, with the weight loss range being 15%-75% of the user's body weight. The user then achieves functional standing with the assistance of a sky-high weight-reducing walking device, a walker, and a knee-ankle-foot orthosis.

[0155] Step 21: The system host executes the weight-loss standing assessment task.

[0156] Step 22: Based on the weight loss standing assessment task performed, the system host detects and obtains the weight loss data, double plantar pressure feedback data and surface electromyography data of the overhead rail user.

[0157] Skyrail User Weight Loss Data: This is the weight loss data for the user after using the Skyrail Weight Loss Walking Device. In this embodiment, since the user is in a standing position, the Skyrail Weight Loss Walking Device reduces their weight by a certain amount, such as 40%. Therefore, the Skyrail User Weight Loss Data is the user's 40% weight loss (body weight) data, in kilograms.

[0158] Surface EMG data: This refers to the surface EMG data collected by a surface EMG acquisition device while the user is standing. Surface EMG electrodes are placed on the bellies of the following muscles using self-adhesive electrodes: rectus abdominis, transverse abdominis, erector spinae, gluteus maximus, gluteus medius, and quadriceps femoris. The surface EMG acquisition device outputs the EMG voltage detected on each channel to the system host.

[0159] Dual plantar pressure feedback data: The plantar pressure sensor detects the pressure of both feet and provides real-time feedback of the dual plantar pressure data. In this embodiment, if the user does not have compensation, the sum of the pressure data output by the plantar pressure sensor should be 60% of the user's body weight.

[0160] In this embodiment, the system host also records the weight loss data of the overhead rail user, the pressure feedback data of both feet and the surface electromyography data obtained by the detection.

[0161] In this embodiment, the system host outputs the weight loss data of the sky rail user, the pressure feedback data of both feet and the surface electromyography data to the electronic audio-visual feedback device.

[0162] Step 23: The system host determines the user's status based on the weight loss data of the overhead rail user, the pressure feedback data of both feet and the surface electromyography data.

[0163] Specifically:

[0164] Step 231: The system host determines the weight reduction of the overhead rail weight-loss walking device based on the obtained user weight, and obtains the weight reduction data of the overhead rail user. According to clinical experience, the weight reduction range is 15%-75% of the user's body weight. In this embodiment, the weight reduction data of the overhead rail user is 40% of the user's body weight.

[0165] Step 232: Calculate the actual weight bearing data of both lower limbs based on the pressure feedback data of both feet.

[0166] Specifically: the built-in pressure sensor in the pressure feedback device on the sole of the foot transmits pressure data to the system host, converts the pressure data into pressure data, and finally converts it into actual weight-bearing data of both lower limbs.

[0167] Step 233: Calculate the user's upper limb support compensation amount based on the weight loss data and the actual weight-bearing data of the lower limbs of the overhead rail user. The specific calculation formula is:

[0168] User's upper limb support compensation (%) = [(user's weight - SkyTrack user weight loss data - actual lower limb weight data) / user's weight] * 100%;

[0169] Among them, the user's weight is obtained when the entire person is suspended by the overhead rail weight-reducing walking device and input into the system host; the actual weight-bearing data of the user's lower limbs = left lower limb weight-bearing data + right lower limb weight-bearing data.

[0170] From the above settings, it can be seen that when the weight of the overhead rail is reduced to a certain extent and the user supports the walker, the compensation amount of the user's upper limb support is obtained.

[0171] Based on empirical data, it is generally recommended that the amount of upper limb support compensation when users stand is <15%.

[0172] Step 234: When there is a double upper limb support compensation amount of the user (double upper limb support compensation amount>0), the system host determines that the user has compensation.

[0173] Step 235: When the user is in a compensatory state, the user's muscle state is determined based on the surface electromyography data.

[0174] If the surface EMG channel voltage values representing the gluteus maximus, gluteus medius, and quadriceps femoris in the surface EMG data are continuously greater than 15 μV, it indicates that the gluteus maximus, gluteus medius, and quadriceps femoris are actively contracting and exerting force; if the surface EMG channel voltage values representing the rectus abdominis, transverse abdominal muscles, and erector spinae in the surface EMG data continue to rise, it indicates that the trunk muscles are exerting force.

