Intelligent drop foot electrical stimulation system and method with muscle fatigue detection

Abstract

The present invention proposes an intelligent drop foot electrical stimulation system and method with muscle fatigue detection. The method comprises: sensing motion posture data of a lower leg by means of a first inertial sensor; sensing motion posture data of a foot by means of a second inertial sensor; determining a gait stage on the basis of the motion posture data, and calculating a lower leg angle and a foot angle; when the gait stage belongs to a swing phase, controlling an electrical stimulator to generate a first pulse wave to at least one electrode to stimulate the lower leg; and determining, on the basis of the foot angle, whether muscle fatigue occurs in the lower leg during the swing phase, and if the muscle fatigue occurs, controlling the electrical stimulator to generate a second pulse wave to the electrode to stimulate the lower leg, wherein wave parameters of the first pulse wave are different from wave parameters of the second pulse wave. Thus, the problem of insufficient stimulation caused by muscle fatigue can be solved.

Description

Intelligent foot drop electrical stimulation system and method with muscle fatigue detection Technical Field

[0001] This disclosure relates to an intelligent foot drop electrical stimulation system and method with muscle fatigue detection, capable of compensating for muscle fatigue. Background Technology

[0002] Foot drop is a common clinical phenomenon, formally known as ankle plantar flexion. A normal ankle joint can perform dorsiflexion, plantar flexion, inversion, and eversion. When dorsiflexion deteriorates, foot drop occurs. Normal gait requires healthy ankle function; once foot drop occurs, various compensatory gaits emerge. For example, hip-hiking uses pelvic elevation to avoid dragging the foot; steppage gait uses increased hip and knee flexion to prolong the time the foot is off the ground; the healthy foot may exhibit vaulting to help the affected foot leave the ground. Patients with milder symptoms may land on their forefoot or slap the ground. Some patients are unaware of these movements and frequently trip. Therefore, for patients with foot drop, walking is not only energy-consuming but also dangerous, which is a problem that must be faced squarely.

[0003] When a patient completely loses strength in their ankle dorsiflexors, clinical practice typically recommends considering ankle and foot supports or wearing a functional electrical stimulator (fES). FES therapy uses functional electrical currents to stimulate contraction of the tibialis anterior muscle in the lower leg, inducing an active upward flexion of the foot, which can improve gait in stroke patients. Clinically, to assist patients with foot drop in improving locomotion and gait adjustment, surface functional electrical stimulation of the tibialis anterior muscle is a common method. Transcutaneous surface functional electrical stimulation (sFES) is a clinical method that uses transcutaneous surface electrical stimulation of motor nerves (which are not under conscious control) to induce contraction in the muscles innervated by those nerves. This method can help patients who have lost voluntary muscle control due to external injury to regain some bodily functions and improve their daily activities.

[0004] However, continuous stimulation of the tibialis anterior muscle with functional electrical stimulation of the skin surface may lead to muscle fatigue, and when the muscle is fatigued, its movements may not be as expected. Summary of the Invention

[0005] This invention proposes an intelligent foot drop electrical stimulation system and method with muscle fatigue detection. It can use data from an inertial sensor to determine whether muscle fatigue has occurred. When it has occurred, the wave parameters of the electrical stimulation pulse can be modified to increase the average energy of the stimulation, thereby compensating for muscle fatigue.

[0006] This invention proposes an intelligent foot drop electrical stimulation system with muscle fatigue detection, comprising the following components: A first inertial sensor is disposed on the calf and senses first calf movement posture data. A second inertial sensor is disposed on the foot and senses second foot movement posture data. A microcontroller is coupled to the first and second inertial sensors to receive the first and second movement posture data, determine the gait stage based on the first and second movement posture data, and calculate the calf angle and foot angle. The electrical stimulator includes at least one electrode disposed on the calf. When the gait stage is in the swing phase, the microcontroller controls the electrical stimulator to generate a first pulse wave to stimulate the electrode on the calf. The microcontroller also determines whether muscle fatigue has occurred in the calf during the swing phase based on the foot angle. If muscle fatigue occurs, the microcontroller controls the electrical stimulator to generate a second pulse wave to stimulate the electrode on the calf, wherein the waveform parameters of the first pulse wave are different from those of the second pulse wave.

