Functional electrical stimulation adjuvant therapy system with multiple motion modes and method thereof

Abstract

The invention discloses a functional electrical stimulation adjuvant therapy system with multiple motion modes and a method thereof, and belongs to the technical field of rehabilitation adjuvant therapy systems.The functional electrical stimulation adjuvant therapy system comprises a motion state configuration unit, a multi-channel FES control system, a muscle fatigue detection device, a muscle spasm detection device, a muscle strength detection device and a patient management platform; the system comprises an illness state diagnosis and quantitative evaluation unit, a master control module, an illness state diagnosis report and a human-computer interaction platform. According to the invention, the condition of a patient can be diagnosed and quantitatively evaluated while adjuvant therapy of the patient is realized; according to the illness state diagnosis and quantitative evaluation result of the patient, adaptively adjusting each channel mode in a passive training mode of the patient; under the active training mode of the patient, adaptively adjusting each channel mode and the mode of a servo motor; the human-computer interaction degree is enhanced, the visual enjoyment of the patient is improved, and the training passion of the patient is aroused.

Description

Technical Field

[0001] The present invention relates to the technical field of rehabilitation auxiliary therapy systems, and in particular to a multi-motion mode functional electrical stimulation auxiliary therapy system and a method thereof. Background Art

[0002] Functional electrical stimulation (FES) uses low-frequency electrical stimulation to activate muscle groups that have lost control of the nerves, thereby improving or restoring muscle or muscle group function and helping patients improve their mobility.

[0003] Invention patent CN113908439B discloses a functional electrical stimulation system for rehabilitation therapy equipment, which can exercise the patient's legs, arms and fingers.

[0004] However, the above system has the following problems:

[0005] 1) It is difficult to diagnose and quantitatively evaluate the patient's condition while receiving adjuvant treatment;

[0006] 2) It is impossible to adaptively adjust the parameters of electrical stimulation in the patient's passive training mode according to the patient's condition diagnosis and quantitative evaluation results;

[0007] 3) It is also impossible to adaptively adjust the parameters of electrical stimulation in the patient's active training mode;

[0008] 4) In addition, the existing functional electrical stimulation systems have problems such as less human-computer interaction and difficulty for patients to persist in active training.

[0009] Based on this, the present invention designs a multi-motion mode functional electrical stimulation assisted treatment system and method to solve the above problems. Summary of the invention

[0010] In view of the above-mentioned shortcomings of the prior art, the present invention provides a functional electrical stimulation assisted treatment system and method with multiple motion modes.

[0011] To achieve the above objectives, the present invention is implemented through the following technical solutions:

[0012] A multi-motion mode functional electrical stimulation assisted therapy system, comprising:

[0013] The motion state configuration unit is used to select and configure the patient's body motion type, training method and training time h for this training; wherein the training method includes active training and passive training;

[0014] Multi-channel FES control system, used to configure the parameters of the electrodes of each channel and the channel mode respectively. The channel modes include standard mode, enhanced mode, consolidation mode and weakened mode.

[0015] A muscle fatigue detection device is used to perform fatigue detection on multiple muscles of the patient during training. When muscle fatigue is detected, the information is transmitted to the main control module to record the current training time L;

[0016] The muscle spasm detection device is used to detect spasms of multiple muscles of the patient during training. When muscle spasm is detected, the information is transmitted to the main control module, and the total number of spasms n within the training time h is counted;

[0017] A muscle strength detection device is used to detect the muscle strength of multiple parts of the patient and output the muscle strength level m;

[0018] Patient management platform, including patient login unit, patient information storage unit, condition diagnosis and quantitative evaluation unit and training dynamic adjustment unit;

[0019] The disease diagnosis and quantitative evaluation unit receives the current training time L when the muscle is fatigued, the total number of cramps n within the training time h, and the muscle strength level m;

[0020] When L>0.5h, assign L=1, when L≤0.5h, assign L=0;

[0021] exist (take integer), assign n = 1, When n=2, When , assign n = 3;

[0022] The muscle strength level is divided into 0-5 levels, and the values ​​are assigned m = 1-5 respectively;

[0023] Calculate the patient's condition coefficient Y:

[0024] Y=L+n+m

[0025] According to the patient's condition coefficient Y, the training dynamic adjustment unit controls the multi-channel FES control system to adjust the channel mode of the next training;

[0026] The main control module controls the multi-channel FES control system and the servo motor to stop when receiving muscle fatigue or muscle spasm; and is used to adjust the mode of the servo motor corresponding to the upper limb / lower limb during the next active training according to the total Y value of the upper limb / lower limb;

[0027] The disease diagnosis report is used to record the channel mode of the next passive training and the mode of the servo motor during the next active training;

[0028] And human-computer interaction platform.

[0029] Furthermore, during the initial training, each channel mode adopts the standard mode, and the electrode sheet parameters in the standard mode are configured as follows: current 50mA, pulse width 100μs, frequency 20Hz.

[0030] Furthermore, the patient login unit is used for patient login accounts; the patient information storage unit is used for storing the patient's personal information and historical motion state configuration, historical multi-channel FES control system parameter configuration and channel mode configuration information, and historical disease diagnosis reports.

