Rehabilitation training device based on multi-split muscle activation feedback and electronic equipment

Abstract

The embodiment of the invention relates to the field of rehabilitation training, and discloses a rehabilitation training device based on multi-split muscle activation feedback and electronic equipment, and the device comprises a signal collection module which is arranged in a body surface projection area of multi-split muscle and is used for obtaining a multi-split muscle signal in a process of performing rehabilitation training for a target training action; and the processor is connected with the signal acquisition module and is used for calculating an activation level in real time according to the multi-split muscle signal and outputting a feedback signal for reflecting a relationship between the activation level and a target training interval. According to the rehabilitation training device based on the multifidus muscle activation feedback, the problems of accurately monitoring the multifidus muscle activation condition and providing instant feedback and action guidance in dynamic waist rehabilitation training are solved, so that the multifidus muscle activation condition can be accurately monitored in the dynamic waist rehabilitation training, and the rehabilitation training efficiency is improved. Immediate feedback and action guidance are provided, and real-time and understandable biological feedback is formed in daily rehabilitation training.

Description

Technical Field

[0001] The embodiments of the present invention relate to the field of rehabilitation training, and in particular to a rehabilitation training device and electronic device based on multifidus muscle activation feedback. Background Technology

[0002] Current clinical lumbar rehabilitation training often adopts the concept of "core stability training," such as the bridge pose, four-point kneeling contralateral extension, and plank. However, in practice, patients often find it difficult to accurately perceive the contraction of the deep multifidus muscles. Most only feel "tightness on both sides of the lower back" and "pushing in the buttocks," without being clear whether the target muscles have been truly activated. Therapists often rely on empirical judgments such as palpation and observation of movement patterns, making it difficult to quantitatively monitor and assess the multifidus muscles in real time during dynamic training.

[0003] Current instrumental methods, such as isokinetic muscle strength testing, surface electromyography (EMG), or ultrasound imaging, are mostly used in assessment or research settings. They are either expensive and bulky, or require specialized operation and offline analysis, making it difficult to generate real-time, understandable biofeedback in daily rehabilitation training. Therefore, the field currently lacks rehabilitation training programs that can accurately monitor multifidus muscle activation during dynamic training and provide immediate feedback and movement guidance. Summary of the Invention

[0004] The purpose of this invention is to provide at least one rehabilitation training device and electronic device based on multifidus muscle activation feedback, which can at least solve the problem of accurately monitoring multifidus muscle activation and providing real-time feedback and movement guidance in dynamic lumbar rehabilitation training.

[0005] To address the aforementioned technical problems, at least one embodiment of this application provides a rehabilitation training device based on multifidus muscle activation feedback, comprising: a signal acquisition module disposed on the surface projection area of ​​the multifidus muscle, used to acquire multifidus muscle signals during rehabilitation training for a target training movement; and a processor connected to the signal acquisition module, used to calculate the activation level in real time based on the multifidus muscle signals, and output a feedback signal reflecting the relationship between the activation level and the target training zone.

[0006] At least one embodiment of this application also provides an electronic device, including: at least one processor; and a memory communicatively connected to the at least one processor; wherein the memory stores instructions executable by the at least one processor, the instructions being executed by the at least one processor to enable the at least one processor to acquire multifidus muscle signals during rehabilitation training for a target training movement based on a signal acquisition module disposed on the surface projection area of ​​the multifidus muscle, calculate the activation level in real time, and output a feedback signal reflecting the relationship between the activation level and the target training zone.

[0007] The rehabilitation training device based on multifidus muscle activation feedback provided in the embodiments of this application acquires multifidus muscle signals during rehabilitation training for target training movements through a signal acquisition module set on the surface projection area of ​​the multifidus muscle. It further calculates the activation level in real time based on the multifidus muscle signals and outputs a feedback signal reflecting the relationship between the activation level and the target training zone. Thus, in dynamic lumbar rehabilitation training, it can accurately monitor the activation of the multifidus muscle and provide immediate feedback and movement guidance, forming real-time and understandable biofeedback in daily rehabilitation training.

[0008] In some optional embodiments, the signal acquisition module includes at least one of an electromyographic device and an ultrasound device; when the signal acquisition module includes an electromyographic device, the electromyographic device is attached to the surface projection area of ​​the multifidus muscle; when the signal acquisition module includes an ultrasound device, the ultrasound device is fixed to the surface projection area of ​​the multifidus muscle.