[0007] In one embodiment of the present invention, the aforementioned first motion attitude data includes multiple accelerations and multiple angular velocities. The microcontroller is used to determine whether the change in each acceleration and each angular velocity is greater than a swing period threshold; if so, it determines that the step stage belongs to the swing period.

[0008] In one embodiment of the present invention, the aforementioned second motion attitude data includes multiple accelerations and multiple angular velocities. The microcontroller is used to determine whether the change in each acceleration and each angular velocity is greater than a swing period threshold; if so, it determines that the step stage belongs to the swing period.

[0009] In one embodiment of the present invention, the microcontroller is used to calculate the change in foot angle during the swing period. If the change is less than the initial change, the microcontroller determines that muscle fatigue has occurred in the calf.

[0010] In one embodiment of the present invention, the amplitude of the second pulse wave is greater than that of the first pulse wave.

[0011] In one embodiment of the present invention, the pulse width of the second pulse wave is greater than the pulse width of the second pulse wave.

[0012] In one embodiment of the present invention, the pulse frequency of the second pulse wave is greater than the pulse frequency of the first pulse wave.

[0013] In one embodiment of the present invention, the electrode includes a first electrode and a second electrode, the first electrode corresponding to the common peroneal nerve of the lower leg and the second electrode corresponding to the tibialis anterior muscle of the lower leg.

[0014] In one embodiment of the present invention, the above-described intelligent foot drop electrical stimulation system further includes a wearable knee brace and a foot plate fixation assembly. A first inertial sensor and a microcontroller are disposed on the wearable knee brace. A second inertial sensor is disposed on the foot plate fixation assembly.

[0015] From another perspective, embodiments of the present invention propose an intelligent foot drop electrical stimulation method with muscle fatigue detection, applicable to intelligent foot drop electrical stimulation systems. This intelligent foot drop electrical stimulation method includes: sensing first motion posture data of the lower leg using a first inertial sensor; sensing second motion posture data of the foot using a second inertial sensor; determining the gait stage based on the first and second motion posture data and calculating the lower leg angle and foot angle; when the gait stage is the swing phase, controlling an electrical stimulator to generate a first pulse wave to stimulate at least one electrode to stimulate the lower leg; and during the swing phase, determining whether muscle fatigue has occurred in the lower leg based on the foot angle, and if muscle fatigue has occurred, controlling the electrical stimulator to generate a second pulse wave to stimulate the electrode to stimulate the lower leg, wherein the wave parameters of the first pulse wave are different from those of the second pulse wave.

[0016] In one embodiment of the present invention, the first motion attitude data includes multiple accelerations and multiple angular velocities. The method further includes: determining whether the change in each acceleration and each angular velocity is greater than a swing period threshold; if so, determining that the step stage belongs to the swing period.

[0017] In one embodiment of the present invention, the second motion attitude data includes multiple accelerations and multiple angular velocities. The method further includes: determining whether the change in each acceleration and each angular velocity is greater than a swing period threshold; if so, determining that the step stage belongs to the swing period.

[0018] In one embodiment of the present invention, the method further includes: calculating a change in foot angle during the swing period; and if the change is less than an initial change, determining that muscle fatigue has occurred in the calf.

[0019] To make the above features and advantages of the present invention more apparent and understandable, specific embodiments are described below in conjunction with the accompanying drawings. Attached Figure Description

[0020] Figure 1 is a schematic diagram of an intelligent foot drop electrical stimulation system with muscle fatigue detection according to an embodiment of the present invention.

[0021] Figure 2 is a schematic diagram showing the installation position of the intelligent foot drop electrical stimulation system according to an embodiment;

[0022] Figures 3A to 3C are graphs showing the angular velocity curves measured by the first inertial sensor 120 during the standing and swinging phases according to one embodiment;

[0023] Figures 4A to 4C are graphs showing the angular velocity curves measured by the second inertial sensor 160 during the standing and swinging phases according to one embodiment;

[0024] Figure 5 is a schematic diagram illustrating stimulation of the calf according to one embodiment;

[0025] Figure 6 is a flowchart illustrating the operation and management of the second inertial sensor 16 according to one embodiment;

[0026] Figure 7 is a schematic diagram illustrating the change in foot angle according to one embodiment;

[0027] Figures 8A to 8C are operation flowcharts of an electronic device 170 according to one embodiment;

[0028] Figure 9 is a flowchart illustrating an intelligent foot drop electrical stimulation method with muscle fatigue detection according to an embodiment;

[0029] Figures 10A to 10C are graphs showing angular velocities measured by a second inertial sensor when muscle fatigue occurs, according to one embodiment. Detailed Implementation

[0030] Some embodiments of the present invention will now be described in detail with reference to the accompanying drawings. Component symbols used in the following description, when appearing in different drawings, are considered to be the same or similar components. These embodiments are only a part of the present invention and do not disclose all possible implementations of the invention. More precisely, these embodiments are merely examples of systems and methods within the scope of the claims of the present invention.