[0031] Furthermore, if 8<Y≤9, the training dynamic adjustment unit controls the multi-channel FES control system to adjust the channel mode configuration of the next training to the enhanced mode; the electrode sheet parameters in the enhanced mode are configured to be 1.2 times of the previous training mode;

[0032] If 5<Y≤8, the training dynamic adjustment unit controls the multi-channel FES control system to adjust the channel mode configuration of the next training to the consolidation mode; the electrode sheet parameters in the consolidation mode are configured to be 1.05 times of the previous training mode;

[0033] If Y≤5, the training dynamic adjustment unit controls the multi-channel FES control system to adjust the channel mode configuration of the next training to the weakening mode; the electrode sheet parameters in the weakening mode are configured to 0.8 times of the previous training mode.

[0034] Furthermore, the upper limit thresholds of the current, pulse width, and frequency parameters are set, with the maximum current being 140mA, the maximum pulse width being 2500μs, and the maximum frequency being 100Hz.

[0035] Furthermore, the main control module adjusts the mode of the servo motor corresponding to the upper limbs / lower limbs during the next active training according to the total Y value of the upper limbs / lower limbs:

[0036] If 96<total Y value of upper limb / lower limb≤108, the main control module controls the servo motor to adjust the next mode configuration to the enhanced mode; the speed and torque parameters in the enhanced mode are configured to be 1.2 times of the previous mode;

[0037] If 60<total Y value of upper limb / lower limb≤96, the main control module controls the servo motor to adjust the next mode configuration to the consolidation mode; the speed and torque parameters in the consolidation mode are configured to be 1.05 times of the previous mode;

[0038] If the total Y value of the upper limb / lower limb is ≤60, the main control module controls the servo motor to adjust the next mode configuration to the weakening mode; the speed and torque parameters in the weakening mode are configured to 0.8 times of the previous mode.

[0039] Furthermore, the disease diagnosis report also records: the type of body movement of this training, the training method, the training time h, the current training time L when the muscles are fatigued, the total number of spasms n within the training time h, the muscle strength level m, the Y value of each channel, the total Y value of the upper limbs, and the total Y value of the lower limbs.

[0040] Furthermore, the types of body movements include upper limb circular movements alone, lower limb circular movements alone, and upper and lower limb circular movements.

[0041] Furthermore, the total Y value of the upper limb refers to the sum of the Y values ​​of the channel electrode sheets attached to the upper limb, and the total Y value of the lower limb refers to the sum of the Y values ​​of the channel electrode sheets attached to the lower limb.

[0042] In order to better achieve the purpose of the present invention, the present invention also provides a multi-exercise mode functional electrical stimulation assisted treatment method, using the multi-exercise mode functional electrical stimulation assisted treatment system, comprising the following steps:

[0043] Step 1: The patient logs in to the account through the patient login unit, and selects and configures the patient's body exercise type, training method and training time h for this training;

[0044] Step 2: If the user chooses active training, after the selection, the multi-channel FES control system automatically configures the electrode parameters and channel mode of the patient's current training according to the last diagnosis report;

[0045] The patient actively trains, and the muscle fatigue detection device detects the fatigue of the patient's muscles. When muscle fatigue is detected, the main control module controls the multi-channel FES control system to shut down and records the current training time L; the muscle spasm detection device detects spasms of multiple muscles of the patient respectively. When muscle spasms are detected, the main control module controls the multi-channel FES control system to shut down, and after the muscle spasms are relieved, the training continues until the training reaches time h, and the total number of spasms n within the training time h is counted; the muscle strength detection device detects the strength of multiple muscles of the patient respectively, and outputs the muscle strength level m;

[0046] The disease diagnosis and quantitative evaluation unit receives the current training time L when the muscle is fatigued, the total number of spasms n within the training time h, and the muscle strength level m; when L>0.5h, the value L=1 is assigned, and when L≤0.5h, the value L=0 is assigned; When n=1, When n=2, When , the value n = 3; the muscle strength level is divided into 0-5 levels, and the values ​​m = 1-5 are assigned respectively;

[0047] Calculate the patient's condition coefficient Y:

[0048] Y=L+n+m

[0049] If 8<Y≤9, the training dynamic adjustment unit controls the multi-channel FES control system to adjust the channel mode configuration of the next training to the enhanced mode; the electrode sheet parameter configuration in the enhanced mode is 1.2 times that of the current training mode;

[0050] If 5<Y≤8, the training dynamic adjustment unit controls the multi-channel FES control system to adjust the channel mode configuration of the next training to the consolidation mode; the electrode sheet parameter configuration in the consolidation mode is 1.05 times that of the current training mode;

[0051] If Y≤5, the training dynamic adjustment unit controls the multi-channel FES control system to adjust the channel mode configuration of the next training to the weakening mode; the electrode sheet parameters in the weakening mode are configured to be 0.8 times of the current training mode;

[0052] Step 3: If the user selects passive training, after the selection, the multi-channel FES control system automatically configures the electrode parameters and channel mode of the patient's current training according to the last diagnosis report; and the main control module automatically configures the mode of controlling the servo motor according to the last diagnosis report;