[0175] Furthermore, the surface electromyography (EMG) data collected by the surface electromyography (SEM) acquisition device under the current weight loss condition is transmitted to the system host. The SEMG data represents the activity of each muscle group "under the current weight loss conditions." If the voltage value of the SEMG channel representing the gluteus maximus, gluteus medius, and quadriceps femoris is greater than 15μv, it can be said that the above muscles are actively contracting and the user is exerting force to maintain active force. If the SEMG voltage value of the SEMG channel representing the rectus abdominis, transverse abdominal muscles, and erector spinae increases, it indicates that the trunk muscles are exerting force. It should be noted that in the standing task, the exertion of trunk muscles is not considered "compensation."

[0176] The electronic feedback device receives the double upper limb support compensation information fed back by the system host in real time. The user can adjust the force in time according to the feedback double upper limb support compensation information, giving the user real-time visual and auditory feedback, promptly clarifying the user's various "compensation" situations, guiding the user to conduct correct rehabilitation training, and ensuring the rehabilitation effect.

[0177] Example 3: Weight Loss Walking Assessment

[0178] When the user is doing "weight loss walking training", the myoelectric changes of each myoelectric channel are detected, and the pressure changes of the two soles of the feet when walking are detected.

[0179] Step 31: The system host executes the weight loss walking assessment task.

[0180] Step 32: Based on the weight loss walking assessment task performed, the system host detects and obtains the weight loss data, double plantar pressure feedback data and surface electromyography data of the overhead rail user.

[0181] Skyrail User Weight Loss Data: This is the weight loss data for the user after using the Skyrail Weight Loss Walking Device. In this embodiment, since the user is walking, the Skyrail Weight Loss Walking Device reduces their weight by a certain amount, such as 40%. Therefore, the Skyrail User Weight Loss Data is the user's 40% weight loss (body weight) data, in kilograms.

[0182] Surface EMG data: This refers to the surface EMG data collected by a surface EMG acquisition device while a user walks. Surface EMG electrodes are placed on the bellies of the following muscles using self-adhesive electrodes: rectus abdominis, transverse abdominis, erector spinae, gluteus maximus, gluteus medius, and quadriceps femoris. The surface EMG acquisition device outputs the EMG voltage detected on each channel to the system host.

[0183] Dual plantar pressure feedback data: The plantar pressure sensor detects the pressure of both feet and provides real-time feedback of the dual plantar pressure data. In this embodiment, if the user does not have compensation, the sum of the pressure data output by the plantar pressure sensor should be 60% of the user's body weight.

[0184] In this embodiment, the system host also records the weight loss data of the overhead rail user, the pressure feedback data of both feet and the surface electromyography data obtained by the detection.

[0185] In this embodiment, the system host outputs the weight loss data of the sky rail user, the pressure feedback data of both feet and the surface electromyography data to the electronic audio-visual feedback device.

[0186] Step 33: The system host determines the user's status based on the weight loss data of the overhead rail user, the pressure feedback data of both feet and the surface electromyography data.

[0187] Specifically:

[0188] Step 331: The system host determines the weight reduction of the overhead rail weight-reducing walking device based on the obtained user weight, and obtains the overhead rail user weight reduction data. In this embodiment, the overhead rail user weight reduction data is 40% of the user's body weight.

[0189] Step 332: Calculate the actual weight bearing data of both lower limbs based on the pressure feedback data of both feet.

[0190] Specifically: the built-in pressure sensor in the pressure feedback device on the sole of the foot transmits pressure data to the system host, converts the pressure data into pressure data, and finally converts it into actual weight-bearing data of both lower limbs.

[0191] Step 333: Calculate the user's upper limb support compensation amount based on the weight loss data and the actual weight-bearing data of the lower limbs of the overhead rail user. The specific calculation formula is:

[0192] User's upper limb support compensation (%) = [(user's weight - SkyTrack user weight loss data - actual lower limb weight data) / user's weight] * 100%;

[0193] Among them, the user's weight is obtained when the entire person is suspended by the overhead rail weight-reducing walking device and input into the system host; the actual weight-bearing data of the user's lower limbs = left lower limb weight-bearing data + right lower limb weight-bearing data.