[0031] The terms "first," "second," etc., used in this article do not specifically refer to order or sequence; they are merely used to distinguish components or operations described using the same technical terms.

[0032] Figure 1 is a schematic diagram of an intelligent foot drop electrical stimulation system with muscle fatigue detection according to an embodiment of the present invention. Referring to Figure 1, the intelligent foot drop electrical stimulation system 100 includes an electronic device 170 and a second inertial sensor 160. The electronic device 170 includes a microcontroller 110, a first inertial sensor 120, a display 130, and an electrical stimulator 140. The microcontroller 110 is coupled to the first inertial sensor 120, the second inertial sensor 160, the display 130, and the electrical stimulator 140.

[0033] The first inertial sensor 120 and the second inertial sensor 160 may include accelerometers, gyroscopes, etc., to measure motion data such as acceleration and angular velocity. The motion data sensed by the first inertial sensor 120 is also called first motion data, and the motion data sensed by the second inertial sensor 160 is also called second motion data. This motion data is transmitted to the microcontroller 110. In other embodiments, the motion data may also include arbitrary information such as the state of motion and whether the angle change is sufficient. In this embodiment, the first inertial sensor 120 is electrically connected to the microcontroller 110 in a wired manner, and the second inertial sensor 160 is wirelessly coupled to the microcontroller 110 (e.g., via Bluetooth). However, in other embodiments, both the first inertial sensor 120 and the second inertial sensor 160 may be coupled to the microcontroller 110 in a wired or wireless manner, and this invention is not limited to this.

[0034] The microcontroller 110 may be a microprocessor, a programmable controller, an application-specific integrated circuit (ASIC), a programmable logic device (PLD), or other components with computing capabilities.

[0035] The display 130 may include a liquid crystal display panel, an organic light-emitting diode panel, an electronic paper panel, etc., and the present invention is not limited thereto. In some embodiments, the display 130 is a touch panel, and the display 130 may display one or more graphic objects (e.g., buttons), which the user can press to make settings. Alternatively, in some embodiments, the electronic device 170 may also include physical buttons.

[0036] The electrical stimulator 140 includes a pulse generator 141, a first electrode 142, and a second electrode 143. The pulse generator 141 generates pulse waves that are conducted through wires to the first electrode 142 and the second electrode 143. These pulse waves can be square waves, triangular waves, sine waves, etc., and the present invention does not limit the waveform of the pulse waves.

[0037] Figure 2 is a schematic diagram showing the installation position of an intelligent foot drop electrical stimulation system according to one embodiment. In the embodiment of Figure 2, the intelligent foot drop electrical stimulation system also includes a wearable knee brace 210 and a footplate fixation assembly 240. The wearable knee brace 210 includes, for example, an elastic strap for covering and fixing to the patient's knee, and an electronic device 170 is disposed on the wearable knee brace 210. In addition, the footplate fixation assembly 240 is, for example, a strap for fixing to the patient's footplate, and a second inertial sensor 160 is disposed on the footplate fixation assembly.

[0038] Referring to Figures 1 and 2, a first inertial sensor 120 can be placed on the lower leg 230 of the patient suffering from foot drop symptoms and sense the first motion posture data of the lower leg 230. A second inertial sensor 160 can be placed on the foot 240 and sense the second motion posture data of the foot 240. This motion posture data is transmitted to a microcontroller 110, which can analyze the gait phase in real time and calculate the lower leg angle and foot angle based on this motion posture data. Specifically, the angle can be obtained by integrating the angular velocity. In addition, the gait phase of a step can include a stance phase and a swing phase. The swing phase can be further subdivided into four sub-phases: pre-swing, initial swing, mid-swing, and terminal swing. The pre-swing and terminal swing phases can represent the state where the foot 240 is partially on the ground and partially suspended in the air, while the initial swing and mid-swing phases can represent the state where the foot 240 is completely suspended in the air. In some embodiments, the microcontroller 110 can determine whether it has entered the oscillation period based on the changes in acceleration and angular velocity in the first motion posture data or the second motion posture data.