[0053] The patient is passively trained. The muscle fatigue detection device detects the fatigue of the patient's muscles. When muscle fatigue is detected, the main control module controls the multi-channel FES control system and the servo motor to stop, and records the current training time L; the muscle spasm detection device detects spasms of multiple muscles of the patient. When muscle spasms are detected, the main control module controls the multi-channel FES control system and the servo motor to stop. After the muscle spasm is relieved, the training continues until the training reaches the time h, and the total number of spasms n within the training time h is counted; the muscle strength detection device detects the strength of multiple muscles of the patient and outputs the muscle strength level m;

[0054] The disease diagnosis and quantitative evaluation unit receives the current training time L when the muscle is fatigued, the total number of spasms n within the training time h, and the muscle strength level m; when L>0.5h, the value L=1 is assigned, and when L≤0.5h, the value L=0 is assigned; (take integer), assign n = 1, When n=2, When , the value is n = 3; the muscle strength level is divided into 0-5 levels and the values ​​are m = 1-5 respectively;

[0055] Calculate the patient's condition coefficient Y:

[0056] Y=L+n+m

[0057] If 8<Y≤9, the training dynamic adjustment unit controls the multi-channel FES control system to adjust the channel mode configuration of the next training to the enhanced mode; the electrode sheet parameter configuration in the enhanced mode is 1.2 times that of the current training mode;

[0058] If 5<Y≤8, the training dynamic adjustment unit controls the multi-channel FES control system to adjust the channel mode configuration of the next training to the consolidation mode; the electrode sheet parameter configuration in the consolidation mode is 1.05 times that of the current training mode;

[0059] If Y≤5, the training dynamic adjustment unit controls the multi-channel FES control system to adjust the channel mode configuration of the next training to the weakening mode; the electrode sheet parameters in the weakening mode are configured to be 0.8 times of the current training mode;

[0060] The main control module adjusts the mode of the servo motor corresponding to the upper limbs / lower limbs during the next active training according to the total Y value of the upper limbs / lower limbs:

[0061] If 96<total Y value of upper limb / lower limb≤108, the main control module controls the servo motor to adjust the next mode configuration to the enhanced mode; the speed and torque parameters in the enhanced mode are configured to be 1.2 times of the current mode;

[0062] If 60<total Y value of upper limb / lower limb≤96, the main control module controls the servo motor to adjust the next mode configuration to the consolidation mode; the speed and torque parameters in the consolidation mode are configured to be 1.05 times of the current mode;

[0063] If the total Y value of the upper limb / lower limb is ≤60, the main control module controls the servo motor to adjust the next mode configuration to the weakening mode; the speed and torque parameters in the weakening mode are configured to be 0.8 times of this mode;

[0064] Step 4. Output the disease diagnosis report, which records the type of body movement, training method, training time h, current training time L when muscle fatigue occurs, total number of spasms n within the training time h, muscle strength level m, Y value of each channel, total Y value of upper limbs, total Y value of lower limbs, as well as the channel mode of the next passive training and the mode of the servo motor during the next active training.

[0065] Compared with the prior art, the present invention has the following beneficial effects: the present invention can diagnose and quantitatively evaluate the patient's condition while assisting the patient's treatment; and according to the diagnosis and quantitative evaluation results of the patient's condition, in the patient's passive training mode, the various channel modes are adaptively adjusted; in the patient's active training mode, the various channel modes and the servo motor modes are adaptively adjusted; the degree of human-computer interaction is enhanced, the patient's visual enjoyment is improved, and the patient's training passion is mobilized. The present invention can realize adaptive parameter configuration adjustment for each patient's condition, preferably configure 6-24 channels, and can perform separate parameter configuration for each channel, so that each patient has a corresponding treatment plan. BRIEF DESCRIPTION OF THE DRAWINGS

[0066] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the prior art descriptions are briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention, and for ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0067] Figure 1 It is a schematic diagram of the structure of a multi-motion mode functional electrical stimulation assisted therapy system of the present invention. DETAILED DESCRIPTION

[0068] In order to make the purpose, technical solution and advantages of the embodiments of the present invention clearer, the technical solution in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are 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 creative work are within the scope of protection of the present invention.

[0069] The terms “left”, “right”, “front”, “back”, “up” and “down” mentioned in the following description are oriented in the viewing direction of the front view.