[0009] In some optional embodiments, the multifidus muscle signal includes one of the electromyographic signal of the multifidus muscle and the thickness signal of the multifidus muscle; the activation level includes one of the electromyographic RMS value of the multifidus muscle and the percentage change in the thickness of the multifidus muscle.

[0010] In some optional embodiments, a preprocessing module is also included, connected to the signal acquisition module and the processor, for pre-amplifying, filtering and rectifying the multifidus muscle signal.

[0011] In some optional embodiments, the signal acquisition module is further configured to: acquire multifidus muscle signals during pre-training of a pre-training movement before performing rehabilitation training for the target training movement; the processor is further configured to determine the target training interval based on the multifidus muscle signals during the pre-training movement.

[0012] In some optional embodiments, the processor is configured to determine the maximum value of the multifidus muscle signal during the pre-training action as an activation threshold, and determine the target training interval based on the activation threshold.

[0013] In some optional embodiments, the processor is configured to determine the average value of the multifidus muscle signal during the pre-training action as an activation threshold, and determine the target training interval based on the activation threshold.

[0014] In some optional embodiments, the feedback signal includes at least one of a visual signal, an audio signal, and a vibration signal; the visual signal reflects the relationship between the activation level and the target training range through an energy display bar or a color display bar; the audio signal reflects the relationship between the activation level and the target training range through a prompt message; and the vibration signal reflects the relationship between the activation level and the target training range through vibration intensity.

[0015] In some optional embodiments, the processor is further configured to: record at least one of the following during rehabilitation training of the target training action: activation level calculated in real time, duration of the target training action, peak activation level, and percentage of time the activation level reaches the target training interval; and sort different target training actions according to the recorded information to generate a target rehabilitation training plan. Attached Figure Description

[0016] One or more embodiments are illustrated by way of example with reference to the accompanying drawings, and these illustrative descriptions do not constitute a limitation on the embodiments.

[0017] Figure 1 This is a schematic diagram of a rehabilitation training device based on multifidus muscle activation feedback provided in an embodiment of this application; Figure 2 This is a schematic diagram of the connection between the signal amplifier and the electrodes provided in an embodiment of this application; Figure 3 This is a schematic diagram of the surface electrode provided in an embodiment of this application; Figure 4 This is a schematic diagram of the structure of a rehabilitation training device based on multifidus muscle activation feedback provided in an embodiment of this application. Detailed Implementation

[0018] To make the objectives, technical solutions, and advantages of the embodiments of this application clearer, the various embodiments of this application will be described in detail below with reference to the accompanying drawings. However, those skilled in the art will understand that many technical details have been provided in the various embodiments of this application to help readers better understand this application. However, the technical solutions claimed in this application can be implemented even without these technical details and various changes and modifications based on the following embodiments. The division of the various embodiments below is for the convenience of description and should not constitute any limitation on the specific implementation of this application. The various embodiments can be combined with and referenced by each other without contradiction.

[0019] To facilitate understanding of the embodiments of this application, relevant content on lumbar rehabilitation training will be introduced first.

[0020] Chronic low back pain has a high incidence rate among the elderly and is closely related to factors such as lumbar degeneration, abnormal posture, and prolonged sitting with little movement. Among these factors, the deep multifidus muscle is a key muscle in maintaining lumbar segmental stability, characterized by short fibers, close proximity to the vertebral body, and sensitivity to small-range postural adjustments. Numerous studies have found that patients with chronic low back pain often exhibit multifidus muscle atrophy, fatty infiltration, and delayed activation. This means that during trunk movements or resisted movements, the multifidus muscle response is delayed, while compensatory muscle groups such as the superficial erector spinae are over-engaged, leading to a further decrease in lumbar segmental stability.

[0021] Current clinical lumbar rehabilitation training often adopts the concept of "core stability training," such as the bridge pose, four-point kneeling contralateral extension, and plank. However, in practice, patients often find it difficult to accurately perceive the contraction of the deep multifidus muscles. Most only feel "tightness on both sides of the lower back" and "pushing in the buttocks," without being clear whether the target muscles have been truly activated. Therapists often rely on empirical judgments such as palpation and observation of movement patterns, making it difficult to quantitatively monitor and assess the multifidus muscles in real time during dynamic training.