[0039] Specifically, Figures 3A to 3C are graphs illustrating the angular velocity curves measured by the first inertial sensor 120 during the standing and oscillating phases according to one embodiment. Here, the X-axis is defined as parallel to the ground surface and parallel to the direction of travel, the Y-axis as parallel to the ground surface and perpendicular to the direction of travel, and the Z-axis as perpendicular to the ground surface. Referring to Figure 3A, the horizontal axis represents time, and the vertical axis represents the numerical value of the angular velocity. Curve 310 represents the X-axis angular velocity measured by the first inertial sensor 120 during the oscillating phase, while curve 320 represents the X-axis angular velocity measured by the first inertial sensor 120 during the standing phase. In some embodiments, the microcontroller 110 can acquire any two angular velocities measured by the first inertial sensor 120 on the X-axis, referred to as the first angular velocity and the second angular velocity, respectively. In other words, both the first and second angular velocities are located on the X-axis, but the time point of the first angular velocity differs from the time point of the second angular velocity; for example, the two angular velocities are separated by n sampling points, where n is a positive integer greater than or equal to 1. The microcontroller 110 determines whether the change in X-axis angular velocity is greater than a swing period threshold. For example, the change can be obtained by calculating the difference between the second angular velocity and the first angular velocity. When the change is greater than the swing period threshold, it indicates that the current gait phase may belong to the swing period.

[0040] Referring to Figure 3B, curve 330 represents the Y-axis angular velocity measured by the first inertial sensor 120 during the swing phase, while curve 340 represents the Y-axis angular velocity measured by the first inertial sensor 120 during the standing phase. Referring to Figure 3C, curve 350 represents the Z-axis angular velocity measured by the first inertial sensor 120 during the swing phase, while curve 360 ​​represents the Z-axis angular velocity measured by the first inertial sensor 120 during the standing phase. In some embodiments, in addition to the X-axis angular velocity, the changes in the Y-axis angular velocity and Z-axis angular velocity are also calculated, as well as the changes in X-axis acceleration, Y-axis acceleration, and Z-axis acceleration. In other words, there are a total of 6 changes. When all 6 changes are greater than the swing phase threshold, the current gait phase is determined to be the swing phase; otherwise, the current gait phase is determined to be the standing phase.

[0041] In addition to using the motion attitude data of the first inertial sensor 120, the motion attitude data of the second inertial sensor 160 can also be used to identify the oscillation and standing phases. Figures 4A to 4C are graphs showing the angular velocity curves measured by the second inertial sensor 160 during the standing and oscillation phases according to one embodiment. Referring to Figure 4A, curve 410 represents the X-axis angular velocity measured by the second inertial sensor 160 during the oscillation phase, while curve 420 represents the X-axis angular velocity measured by the second inertial sensor 160 during the standing phase. Referring to Figure 4B, curve 430 represents the Y-axis angular velocity measured by the second inertial sensor 160 during the oscillation phase, while curve 440 represents the Y-axis angular velocity measured by the second inertial sensor 160 during the standing phase. Referring to Figure 4C, curve 450 represents the Z-axis angular velocity measured by the second inertial sensor 160 during the oscillation phase, while curve 460 represents the Z-axis angular velocity measured by the second inertial sensor 160 during the standing phase. Similarly, the microcontroller 110 determines whether the changes in X-axis angular velocity, Y-axis angular velocity, Z-axis angular velocity, X-axis acceleration, Y-axis acceleration, and Z-axis acceleration are greater than a swing phase threshold. If all six changes are greater than the swing phase threshold, the current gait phase is determined to be the swing phase; otherwise, the current gait phase is determined to be the standing phase.