[0070] Embodiment 1: In some embodiments, please refer to the drawings of the specification Figure 1 , a multi-motion mode functional electrical stimulation assisted therapy system, comprising:

[0071] The exercise state configuration unit is used to select and configure the patient's body exercise type, training method and training time h for this training; the training time h is generally controlled within 10-30 minutes and should not be too long. In the early stage, it can start with 10 minutes;

[0072] Among them, the types of body movements include single upper limb circular movement, single lower limb circular movement (sitting), single lower limb circular movement (lying), and upper and lower limb circular movement; single upper limb circular movement is suitable for patients with upper limb monoplegia, single lower limb circular movement (sitting) and single lower limb circular movement (lying) are suitable for patients with paraplegia, and upper and lower limb circular movement is suitable for patients with hemiplegia;

[0073] Among them, the training methods include active training and passive training. In passive training, the corresponding servo motor is driven to start according to the type of body movement;

[0074] The multi-channel FES control system is used to configure the parameters of the electrodes of each channel and the channel mode. The channel modes include standard mode, enhanced mode, consolidation mode and weakened mode. During the initial training, each channel mode adopts the standard mode, and the electrode parameters in the standard mode are configured as follows: current 50mA, pulse width 100μs, frequency 20Hz;

[0075] The muscle fatigue detection device is used to perform fatigue detection on multiple muscles of the patient during training. When muscle fatigue is detected, the information is transmitted to the main control module to record the current training time L (L≤h);

[0076] The muscle spasm detection device is used to detect spasms of multiple muscles of the patient during training. When muscle spasm is detected, the information is transmitted to the main control module, and the total number of spasms n within the training time h is counted;

[0077] A muscle strength detection device is used to detect the muscle strength of multiple parts of the patient and output the muscle strength level m;

[0078] Patient management platform, including patient login unit, patient information storage unit, condition diagnosis and quantitative evaluation unit and training dynamic adjustment unit;

[0079] Patient login unit, used for patients to log into their accounts;

[0080] A patient information storage unit, used to store the patient's personal information and historical motion state configuration, historical multi-channel FES control system parameter configuration and channel mode configuration information, and historical disease diagnosis reports;

[0081] The disease diagnosis and quantitative evaluation unit receives the current training time L when the muscle is fatigued, the total number of cramps n within the training time h, and the muscle strength level m;

[0082] When L>0.5h, assign L=1, when L≤0.5h, assign L=0;

[0083] exist (take integer), assign n = 1, When n=2, When , assign n = 3;

[0084] The muscle strength level is divided into 0-5 levels (muscle strength measurement standards); at level 0, the value is assigned to m = 0, at level 1, the value is assigned to m = 1, at level 2, the value is assigned to m = 2, at level 3, the value is assigned to m = 3, at level 4, the value is assigned to m = 4, and at level 5, the value is assigned to m = 5;

[0085] Calculate the patient's condition coefficient Y:

[0086] Y=L+n+m

[0087] If 8<Y≤9, it means that the patient has adapted well, and the training dynamic adjustment unit controls the multi-channel FES control system to adjust the channel mode configuration of the next training to the enhanced mode; the electrode sheet parameters in the enhanced mode are configured to be 1.2 times of the previous training mode (e.g., standard mode): current 60mA, pulse width 120μs, frequency 24Hz;

[0088] If 5<Y≤8, it means that the patient adapts normally, and the training dynamic adjustment unit controls the multi-channel FES control system to adjust the channel mode configuration of the next training to the consolidation mode; the electrode sheet parameters in the consolidation mode are configured to be 1.05 times of the last training mode (e.g., standard mode): current 52.5mA, pulse width 105μs, frequency 21Hz;

[0089] If Y≤5, it means that the patient's adaptation is poor, and the training dynamic adjustment unit controls the multi-channel FES control system to adjust the channel mode configuration of the next training to the weakened mode; the electrode sheet parameters in the weakened mode are configured to be 0.8 times of the last training mode (such as the standard mode): current 40mA, pulse width 80μs, frequency 16Hz;

[0090] Set the upper limit thresholds of current, pulse width, and frequency parameters. The maximum current is 140mA, the maximum pulse width is 2500μs, and the maximum frequency is 100Hz. If the upper limit is reached, the threshold is used as the parameter configuration;

[0091] When the main control module receives muscle fatigue or muscle spasm, it controls the multi-channel FES control system and the servo motor to stop, and no longer conducts electrical stimulation and passive training; after the muscle spasm is relieved, the training continues until the training reaches time h; when the training mode is active training, the servo motor is controlled to start. During the initial training, the servo motor adopts the standard mode, the speed is set to v0, and the torque is set to T0; at the same time, according to the total Y value of the upper limbs / lower limbs (12 channels for each upper limb and lower limb, a total of 24 channels), the mode of the servo motor corresponding to the upper limb / lower limb during the next active training is adjusted:

[0092] If 96<total Y value of upper limb / lower limb≤108, it means that the patient adapts well, and the main control module controls the servo motor to adjust the next mode configuration to the enhanced mode; the speed and torque parameters in the enhanced mode are configured to be 1.2 times of the previous mode (such as the standard mode): v=1.2×v0, T=1.2×T0; the total Y value of the upper limb refers to the sum of the Y values ​​of the 12-channel electrode sheets attached to the upper limbs, and the total Y value of the lower limb refers to the sum of the Y values ​​of the 12-channel electrode sheets attached to the lower limbs;

[0093] If 60<total Y value of upper limb / lower limb≤96, it means that the patient adapts normally, and the main control module controls the servo motor to adjust the next mode configuration to the consolidation mode; the speed and torque parameters in the consolidation mode are configured to be 1.05 times of the previous mode (such as the standard mode): v=1.05×v0, T=1.05×T0;