[0022] Current instruments and methods, such as isokinetic muscle strength testing, surface electromyography, or ultrasound imaging, are mostly used in assessment or research scenarios. They are either expensive and bulky, or require professional operation and offline analysis, making it difficult to generate real-time and understandable biofeedback in daily rehabilitation training.

[0023] Some related technologies use structures such as a base, tilting seat, armrests, and grips to allow users to perform two training modes—lumbar rotation and left / right tilting—while sitting or kneeling, thereby training the lumbar and core muscles. Although the device structure is adjustable and can be oriented in various directions, it primarily focuses on engaging the overall lumbar / core muscles, without specifically targeting the activation of deep lumbar segmental muscles (such as the multifidus). The device lacks a real-time monitoring or feedback mechanism for deep muscle activation, only providing structural resistance. Other related technologies collect electromyographic signals, pressure signals, and displacement signals, and visualize changes in core muscles (including the abdominal wall and trunk) to help users monitor their core muscle function. While signal monitoring and display are achieved, they primarily target the abdominal wall or trunk as a whole core muscle group, rather than specifically targeting the deep multifidus muscles of the lumbar segment.

[0024] To address the aforementioned technical challenges of accurately monitoring multifidus muscle activation and providing immediate feedback and movement guidance during dynamic lumbar rehabilitation training, this invention proposes a rehabilitation training device based on multifidus muscle activation feedback. The implementation details of this embodiment of the rehabilitation training device based on multifidus muscle activation feedback are described below. The following details are provided for ease of understanding and are not essential for implementing this solution.

[0025] Example 1: The rehabilitation training device based on multifidus muscle activation feedback in this embodiment can be applied to electronic devices with communication, computing, and data storage capabilities. Its specific process can be as follows: Figure 1 As shown, it includes: The signal acquisition module 101 is located on the surface projection area of ​​the multifidus muscle and is used to acquire multifidus muscle signals during rehabilitation training for the target training movements.

[0026] The processor 102, connected to the signal acquisition module, is used to calculate the activation level in real time based on the multifidus muscle signal and output a feedback signal that reflects the relationship between the activation level and the target training zone.

[0027] Specifically, the target training movements refer to movements selected for the current patient that are suitable for their lumbar stability training, such as the supine bridge, side bridge, and four-point kneeling contralateral extension. Different patients can choose different target training movements, and there can be one or more target training movements. For example, the current patient may be an elderly person or someone who needs lumbar stability training. In addition to classic movements such as the bridge and side bridge, various movements can be selected according to the patient's tolerance, such as seated resisted lumbar extension and standing gait training combined with multifidus muscle feedback.

[0028] In this embodiment, a signal acquisition module located on the surface projection area of ​​the multifidus muscle acquires multifidus muscle signals during rehabilitation training for the target training movements. The activation level is then calculated in real time based on the multifidus muscle signals, and a feedback signal reflecting the relationship between the activation level and the target training zone is output. Thus, in dynamic lumbar rehabilitation training, the activation status of the multifidus muscle can be accurately monitored, and immediate feedback and movement guidance can be provided, forming real-time and understandable biofeedback in daily rehabilitation training.

[0029] In some embodiments, the signal acquisition module includes at least one of an electromyography (EMG) device and an ultrasound device, wherein the EMG device includes at least one of an EMG sensor and an EMG surface electrode.

[0030] Specifically, when the signal acquisition module includes an electromyography (EMG) device, the EMG sensor or electrode is attached to the surface projection area of ​​the multifidus muscle. In practical applications, the EMG sensor or surface electrode can be attached to the surface projection area of ​​the multifidus muscle according to pre-designed anatomical landmarks (e.g., 2-3 cm lateral to the spinous processes of the 4th-5th lumbar vertebrae). If necessary, palpation can be used to confirm the muscle location of the multifidus muscle. An 8-channel surface electrode can be selected. When the signal acquisition module includes an ultrasound device, the ultrasound device is fixed to the surface projection area of ​​the multifidus muscle. In practical applications, a portable ultrasound device can be used, fixed to the corresponding segment (e.g., 2-3 cm lateral to the spinous processes of the 4th-5th lumbar vertebrae). The probe of the portable ultrasound device is stabilized by a strap or bracket to obtain signals showing the thickness changes of the multifidus muscle with contraction.