[0042] Figure 5 is a schematic diagram illustrating calf stimulation according to one embodiment. Referring to Figures 1 and 5, after determining the swing phase, the microcontroller 110 controls the electrical stimulator 140 to output a pulse wave (also called a first pulse wave) to electrodes 142 and 143 during the swing phase. For example, the microcontroller 110 can control the electrical stimulator 140 to output a pulse wave when the early swing phase is detected, and control the electrical stimulator 140 to stop outputting pulse waves when the late swing phase is detected. The pulse wave output to the first electrode 142 is used to stimulate the common peroneal nerve 510 of the calf 230, and the pulse wave output to the second electrode 143 is used to stimulate the tibialis anterior muscle 520 of the calf 230. The pulse waves output to the first electrode 142 and the second electrode 143 may have the same or different waveform parameters. It is worth noting that the first electrode 142 and the second electrode 143 can be attached to the skin of the lower leg 230 to conduct electrical stimulation pulse waves, and the pulse wave generator 141 can generate biphasic pulse trains with specific amplitude, frequency and pulse width according to the instructions of the microcontroller 110 to appropriately stimulate the common peroneal nerve 510, induce the tibialis anterior muscle 520 to contract and produce ankle and foot dorsiflexion.

[0043] In addition, the microcontroller 110 determines whether muscle fatigue has occurred in the calf 230 based on the foot angle during the swing phase. When muscle fatigue occurs, the change in foot angle is relatively small, so the change in foot angle during the swing phase can be used to determine whether muscle fatigue has occurred. If muscle fatigue occurs, the microcontroller 110 controls the electrical stimulator 140 to generate another pulse wave (also called a second pulse wave) at electrodes 142 and 143 to stimulate the calf 230. The first pulse wave has at least one wave parameter that differs from the second pulse wave parameter. This wave parameter can be amplitude, pulse frequency, pulse width, etc. For example, the amplitude of the second pulse wave can be greater than that of the first pulse wave, the pulse width of the second pulse wave can be greater than that of the first pulse wave, or the pulse frequency of the second pulse wave can be greater than that of the first pulse wave. Therefore, the second pulse wave will generate greater average energy, thereby compensating for muscle fatigue.

[0044] In this embodiment, the second inertial sensor 160 transmits data to the microcontroller 110 via Bluetooth. Therefore, the second inertial sensor 160 can also be paired with a controller for related system management. The operation of this controller paired with the second inertial sensor 160 is described below. Figure 6 is a flowchart illustrating the operation management of the second inertial sensor 160 according to one embodiment. Referring to Figure 6, in step 601, an initial procedure is executed, such as configuring memory, setting initial parameters, etc. In step 602, a sleep mode is entered. In this mode, the second inertial sensor 160 and the corresponding controller do not generate clock signals, and the memory in the controller does not retain data. In step 603, a wake-up command is awaited. In step 604, it is determined whether a wake-up command has been received. In some embodiments, if the second inertial sensor 160 receives new motion attitude data, it indicates that a wake-up command has been received. In other embodiments, the second inertial sensor 160 can also receive a wake-up command from the microcontroller 110. If no wake-up command is received, the process returns to step 602; otherwise, step 605 is performed to provide power (start generating a clock signal). In step 606, it is determined whether the system is idle. Idleness is indicated when no operation is performed for more than a preset time (e.g., 30 seconds). If idle, the system returns to step 602; otherwise, it proceeds to step 607. In step 607, motion posture data and foot angle generated within a stride are received. This foot angle can be calculated by the controller of the second inertial sensor 160 or by the microcontroller 110, which is not limited to this method. In step 608, it is determined whether the foot angle is correct. In some embodiments, the change in foot angle during the swing phase can be calculated. Figure 7 is a schematic diagram illustrating the change in foot angle according to an embodiment. Referring to Figures 6 and 7, when the change in foot angle 710 during the swing phase is less than an initial change, it can be determined that muscle fatigue has occurred in the calf (the result of step 608 is negative). Next, step 609 is performed, transmitting the corresponding signal to the electronic device 170. On the other hand, if the change in foot angle during the swing phase 710 is greater than or equal to the initial change, it can be determined that there is no muscle fatigue in the calf (the result of step 608 is yes), and then step 610 is performed to transmit the corresponding signal to the electronic device 170. In some embodiments, the signals transmitted in steps 609 and 610 represent a state, not an angle.