[0094] If the total Y value of the upper limb / lower limb is ≤60, it means that the patient's adaptation is poor, and the main control module controls the servo motor to adjust the next mode configuration to the weakening mode; the speed and torque parameters in the weakening mode are configured to be 0.8 times of the previous mode (such as the standard mode): v = 0.8 × v0, T = 0.8 × T0;

[0095] Set the upper limit threshold of the speed and torque parameters. If the upper limit is reached, the threshold is used as the parameter configuration;

[0096] The disease diagnosis report is used to record the type of body movement, training method, training time h, current training time L when muscle fatigue occurs, total number of spasms n within the training time h, muscle strength level m, Y value of each channel, total Y value of upper limbs, total Y value of lower limbs, and the mode of each channel for the next passive training and the mode of the servo motor for the next active training;

[0097] The human-computer interaction platform is used to display the cycling images of patients during training, such as showing a bicycle riding on a beautiful sunny avenue. The bicycle's speed is set proportional to the patient's active / passive training speed, which is conducive to improving the degree of human-computer interaction, enhancing the patient's visual enjoyment, and mobilizing the patient's training passion;

[0098] The present invention can diagnose and quantitatively evaluate the patient's condition while providing auxiliary treatment to the patient; and according to the diagnosis and quantitative evaluation results of the patient's condition, in the patient's passive training mode, adaptively adjust each channel mode; in the patient's active training mode, adaptively adjust each channel mode and the mode of the servo motor; enhance the degree of human-computer interaction, improve the patient's visual enjoyment, and mobilize the patient's training passion.

[0099] Embodiment 2: In some embodiments, Figure 1 As shown, as a preferred embodiment of the present invention, a multi-exercise mode functional electrical stimulation assisted treatment method comprises the following steps:

[0100] Step 1: The patient logs in to the account through the patient login unit, and selects and configures the patient's body movement type, training method and training time h for this training;

[0101] Among them, the types of body movements include single upper limb circular movement, single lower limb circular movement (sitting), single lower limb circular movement (lying), and upper and lower limb circular movement; single upper limb circular movement is suitable for patients with upper limb monoplegia, single lower limb circular movement (sitting) and single lower limb circular movement (lying) are suitable for patients with paraplegia, and upper and lower limb circular movement is suitable for patients with hemiplegia;

[0102] Among them, the training methods include active training and passive training. In passive training, the corresponding servo motor is driven to start according to the type of body movement;

[0103] Step 2: If the user chooses active training, after the selection, the multi-channel FES control system automatically configures the electrode parameters and channel mode of the patient's current training according to the last diagnosis report;

[0104] The patient actively trains, and the muscle fatigue detection device detects the fatigue of the patient's muscles. When muscle fatigue is detected, the main control module controls the multi-channel FES control system to shut down and records the current training time L (L≤h); the muscle spasm detection device detects spasms of multiple muscles of the patient respectively. When muscle spasms are detected, the main control module controls the multi-channel FES control system to shut down, and after the muscle spasms are relieved, the training continues until the training reaches time h, and the total number of spasms n within the training time h is counted; the muscle strength detection device detects the strength of multiple muscles of the patient respectively, and outputs the muscle strength level m;

[0105] The disease diagnosis and quantitative evaluation unit receives the current training time L when the muscle is fatigued, the total number of spasms n within the training time h, and the muscle strength level m; when L>0.5h, the value L=1 is assigned, and when L≤0.5h, the value L=0 is assigned; (take integer), assign n = 1, When n=2, When n=3, the value is assigned; the muscle strength level is divided into 0-5 levels (muscle strength measurement standard); when it is level 0, the value is assigned m=0, when it is level 1, the value is assigned m=1, when it is level 2, the value is assigned m=2, when it is level 3, the value is assigned m=3, when it is level 4, the value is assigned m=4, when it is level 5, the value is assigned m=5;

[0106] Calculate the patient's condition coefficient Y:

[0107] Y=L+n+m

[0108] If 8<Y≤9, it means that the patient has adapted well, and the training dynamic adjustment unit controls the multi-channel FES control system to adjust the channel mode configuration of the next training to the enhanced mode; the electrode sheet parameters in the enhanced mode are configured to be 1.2 times that of the current training mode;

[0109] If 5<Y≤8, it means that the patient's adaptation is normal, and the training dynamic adjustment unit controls the multi-channel FES control system to adjust the channel mode configuration of the next training to the consolidation mode; the electrode sheet parameter configuration in the consolidation mode is 1.05 times that of the current training mode;

[0110] If Y≤5, it means that the patient's adaptation is poor, and the training dynamic adjustment unit controls the multi-channel FES control system to adjust the channel mode configuration of the next training to the weakening mode; the electrode sheet parameters in the weakening mode are configured to be 0.8 times of the current training mode;

[0111] Set the upper limit thresholds of current, pulse width, and frequency parameters. The maximum current is 140mA, the maximum pulse width is 2500μs, and the maximum frequency is 100Hz. If the upper limit is reached, the threshold is used as the parameter configuration.