[0194] From the above settings, it can be seen that when the weight of the overhead rail is reduced to a certain extent and the user supports the walker, the compensation amount of the user's upper limb support is obtained.

[0195] Based on empirical data, it is generally recommended that users maintain a maximum support compensation of <15% with both upper limbs when walking.

[0196] Step 334: When there is a double upper limb support compensation amount of the user (double upper limb support compensation amount>0), the system host determines that the user is in a compensated state.

[0197] Step 335: When the user is in a compensatory state, the user's muscle state is determined based on the surface electromyography data.

[0198] If the surface EMG channel voltage value representing the gluteus maximus, gluteus medius, and quadriceps femoris in the surface EMG data is continuously greater than 15 μV, it means that the gluteus maximus, gluteus medius, and quadriceps femoris are actively contracting and exerting force;

[0199] If the surface electromyography channel electromyography voltage values representing the rectus abdominis, transverse abdominal muscles, and erector spinae muscles in the surface electromyography data continue to rise, it indicates that the trunk muscles are exerting force.

[0200] When users with severe spinal cord injuries in the lower thoracic and lumbar regions undergo walking training, they use the contraction of the rectus abdominis and transverse abdominal muscles on the stepping side to drive the lower limbs to "swing" forward, while using the upper limbs to support the body, increase weight loss, and "compensation" occurs.

[0201] The following uses the "left lower limb bearing weight, right lower limb stepping" task as an example to illustrate the logical judgment of "compensation" during functional walking:

[0202] "Left Lower Limb Weight-Bearing": The output of the left plantar pressure sensor increases, while the output of the right decreases. According to the formula "Actual Lower Limb Weight-Bearing = Left Lower Limb Weight-Bearing + Right Lower Limb Weight-Bearing," if the left lower limb weight-bearing is greater than or equal to the user's "Weight-Reduced Standing Assessment" actual lower limb weight-bearing * 100%, and if the left "gluteus maximus, gluteus medius, and quadriceps femoris" EMG values are greater than 15μV, it can be considered that the user is not "compensating" in the current weight-reducing state. If the "Upper Limb Support Compensation Amount" is not "0," it indicates that the left limb weight-bearing is being compensated with the help of the upper limbs.

[0203] "Right Lower Limb Step": The left plantar pressure sensor maintains output, the EMG values of the left "gluteus maximus, gluteus medius, and quadriceps femoris" channels are greater than 15μV, and the EMG value of the right "quadriceps femoris" channel remains above 20μV during stepping. If the EMG values of the right "rectus abdominis, transverse abdominis, and erector spinae" are less than 15μV, it can be considered that the user is not "compensating" during the current weight-loss walking training. If the "Dual Upper Limb Support Compensation Amount" is not "0", it indicates that the left limb is bearing weight with the help of the upper limbs, and "compensating" is occurring. If the EMG value of the right "quadriceps femoris" channel cannot be maintained above 20μV during stepping, and the EMG values of the right "rectus abdominis, transverse abdominis, and erector spinae" are continuously greater than 20μV, it indicates that the right lower limb is "compensating" by the trunk muscles when stepping.

[0204] All of the above information is provided to the user visually and auditorily via the "electronic visual and auditory feedback device." If the user exhibits the aforementioned "compensatory" behavior, the "electronic visual and auditory feedback device" will provide a prompt in the form of images and sounds. The prompt content is based on the system host's comprehensive assessment of various information.

[0205] The electronic audiovisual feedback device is installed on the walker, and the user can receive the feedback by lowering their head. In addition, the walker adopts a "front roller" type walker, which ensures that the walker is "pushed" forward and ensures the stability of the electronic audiovisual feedback device.

[0206] like Figure 3 As shown, the present invention also proposes a device for determining compensation in rehabilitation training, which includes an execution unit, a detection unit, and a judgment unit.

[0207] An execution unit, used to execute pre-set tasks;

[0208] A detection unit is used to detect and obtain the weight loss data, double plantar pressure feedback data and surface electromyography data of the sky rail user according to the tasks performed;

[0209] The judgment unit is used to judge the user's status based on the weight loss data of the sky rail user, the pressure feedback data of both feet and the surface electromyography data.