[0045] Figures 8A to 8C are operation flowcharts of an electronic device 170 according to one embodiment. Referring to Figure 8A, in step 801, an initial procedure is executed, such as configuring memory, setting parameters, etc. In step 802, sleep mode is entered. In step 803, a wake-up command is awaited. In step 804, it is determined whether a wake-up command has been received. In some embodiments, a wake-up command is generated to the microcontroller 110 when the first inertial sensor 120 receives new data; in other embodiments, the patient can also generate a wake-up command via the display 130 or a physical button. If no wake-up command is received, the process returns to step 802; otherwise, step 805 is performed to turn on the power (start generating a clock). In step 806, it is determined whether the device is idle, for example, if no operation is performed for more than a preset time (e.g., 30 seconds), indicating a delay. If the device is determined to be idle, the process returns to step 802; otherwise, step 807 is performed. In step 807, a low battery condition is detected. If there is no low battery condition, in step 808, motion posture data within a step is obtained and the gait phase is calculated. In this embodiment, the gait phase can be calculated based on the first motion posture data.

[0046] Referring to Figure 8B, in step 809, it is determined whether the gait phase is the swing phase. If the result of step 809 is no, proceed to step 814. If it is in the swing phase, proceed to step 810, control the electrical stimulator 140 to generate a pulse wave, and in step 811 receive a signal from the second inertial sensor 160 (to indicate whether the foot angle is correct, please refer to the flowchart in Figure 6). In step 812, it is determined whether the foot angle is correct. If not, proceed to step 813, adjust at least one wave parameter, such as adjustable amplitude, pulse frequency, pulse width, etc. If the foot angle is correct, proceed to step 814. In step 814, it is determined whether it is in the operating mode. If yes, proceed to step 815, determine whether to enter the wave adjustment mode. If the result of step 815 is yes, proceed to step 816, enter the wave parameter adjustment mode, and generate a second pulse wave to the electrode after adjusting the wave parameter; otherwise, proceed to step 817, enter the amplitude adjustment mode, and generate a second pulse wave to the electrode after adjusting the amplitude.

[0047] Referring to Figure 8C, in step 818, it is determined whether the setting mode is active. If the result of step 818 is yes, steps 819-821 are performed, providing interfaces to edit the pulse frequency, pulse width, and the interval between two pulses in opposite directions, in response to the operation on the display 130. The patient can choose which waveform parameter to edit. Next, step 822 is performed to determine whether to increase the waveform parameter, which can also be set via the display 130. If the result of step 822 is yes, a default value (e.g., 1) is added to the corresponding waveform parameter in step 823. If the result of step 822 is no, step 824 is performed to determine whether to decrease the waveform parameter, which can also be set via the display 130. If the result of step 824 is yes, a default value (e.g., 1) is subtracted from the corresponding waveform parameter in step 825. Finally, step 826 displays the relevant information (e.g., the adjusted waveform parameter) on the display 130.

[0048] Figure 9 is a flowchart illustrating an intelligent foot drop electrical stimulation method with muscle fatigue detection according to an embodiment. Referring to Figure 9, in step 901, a first motion posture data of the lower leg is sensed by a first inertial sensor. In step 902, a second motion posture data of the foot is sensed by a second inertial sensor. In step 903, the gait stage is determined based on the first and second motion posture data, and the lower leg angle and foot angle are calculated. In step 904, it is determined whether the gait is in the swing phase. If it is in the swing phase, in step 905, the electrical stimulator generates a first pulse wave to stimulate at least one electrode to stimulate the lower leg. Next, in step 906, during the swing phase, it is determined whether muscle fatigue has occurred in the lower leg based on the foot angle. In the above embodiment, the change in foot position is used to determine whether muscle fatigue has occurred, but in other embodiments, waveform comparison can also be used for determination.

[0049] Figures 10A to 10C are graphs illustrating the angular velocity measured by a second inertial sensor when muscle fatigue occurs, according to one embodiment. Referring to Figure 10A, curve 1010 represents the angular velocity measured by the second inertial sensor along the X-axis under normal conditions, and curve 1020 represents the angular velocity measured by the second inertial sensor along the X-axis when muscle fatigue occurs. Referring to Figure 10B, curve 1030 represents the angular velocity measured by the second inertial sensor along the Y-axis under normal conditions, and curve 1040 represents the angular velocity measured by the second inertial sensor along the Y-axis when muscle fatigue occurs. Referring to Figure 10C, curve 1050 represents the angular velocity measured by the second inertial sensor along the Z-axis under normal conditions, and curve 1060 represents the angular velocity measured by the second inertial sensor along the Z-axis when muscle fatigue occurs. In some embodiments, the angular velocities of multiple patients along each axis during movement can be collected and labeled. For example, curves at 1010, 1030, and 1050 are labeled "normal," while curves at 1020, 1040, and 1060 are labeled "abnormal." These angular velocities and labels are then used to train a machine learning model. This machine learning model can be a decision tree, random forest, k-nearest neighbor algorithm, multi-level neural network, convolutional neural network, support vector machine, extreme gradient boosting (XGBoost), autoencoder, etc., and this invention is not limited to these. During the testing phase, the corresponding angular velocities (including X, Y, and Z axes) can be input into the trained machine learning model to determine whether muscle fatigue has occurred.