[0112] Step 3: If the user selects passive training, after the selection, the multi-channel FES control system automatically configures the electrode parameters and channel mode of the patient's current training according to the last diagnosis report; and the main control module automatically configures the mode of controlling the servo motor according to the last diagnosis report;

[0113] The patient is passively trained. The muscle fatigue detection device detects the fatigue of the patient's muscles. When muscle fatigue is detected, the main control module controls the multi-channel FES control system and the servo motor to stop, and records the current training time L (L≤h); the muscle spasm detection device detects spasms of multiple muscles of the patient. When muscle spasms are detected, the main control module controls the multi-channel FES control system and the servo motor to stop. After the muscle spasm is relieved, the training continues until the training reaches the time h, and the total number of spasms n within the training time h is counted; the muscle strength detection device detects the strength of multiple muscles of the patient and outputs the muscle strength level m;

[0114] The disease diagnosis and quantitative evaluation unit receives the current training time L when the muscle is fatigued, the total number of spasms n within the training time h, and the muscle strength level m; when L>0.5h, the value L=1 is assigned, and when L≤0.5h, the value L=0 is assigned; (take integer), assign n = 1, When n=2, When n=3, the value is assigned; the muscle strength level is divided into 0-5 levels (muscle strength measurement standard); when it is level 0, the value is assigned m=0, when it is level 1, the value is assigned m=1, when it is level 2, the value is assigned m=2, when it is level 3, the value is assigned m=3, when it is level 4, the value is assigned m=4, when it is level 5, the value is assigned m=5;

[0115] Calculate the patient's condition coefficient Y:

[0116] Y=L+n+m

[0117] If 8<Y≤9, it means that the patient has adapted well, and the training dynamic adjustment unit controls the multi-channel FES control system to adjust the channel mode configuration of the next training to the enhanced mode; the electrode sheet parameters in the enhanced mode are configured to be 1.2 times that of the current training mode;

[0118] If 5<Y≤8, it means that the patient's adaptation is normal, and the training dynamic adjustment unit controls the multi-channel FES control system to adjust the channel mode configuration of the next training to the consolidation mode; the electrode sheet parameter configuration in the consolidation mode is 1.05 times that of the current training mode;

[0119] If Y≤5, it means that the patient's adaptation is poor, and the training dynamic adjustment unit controls the multi-channel FES control system to adjust the channel mode configuration of the next training to the weakening mode; the electrode sheet parameters in the weakening mode are configured to be 0.8 times of the current training mode;

[0120] Set the upper limit thresholds of current, pulse width, and frequency parameters. The maximum current is 140mA, the maximum pulse width is 2500μs, and the maximum frequency is 100Hz. If the upper limit is reached, the threshold is used as the parameter configuration.

[0121] The main control module adjusts the mode of the servo motor corresponding to the upper limbs / lower limbs during the next active training according to the total Y value of the upper limbs / lower limbs (12 channels for each upper limb and lower limb, a total of 24 channels):

[0122] If 96<total Y value of upper limb / lower limb≤108, it means that the patient adapts well, and the main control module controls the servo motor to adjust the next mode configuration to the enhanced mode; the speed and torque parameters in the enhanced mode are configured to be 1.2 times of this mode; the total Y value of the upper limb refers to the sum of the Y values ​​of the 12-channel electrode sheets attached to the upper limbs, and the total Y value of the lower limb refers to the sum of the Y values ​​of the 12-channel electrode sheets attached to the lower limbs;

[0123] If 60<total Y value of upper limb / lower limb≤96, it means that the patient adapts normally, and the main control module controls the servo motor to adjust the next mode configuration to the consolidation mode; the speed and torque parameters in the consolidation mode are configured to be 1.05 times of this mode;

[0124] If the total Y value of the upper limbs / lower limbs is ≤60, it means that the patient's adaptation is poor, and the main control module controls the servo motor to adjust the next mode configuration to the weakening mode; the speed and torque parameters in the weakening mode are configured to be 0.8 times of this mode;

[0125] Set the upper limit threshold of the speed and torque parameters. When the upper limit is reached, the threshold is used as the parameter configuration.

[0126] Step 4. Output the disease diagnosis report, which records the type of body movement, training method, training time h, current training time L when muscle fatigue occurs, total number of spasms n within the training time h, muscle strength level m, Y value of each channel, total Y value of upper limbs, total Y value of lower limbs, as well as the channel mode of the next passive training and the mode of the servo motor during the next active training.

[0127] The present invention can realize adaptive parameter configuration adjustment according to the condition of each patient, preferably configure 6-24 channels, and perform independent parameter configuration for each channel to realize corresponding treatment plan for each patient.