[0031] In addition to surface electromyography (EMG) modules such as EMG sensors and surface electrodes, and portable ultrasound devices, high-density EMG arrays, near-infrared spectrometers (NIRS), or muscle mechanoreceptors (such as accelerometers) can also be used as auxiliary signal sources to reflect the degree of contraction of multifidus muscles.

[0032] In some embodiments, the multifidus signal includes one of the electromyographic signal of the multifidus muscle and the thickness signal of the multifidus muscle; the activation level includes one of the RMS value of the electromyographic signal of the multifidus muscle and the percentage change in the thickness of the multifidus muscle. The RMS value (root mean square value) of the electromyographic signal is a key indicator reflecting the intensity of the muscle electrical signal and the level of muscle activity. It quantifies the overall energy characteristics of the electromyographic signal and is used to assess the degree of muscle activation, fatigue state and contraction intensity.

[0033] In some embodiments, the above-described rehabilitation training device based on multifidus muscle activation feedback further includes a preprocessing module connected to the signal acquisition module and the processor, used for pre-amplifying, filtering, and rectifying the multifidus muscle signal. In practical applications, the preprocessing module can be a signal amplifier, including a preamplifier, a filter, and a rectifier connected in sequence, used for pre-processing the multifidus muscle signal such as pre-amplification, filtering, and rectification, amplifying the weak electromyographic signal to a certain extent for subsequent processing, such as... Figure 2 As shown, each electrode channel is equipped with an amplifier module. Figure 2 The example uses only four electrodes and does not mean that this embodiment is only applicable to 4-channel surface electrodes.

[0034] In some embodiments, the signal acquisition module is further configured to: acquire multifidus muscle signals during pre-training of the target training movement before rehabilitation training for that movement; the processor is further configured to determine the target training zone based on the multifidus muscle signals during the pre-training movement. For example, before formal rehabilitation training, a therapist can guide the patient to complete a series of low-load, segmental lumbar and back movements, such as mild lumbar extension and slight anterior pelvic tilt. During this series of movements, the corresponding multifidus muscle signals are recorded simultaneously, and the session is stopped when the therapist confirms through palpation and the patient that "deep local force in the lumbar spine has been clearly felt without significant pain."

[0035] In some embodiments, the processor is used to determine the maximum value of the multifidus muscle signal during the pre-training action as the activation threshold, and to determine the target training interval based on the activation threshold. Specifically, the maximum value of the electromyographic value or thickness change value during the corresponding time period of the pre-training action is used as the activation threshold of the current patient's individualized multifidus muscle, and then 0.8 to 1 times the activation threshold is set as the target training interval.

[0036] In some embodiments, the processor is used to determine the average value of the multifidus muscle signal during the pre-training exercise as the activation threshold, and to determine the target training interval based on the activation threshold. Specifically, the average value of the electromyographic value or thickness change value during the corresponding time period of the pre-training exercise is used as the activation threshold of the current patient's individualized multifidus muscle, and then 0.8 to 1 times the activation threshold is set as the target training interval.

[0037] The activation threshold can also be determined using different strategies, such as the percentage of maximum voluntary contraction (e.g., 30–40% of the maximum contraction of the multifidus muscle); the target training range can also be dynamically adjusted according to the patient's fatigue level and pain status.

[0038] In some embodiments, the feedback signal includes at least one of visual, auditory, and vibration signals. The visual signal reflects the relationship between the activation level and the target training zone through an energy bar or color bar. For example, the activation level of the multifidus muscle is converted into visual feedback in real time, displaying an energy bar or color bar. When the activation level of the multifidus muscle is below the lower limit of the target training zone, it is gray and short; when it is above the lower limit, it turns green and increases in height. The auditory signal reflects the relationship between the activation level and the target training zone through prompts. For example, when the activation level remains below the lower limit of the target training zone for a specific duration (e.g., 2-3 seconds), a prompt sound is emitted to remind the patient to adjust their movements or reduce compensation; when the activation level stabilizes above the lower limit of the target training zone, a "pass" prompt is given. The vibration signal reflects the relationship between the activation level and the target training zone through vibration intensity. When the activation level is below the lower limit of the target training zone, a vibration signal is emitted; the greater the degree below the lower limit, the stronger the vibration signal, prompting the patient to adjust their movements or reduce compensation. Different tones can be played through headphones, tactile feedback can be provided by wearing a lumbar vibration belt, or simple feedback can be achieved using color-changing indicator lights, making it suitable for elderly patients with poor eyesight or difficulty viewing screens. In dynamic rehabilitation training, individualized activation thresholds are set based on the collected multifidus muscle signals, and a real-time feedback mechanism is constructed, which can effectively guide patients to maintain multifidus muscle activation within a preset target range.