[0210] In one embodiment of the present invention, the apparatus for determining compensation in rehabilitation training of the present invention further comprises: a recording unit for recording the weight loss data, surface electromyography data and double plantar pressure feedback data of the sky rail user obtained by detection;

[0211] The output unit is used to output the weight loss data of the sky rail user, the pressure feedback data of both feet and the surface electromyography data to the electronic audio-visual feedback device.

[0212] like Figure 4 As shown, the present invention also proposes a system for determining compensation in rehabilitation training, including a processor and a memory storing a computer program. When the computer program is run by the processor, it executes the aforementioned method for determining compensation in rehabilitation training.

[0213] The above describes in detail the preferred embodiments of this patent, but this patent is not limited to the above embodiments. Various changes can be made within the scope of knowledge possessed by ordinary technicians in this field without departing from the purpose of this patent.

Claims

1. A method for determining compensation in rehabilitation training, characterized in that: include: Performing pre-set tasks, wherein the pre-set tasks include: a suspended baseline assessment, a weight-reduced standing assessment, and / or a weight-reduced walking assessment; According to the tasks performed, the weight loss data of the sky rail user, the pressure feedback data of both feet, and the surface electromyography data are detected and obtained; the weight loss data of the sky rail user is the data of the user's weight loss after the user uses the sky rail weight loss walking device; the surface electromyography data is the surface electromyography data of the user collected by the surface electromyography acquisition device; the double plantar pressure feedback data is the double plantar pressure data detected by the plantar pressure sensor and immediately fed back; The user's status is determined based on the SkyRail user's weight loss data, double foot pressure feedback data, and surface electromyography data; The user's status is determined based on the weight loss data, the pressure feedback data of both feet and the surface electromyography data of the SkyTrain user as follows: Determine the weight reduction of the Skyrail weight-loss walking device according to the obtained user weight, and obtain the Skyrail user's weight reduction data; According to the pressure feedback data of both soles of the feet, the actual weight bearing data of both lower limbs are calculated; The user's upper limb support compensation amount is calculated based on the user's weight, the SkyRail user's weight loss data, and the actual weight-bearing data of both lower limbs. The user's upper limb support compensation amount (%) = [(user's weight - SkyRail user's weight loss data - actual weight-bearing data of both lower limbs) / user's weight] * 100%; where the actual weight-bearing data of both lower limbs = the weight-bearing data of the left lower limb + the weight-bearing data of the right lower limb According to the obtained compensation amount of the user's upper limb support, it is judged whether the user is in a compensated state or a non-compensated state; When the user is in a compensated state or an uncompensated state, the user's muscle state is judged based on surface electromyography data.

2. The method for determining compensation in rehabilitation training according to claim 1, characterized in that: When the preset task is a suspended baseline assessment, the user's upper limb support compensation amount is 0, and the user is determined to be in a non-compensated state.

3. The method for determining compensation in rehabilitation training according to claim 2, characterized in that: When the user is in an uncompensated state, the user's muscle state is judged based on surface electromyography data; If the surface electromyography channel electromyography voltage value of the surface electromyography data is less than or equal to 10μv, the user relaxes the whole body; If the surface electromyography channel electromyography voltage value of the surface electromyography data is greater than 10μv, the user is in a state of tension, muscle spasm or movement.

4. The method for determining compensation in rehabilitation training according to claim 1, characterized in that: When the preset task is a weight-loss standing assessment or a weight-loss walking assessment, if the user's upper limb support compensation amount is greater than 0, it is determined that the user is in a compensated state.

5. The method for determining compensation in rehabilitation training according to claim 4, characterized in that: The pre-set task is a weight-loss standing assessment or a weight-loss walking assessment. When the user is in a compensated state, the user's muscle state is judged based on surface electromyography data; If the surface EMG channel voltage value representing the gluteus maximus, gluteus medius, and quadriceps femoris in the surface EMG data is continuously greater than 15 μV, it means that the gluteus maximus, gluteus medius, and quadriceps femoris are actively contracting and exerting force; If the surface electromyography channel electromyography voltage values representing the rectus abdominis, transverse abdominal muscles, and erector spinae muscles in the surface electromyography data continue to rise, it indicates that the trunk muscles are exerting force.