[0128] The above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit the same. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that the technical solutions described in the aforementioned embodiments may still be modified, or some of the technical features may be replaced by equivalents. Such modifications or replacements will not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A multi-exercise mode functional electrical stimulation assisted therapy system, characterized in that: include: The motion state configuration unit is used to select and configure the patient's body motion type, training method and training time h for this training; wherein the training method includes active training and passive training; Multi-channel FES control system, used to configure the parameters of the electrodes of each channel and the channel mode respectively. The channel modes include standard mode, enhanced mode, consolidation mode and weakened mode. A muscle fatigue detection device is used to perform fatigue detection on multiple muscles of the patient during training. When muscle fatigue is detected, the information is transmitted to the main control module to record the current training time L; The muscle spasm detection device is used to detect spasms of multiple muscles of the patient during training. When muscle spasm is detected, the information is transmitted to the main control module, and the total number of spasms n within the training time h is counted; A muscle strength detection device is used to detect the muscle strength of multiple parts of the patient and output the muscle strength level m; Patient management platform, including patient login unit, patient information storage unit, condition diagnosis and quantitative evaluation unit and training dynamic adjustment unit; The disease diagnosis and quantitative evaluation unit receives the current training time L when the muscle is fatigued, the total number of cramps n within the training time h, and the muscle strength level m; When L>0.5h, assign L=1, when L≤0.5h, assign L=0; exist (take integer), assign n = 1, When n=2, When , assign n = 3; The muscle strength level is divided into 0-5 levels, and the values ​​are assigned m = 1-5 respectively; Calculate the patient's condition coefficient Y: Y=L+n+m According to the patient's condition coefficient Y, the training dynamic adjustment unit controls the multi-channel FES control system to adjust the channel mode of the next training; The main control module controls the multi-channel FES control system and the servo motor to stop when receiving muscle fatigue or muscle spasm; and is used to adjust the mode of the servo motor corresponding to the upper limb / lower limb during the next active training according to the total Y value of the upper limb / lower limb; The disease diagnosis report is used to record the channel mode of the next passive training and the mode of the servo motor during the next active training; And human-computer interaction platform.

2. The multi-motion mode functional electrical stimulation assisted therapy system according to claim 1, characterized in that: During the initial training, each channel mode adopts the standard mode, and the electrode sheet parameters in the standard mode are configured as follows: current 50mA, pulse width 100μs, frequency 20Hz.

3. The multi-motion mode functional electrical stimulation assisted therapy system according to claim 2, characterized in that: The patient login unit is used for patients to log into their accounts; the patient information storage unit is used to store the patient's personal information and historical motion state configuration, historical multi-channel FES control system parameter configuration and channel mode configuration information, and historical disease diagnosis reports.

4. The multi-motion mode functional electrical stimulation assisted therapy system according to claim 3, characterized in that: If 8<Y≤9, the training dynamic adjustment unit controls the multi-channel FES control system to adjust the channel mode configuration of the next training to the enhanced mode; the electrode sheet parameters in the enhanced mode are configured to be 1.2 times of the previous training mode; If 5<Y≤8, the training dynamic adjustment unit controls the multi-channel FES control system to adjust the channel mode configuration of the next training to the consolidation mode; the electrode sheet parameters in the consolidation mode are configured to be 1.05 times of the previous training mode; If Y≤5, the training dynamic adjustment unit controls the multi-channel FES control system to adjust the channel mode configuration of the next training to the weakening mode; the electrode sheet parameters in the weakening mode are configured to 0.8 times of the previous training mode.

5. The multi-motion mode functional electrical stimulation assisted therapy system according to claim 4, characterized in that: Set the upper limit thresholds of current, pulse width, and frequency parameters. The maximum current is 140mA, the maximum pulse width is 2500μs, and the maximum frequency is 100Hz.

6. The multi-motion mode functional electrical stimulation assisted therapy system according to claim 5, characterized in that: The main control module adjusts the mode of the servo motor corresponding to the upper limbs / lower limbs during the next active training according to the total Y value of the upper limbs / lower limbs: If 96<total Y value of upper limb / lower limb≤108, the main control module controls the servo motor to adjust the next mode configuration to the enhanced mode; the speed and torque parameters in the enhanced mode are configured to be 1.2 times of the previous mode; If 60<total Y value of upper limb / lower limb≤96, the main control module controls the servo motor to adjust the next mode configuration to the consolidation mode; the speed and torque parameters in the consolidation mode are configured to be 1.05 times of the previous mode; If the total Y value of the upper limb / lower limb is ≤60, the main control module controls the servo motor to adjust the next mode configuration to the weakening mode; the speed and torque parameters in the weakening mode are configured to 0.8 times of the previous mode.

7. The multi-motion mode functional electrical stimulation assisted therapy system according to claim 6, characterized in that: The disease diagnosis report also records: the type of body movement of this training, training method, training time h, the current training time L when muscles are fatigued, the total number of spasms n within the training time h, muscle strength level m, Y value of each channel, total Y value of upper limbs, and total Y value of lower limbs.

8. The multi-motion mode functional electrical stimulation assisted therapy system according to claim 7, characterized in that: Types of body movements include single upper limb circular movements, single lower limb circular movements, and upper and lower limb circular movements.

9. The multi-motion mode functional electrical stimulation assisted therapy system according to claim 8, characterized in that: The total Y value of the upper limb refers to the sum of the Y values ​​of the channel electrode sheets attached to the upper limb, and the total Y value of the lower limb refers to the sum of the Y values ​​of the channel electrode sheets attached to the lower limb.