[0050] Referring back to Figure 9, if muscle fatigue occurs, in step 907, the electrical stimulator generates a second pulse wave to stimulate the calf, wherein the waveform parameters of the first pulse wave are different from those of the second pulse wave. If muscle fatigue does not occur, the first pulse wave continues to be generated to stimulate the calf. The steps in Figure 9 have been described in detail above and will not be repeated here. It is worth noting that each step in Figure 9 can be implemented as multiple program codes or circuits, and this invention is not limited thereto. Furthermore, the method in Figure 9 can be used in conjunction with the above embodiments or used alone; in other words, other steps can be added between the steps in Figure 9.

[0051] In the aforementioned system and method, timely electrical stimulation of the calf can improve foot drop. Additionally, when muscle fatigue occurs, the average energy of the electrical stimulation can be adjusted accordingly to prevent insufficient dorsiflexion angle.

[0052] The aforementioned systems and methods can be used in many technical fields and application scenarios, including intelligent gait detection, automatic adjustment of electrical stimulation intensity, manual selection of electrical stimulation intensity, and cloud databases. Intelligent gait detection detects information such as angles and gait patterns, and can be combined with other devices or systems to adjust electrical stimulation intensity. For example, intelligent gait detection can be used to help with muscle weakness related to upper motor neuron diseases / injuries, improve individual gait (foot drop), provide muscle re-education, address muscle fatigue caused by electrical stimulation, maintain or increase joint range of motion, and increase local blood flow (circulation). Alternatively, the system disclosed herein can automatically adjust the electrical stimulation intensity, similarly used to help with muscle weakness related to upper motor neuron diseases / injuries, address muscle fatigue caused by electrical stimulation, maintain or increase joint range of motion, and increase local blood flow (circulation). In some situations, the aforementioned systems and methods can provide angle, gait, and other information to healthcare professionals, who can then help with muscle weakness related to upper motor neuron diseases / injuries; this falls under the category of manually selected electrical stimulation intensity (non-automatic). In some scenarios, the aforementioned systems and methods can upload any calculated information, including angles, gait, and electrical stimulation intensity, to a cloud database. Other relevant personnel can then obtain this information from the cloud database for use in any suitable situation. For example, it can be used to help with muscle weakness related to upper motor neuron diseases / injuries, improve individual gait (foot drop), re-educate muscles, resolve muscle fatigue caused by electrical stimulation, maintain or increase joint range of motion, and increase local blood flow (blood circulation).

[0053] Although the present invention has been disclosed above by way of embodiments, it is not intended to limit the present invention. Any person skilled in the art may make some modifications and refinements without departing from the spirit and scope of the present invention. Therefore, the scope of protection of the present invention shall be determined by the scope of the appended claims.

[0054] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, and not to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some or all of the technical features; and these modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present invention.

Claims

1. A smart foot drop electrical stimulation system with muscle fatigue detection, characterized in that, Include: A first inertial sensor is installed on the lower leg and senses the first motion posture data of the lower leg; A second inertial sensor is installed on the foot and senses the second motion posture data of the foot; A microcontroller, coupled to the first inertial sensor and the second inertial sensor, receives the first motion posture data and the second motion posture data, determines the gait stage based on the first motion posture data and the second motion posture data, and calculates the lower leg angle and the foot angle; and An electrical stimulator, comprising electrodes disposed on the lower leg. When the gait phase is the swing phase, the microcontroller controls the electrical stimulator to generate a first pulse to stimulate the electrodes in the calf. The microcontroller is used to determine whether muscle fatigue occurs in the calf based on the foot angle during the swinging period. If muscle fatigue occurs, the microcontroller controls the electrical stimulator to generate a second pulse wave to stimulate the calf by supplying the electrodes. The wave parameters of the first pulse wave are different from those of the second pulse wave.