6. The method for determining compensation in rehabilitation training according to claim 1, characterized in that: The method further includes: recording the weight loss data, surface electromyography data and double plantar pressure feedback data of the sky rail user obtained by the detection; The weight loss data of the sky rail user, the pressure feedback data of both feet and the surface electromyography data are output to the electronic audio-visual feedback device.

7. A device for determining compensation during rehabilitation training, characterized in that: include: an execution unit, configured to execute a preset task, wherein the preset task includes: a suspended baseline assessment, a weight-reduced standing assessment, and / or a weight-reduced walking assessment; The detection unit is configured to detect and obtain, based on the executed task, weight loss data of the overhead rail user, dual plantar pressure feedback data, and surface electromyography data; the weight loss data of the overhead rail user is data indicating the weight loss of the user after the user passes through the overhead rail weight loss walking device; the surface electromyography data is surface electromyography data of the user collected by the surface electromyography acquisition device; and the dual plantar pressure feedback data is dual plantar pressure data detected by the plantar pressure sensor and immediately fed back; A judgment unit, used to judge the user's status based on the weight loss data of the sky rail user, the pressure feedback data of both feet and the surface electromyography data; The user's status is determined based on the weight loss data, the pressure feedback data of both feet and the surface electromyography data of the SkyTrain user as follows: Determine the weight reduction of the Skyrail weight-loss walking device according to the obtained user weight, and obtain the Skyrail user's weight reduction data; According to the pressure feedback data of both soles of the feet, the actual weight bearing data of both lower limbs are calculated; The user's upper limb support compensation amount is calculated based on the user's weight, the SkyRail user's weight loss data, and the actual weight-bearing data of both lower limbs. The user's upper limb support compensation amount (%) = [(user's weight - SkyRail user's weight loss data - actual weight-bearing data of both lower limbs) / user's weight] * 100%; where the actual weight-bearing data of both lower limbs = the weight-bearing data of the left lower limb + the weight-bearing data of the right lower limb According to the obtained compensation amount of the user's upper limb support, it is judged whether the user is in a compensated state or a non-compensated state; When the user is in a compensated state or an uncompensated state, the user's muscle state is judged based on surface electromyography data.

8. The device for determining compensation during rehabilitation training according to claim 7, characterized in that: When the preset task is a suspended baseline assessment, the user's upper limb support compensation amount is 0, and the user is determined to be in a non-compensated state.

9. The device for determining compensation during rehabilitation training according to claim 8, characterized in that: When the user is in an uncompensated state, the user's muscle state is judged based on surface electromyography data; If the surface electromyography channel electromyography voltage value of the surface electromyography data is less than or equal to 10μv, the user relaxes the whole body; If the surface electromyography channel electromyography voltage value of the surface electromyography data is greater than 10μv, the user is in a state of tension, muscle spasm or movement.

10. The device for determining compensation in rehabilitation training according to claim 7, characterized in that: When the preset task is a weight-loss standing assessment or a weight-loss walking assessment, if the user's upper limb support compensation amount is greater than 0, it is determined that the user is in a compensated state.

11. The device for determining compensation in rehabilitation training according to claim 10, characterized in that: The pre-set task is a weight-loss standing assessment or a weight-loss walking assessment. When the user is in a compensated state, the user's muscle state is judged based on surface electromyography data; If the surface EMG channel voltage value representing the gluteus maximus, gluteus medius, and quadriceps femoris in the surface EMG data is continuously greater than 15 μV, it means that the gluteus maximus, gluteus medius, and quadriceps femoris are actively contracting and exerting force; If the surface electromyography channel electromyography voltage values representing the rectus abdominis, transverse abdominal muscles, and erector spinae muscles in the surface electromyography data continue to rise, it indicates that the trunk muscles are exerting force.

12. The device for determining compensation in rehabilitation training according to claim 7, characterized in that: The device further comprises: a recording unit for recording the weight loss data, surface electromyography data and double plantar pressure feedback data of the sky rail user obtained by detection; The output unit is used to output the weight loss data of the sky rail user, the pressure feedback data of both feet and the surface electromyography data to the electronic audio-visual feedback device.