10. A multi-exercise mode functional electrical stimulation assisted treatment method, using the multi-exercise mode functional electrical stimulation assisted treatment system according to claim 9, characterized in that: The following steps are involved: Step 1: The patient logs in to the account through the patient login unit, and selects and configures the patient's body exercise type, training method and training time h for this training; Step 2: If the user chooses active training, after the selection, the multi-channel FES control system automatically configures the electrode parameters and channel mode of the patient's current training according to the last diagnosis report; The patient actively trains, and the muscle fatigue detection device detects the fatigue of the patient's muscles. When muscle fatigue is detected, the main control module controls the multi-channel FES control system to shut down and records the current training time L; the muscle spasm detection device detects spasms of multiple muscles of the patient respectively. When muscle spasms are detected, the main control module controls the multi-channel FES control system to shut down, and after the muscle spasms are relieved, the training continues until the training reaches time h, and the total number of spasms n within the training time h is counted; the muscle strength detection device detects the strength of multiple muscles of the patient respectively, and outputs the muscle strength level m; The disease diagnosis and quantitative evaluation unit receives the current training time L when the muscle is fatigued, the total number of spasms n within the training time h, and the muscle strength level m; when L>0.5h, the value L=1 is assigned, and when L≤0.5h, the value L=0 is assigned; When n=1, When n=2, When , the value n = 3; the muscle strength level is divided into 0-5 levels, and the values ​​m = 1-5 are assigned respectively; Calculate the patient's condition coefficient Y: Y=L+n+m If 8<Y≤9, the training dynamic adjustment unit controls the multi-channel FES control system to adjust the channel mode configuration of the next training to the enhanced mode; the electrode sheet parameter configuration in the enhanced mode is 1.2 times that of the current training mode; If 5<Y≤8, the training dynamic adjustment unit controls the multi-channel FES control system to adjust the channel mode configuration of the next training to the consolidation mode; the electrode sheet parameter configuration in the consolidation mode is 1.05 times that of the current training mode; If Y≤5, the training dynamic adjustment unit controls the multi-channel FES control system to adjust the channel mode configuration of the next training to the weakening mode; the electrode sheet parameters in the weakening mode are configured to be 0.8 times of the current training mode; Step 3: If the user selects passive training, after the selection, the multi-channel FES control system automatically configures the electrode parameters and channel mode of the patient's current training according to the last diagnosis report; And the main control module automatically configures the mode of controlling the servo motor according to the latest disease diagnosis report; The patient is passively trained. The muscle fatigue detection device detects the fatigue of the patient's muscles. When muscle fatigue is detected, the main control module controls the multi-channel FES control system and the servo motor to stop, and records the current training time L; the muscle spasm detection device detects spasms of multiple muscles of the patient. When muscle spasms are detected, the main control module controls the multi-channel FES control system and the servo motor to stop. After the muscle spasm is relieved, the training continues until the training reaches the time h, and the total number of spasms n within the training time h is counted; the muscle strength detection device detects the strength of multiple muscles of the patient and outputs the muscle strength level m; The disease diagnosis and quantitative evaluation unit receives the current training time L when the muscle is fatigued, the total number of spasms n within the training time h, and the muscle strength level m; when L>0.5h, the value L=1 is assigned, and when L≤0.5h, the value L=0 is assigned; (take integer), assign n = 1, When n=2, When , the value is n = 3; the muscle strength level is divided into 0-5 levels and the values ​​are m = 1-5 respectively; Calculate the patient's condition coefficient Y: Y=L+n+m If 8<Y≤9, the training dynamic adjustment unit controls the multi-channel FES control system to adjust the channel mode configuration of the next training to the enhanced mode; the electrode sheet parameter configuration in the enhanced mode is 1.2 times that of the current training mode; If 5<Y≤8, the training dynamic adjustment unit controls the multi-channel FES control system to adjust the channel mode configuration of the next training to the consolidation mode; the electrode sheet parameter configuration in the consolidation mode is 1.05 times that of the current training mode; If Y≤5, the training dynamic adjustment unit controls the multi-channel FES control system to adjust the channel mode configuration of the next training to the weakening mode; the electrode sheet parameters in the weakening mode are configured to be 0.8 times of the current training mode; The main control module adjusts the mode of the servo motor corresponding to the upper limbs / lower limbs during the next active training according to the total Y value of the upper limbs / lower limbs: If 96<total Y value of upper limb / lower limb≤108, the main control module controls the servo motor to adjust the next mode configuration to the enhanced mode; the speed and torque parameters in the enhanced mode are configured to be 1.2 times of the current mode; If 60<total Y value of upper limb / lower limb≤96, the main control module controls the servo motor to adjust the next mode configuration to the consolidation mode; The speed and torque parameters in the consolidation mode are configured to be 1.05 times that of this mode; If the total Y value of the upper limb / lower limb is ≤60, the main control module controls the servo motor to adjust the next mode configuration to the weakening mode; the speed and torque parameters in the weakening mode are configured to be 0.8 times of this mode; Step 4. Output the disease diagnosis report, which records the type of body movement, training method, training time h, current training time L when muscle fatigue occurs, total number of spasms n within the training time h, muscle strength level m, Y value of each channel, total Y value of upper limbs, total Y value of lower limbs, as well as the channel mode of the next passive training and the mode of the servo motor during the next active training.

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