2. The intelligent foot drop electrical stimulation system according to claim 1, characterized in that, The first motion attitude data includes multiple accelerations and multiple angular velocities. The microcontroller is used to determine whether the change in each of the plurality of accelerations and each of the plurality of angular velocities is greater than the swing period threshold; if so, it is determined that the gait phase belongs to the swing period.

3. The intelligent foot drop electrical stimulation system according to claim 1, characterized in that, The second motion attitude data includes multiple accelerations and multiple angular velocities. The microcontroller is used to determine whether the change in each of the plurality of accelerations and each of the plurality of angular velocities is greater than the swing period threshold; if so, it is determined that the gait phase belongs to the swing period.

4. The intelligent foot drop electrical stimulation system according to claim 1, characterized in that, The microcontroller is used to calculate the change in the foot angle during the swinging phase. If the change is less than the initial change, the microcontroller determines that the calf has experienced muscle fatigue.

5. The intelligent foot drop electrical stimulation system according to claim 1, characterized in that, The amplitude of the second pulse is greater than the amplitude of the first pulse.

6. The intelligent foot drop electrical stimulation system according to claim 1, characterized in that, The pulse width of the second pulse is greater than the pulse width of the first pulse.

7. The intelligent foot drop electrical stimulation system according to claim 1, characterized in that, The pulse frequency of the second pulse is greater than that of the first pulse.

8. The intelligent foot drop electrical stimulation system according to claim 1, characterized in that, The electrode includes a first electrode and a second electrode, the first electrode corresponding to the common peroneal nerve of the lower leg, and the second electrode corresponding to the tibialis anterior muscle of the lower leg.

9. The intelligent foot drop electrical stimulation system according to claim 1, characterized in that, Also includes: A wearable knee brace, wherein the first inertial sensor and the microcontroller are disposed on the wearable knee brace; and A footplate fixation assembly, wherein the second inertial sensor is disposed on the footplate fixation assembly.

10. A smart foot drop electrical stimulation method with muscle fatigue detection, characterized in that, Applicable to intelligent foot drop electrical stimulation systems, the intelligent foot drop electrical stimulation method includes: The first motion posture data of the lower leg is sensed by the first inertial sensor; The second inertial sensor senses the second motion posture data of the foot; The gait stage is determined based on the first and second motion posture data, and the lower leg angle and foot angle are calculated. When the gait phase is the swing phase, the electrical stimulator generates a first pulse wave to stimulate the lower leg to the electrodes. as well as During the swinging period, the angle of the foot is used to determine whether muscle fatigue occurs in the calf. If muscle fatigue occurs, the electrical stimulator is controlled to generate a second pulse wave to stimulate the electrode to stimulate the calf. The wave parameters of the first pulse wave are different from those of the second pulse wave.

11. The intelligent foot drop electrical stimulation method according to claim 10, characterized in that, The first motion posture data includes multiple accelerations and multiple angular velocities, and the intelligent foot drop electrical stimulation method further includes: Determine whether the change in each of the plurality of accelerations and each of the plurality of angular velocities is greater than the swing period threshold; if so, determine that the gait phase belongs to the swing period.

12. The intelligent foot drop electrical stimulation method according to claim 10, characterized in that, The second motion posture data includes multiple accelerations and multiple angular velocities, and the intelligent foot drop electrical stimulation method further includes: Determine whether the change in each of the plurality of accelerations and each of the plurality of angular velocities is greater than the swing period threshold; if so, determine that the gait phase belongs to the swing period.

13. The intelligent foot drop electrical stimulation method according to claim 10, characterized in that, Also includes: Calculate the change in the foot angle during the swing phase; as well as If the change is less than the initial change, it is determined that the calf muscle has experienced fatigue.

14. The intelligent foot drop electrical stimulation method according to claim 10, characterized in that, The amplitude of the second pulse is greater than the amplitude of the first pulse.

15. The intelligent foot drop electrical stimulation method according to claim 10, characterized in that, The pulse width of the second pulse is greater than the pulse width of the first pulse.

16. The intelligent foot drop electrical stimulation method according to claim 10, characterized in that, The pulse frequency of the second pulse is greater than that of the first pulse.

17. The intelligent foot drop electrical stimulation method according to claim 10, characterized in that, The electrode includes a first electrode and a second electrode, the first electrode corresponding to the common peroneal nerve of the lower leg, and the second electrode corresponding to the tibialis anterior muscle of the lower leg.

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