13. A system for determining compensation during rehabilitation training, characterized in that: include: System host, overhead weight-reducing walking device, plantar pressure sensor, and surface electromyography acquisition device; The system host executes pre-set tasks, which include: hanging baseline assessment, weight-reduced standing assessment and / or weight-reduced walking assessment; The system host detects and obtains weight loss data, dual plantar pressure feedback data, and surface electromyography data of the overhead rail user according to the executed task; the weight loss data of the overhead rail user is data of the user's weight loss after the user uses the overhead rail weight loss walking device; the surface electromyography data is the surface electromyography data of the user collected by the surface electromyography acquisition device; the dual plantar pressure feedback data is the dual plantar pressure data detected by the plantar pressure sensor and immediately fed back; The system host determines the user's status based on the user's weight loss data, double foot pressure feedback data and surface electromyography data; The user's status is determined based on the weight loss data, the pressure feedback data of both feet and the surface electromyography data of the SkyTrain user as follows: Determine the weight reduction of the Skyrail weight-loss walking device according to the obtained user weight, and obtain the Skyrail user's weight reduction data; According to the pressure feedback data of both soles of the feet, the actual weight bearing data of both lower limbs are calculated; The user's upper limb support compensation amount is calculated based on the user's weight, the SkyRail user's weight loss data, and the actual weight-bearing data of both lower limbs. The user's upper limb support compensation amount (%) = [(user's weight - SkyRail user's weight loss data - actual weight-bearing data of both lower limbs) / user's weight] * 100%; where the actual weight-bearing data of both lower limbs = the weight-bearing data of the left lower limb + the weight-bearing data of the right lower limb According to the obtained compensation amount of the user's upper limb support, it is judged whether the user is in a compensated state or a non-compensated state; When the user is in a compensated state or an uncompensated state, the user's muscle state is judged based on surface electromyography data.

14. The system for determining compensation during rehabilitation training according to claim 13, characterized in that: When the preset task is a suspended baseline assessment, the user's upper limb support compensation amount is 0, and the user is determined to be in a non-compensated state.

15. The system for determining compensation during rehabilitation training according to claim 14, characterized in that: When the user is in an uncompensated state, the user's muscle state is judged based on surface electromyography data; If the surface electromyography channel electromyography voltage value of the surface electromyography data is less than or equal to 10μv, the user relaxes the whole body; If the surface electromyography channel electromyography voltage value of the surface electromyography data is greater than 10μv, the user is in a state of tension, muscle spasm or movement.

16. The system for determining compensation during rehabilitation training according to claim 13, characterized in that: When the preset task is a weight-loss standing assessment or a weight-loss walking assessment, if the user's upper limb support compensation amount is greater than 0, it is determined that the user is in a compensated state.

17. The system for determining compensation during rehabilitation training according to claim 16, characterized in that: The pre-set task is a weight-loss standing assessment or a weight-loss walking assessment. When the user is in a compensated state, the user's muscle state is judged based on surface electromyography data; If the surface EMG channel voltage value representing the gluteus maximus, gluteus medius, and quadriceps femoris in the surface EMG data is continuously greater than 15 μV, it means that the gluteus maximus, gluteus medius, and quadriceps femoris are actively contracting and exerting force; If the surface electromyography channel electromyography voltage values representing the rectus abdominis, transverse abdominal muscles, and erector spinae muscles in the surface electromyography data continue to rise, it indicates that the trunk muscles are exerting force.

18. The system for determining compensation during rehabilitation training according to claim 13, characterized in that: The system host also records the weight loss data, surface electromyography data and double plantar pressure feedback data of the sky rail user obtained by the detection; The system host outputs the weight loss data of the sky rail user, the pressure feedback data of both feet and the surface electromyography data to the electronic audio-visual feedback device.

19. A system for determining compensation during rehabilitation training, characterized in that: The system includes a processor and a memory storing a computer program, and when the computer program is executed by the processor, the method according to any one of claims 1 to 6 is executed.

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