[0039] In some embodiments, the rehabilitation training device based on multifidus muscle activation feedback further includes a display connected to a processor for displaying visual feedback signals such as the energy display bar or color display bar. It may also include a vibration belt worn around the waist and / or headphones. The display and processor can be integrated into a tablet computer, mobile phone, small dedicated server, or cloud server, allowing users to use it in hospital, community, or home environments.

[0040] In some embodiments, the processor is further configured to: record at least one of the following during rehabilitation training of the target training movement: activation level calculated in real time, duration of the target training movement, peak activation level, and percentage of time the activation level reaches the target training interval; and to sort different target training movements according to the recorded information to generate a target rehabilitation training plan. Figure 4As shown, on the one hand, the activation level of the multifidus muscle can be converted into a visual feedback signal in real time by displaying an energy bar on the screen; on the other hand, the activation level calculated in real time can be displayed synchronously by displaying a curve in real time to indicate the muscle contraction, so that the patient can adjust the force according to the displayed content, and achieve real-time feedback to guide the patient to inhibit superficial compensation during training.

[0041] In one example, when generating a target rehabilitation training program, the programs are ranked according to the percentage of time the activation level reaches the target training range. From multiple target training movements, the 2-3 most effective movements for the current patient are selected as priority training movements. Movements with a lower percentage of time reaching the target training range indicate significantly lower activation efficiency and can be temporarily excluded from early training. Furthermore, based on the priority training movements and the patient's current pain level, physical condition, and activation status, the number of sets, holding time, and training cycle for each training session can be determined, forming an individualized rehabilitation prescription as the target rehabilitation training program. This device also provides a setting interface for rehabilitation training programs, which, based on the user's settings for the number of sets, holding time, and training cycle for each training session for the priority movements, are used to generate a target rehabilitation training program along with the selected priority training movements. Through quantitative comparison of the multifidus muscle activation efficiency under different training movements, an effectiveness ranking of the movement library and the generation of individualized training prescriptions are established.

[0042] This embodiment addresses the problem that existing technologies cannot accurately monitor and guide patients to effectively activate the multifidus muscle in dynamic lumbar rehabilitation training. It proposes a lumbar strain rehabilitation training device based on multifidus muscle activation feedback. By collecting multifidus muscle signals and setting individualized activation thresholds for different patients, the activation level of the multifidus muscle is converted into easily understandable visual, vibration, or sound feedback in real time, realizing real-time biofeedback training. This guides patients to preferentially activate the deep multifidus muscle and inhibit superficial compensation during lumbar stability training such as the bridge pose, thus achieving precise and individualized training.

[0043] Example 2: The rehabilitation training process using the multifidus muscle activation feedback-based rehabilitation training device in the above embodiments includes: First, obtaining the activation signal of the multifidus muscle through a signal acquisition module; second, setting an individualized activation threshold based on the individual's effective activation level; then, monitoring the degree of multifidus muscle activation in real time during training and providing feedback to the patient in the form of graphics, colors, or sounds, so that while completing core stability movements, the patient can actively adjust their exertion to maintain multifidus muscle activation above the lower limit of the target training range determined by the activation threshold; finally, sorting the movement library according to the activation efficiency under different movements to provide a basis for developing individualized training prescriptions.

[0044] 1. Target muscle signal acquisition (1) Use surface electromyography sensors or multifidus surface electrodes, and attach them to the surface projection area of ​​the multifidus muscle according to the pre-designed anatomical landmarks (such as 2-3 cm lateral to the spinous processes of the 4th and 5th lumbar vertebrae); if necessary, palpation can be used to confirm the muscle location. As an alternative or supplementary option, a portable ultrasound device can be fixed to the segment corresponding to the muscle location, and the probe can be kept stable by a strap or bracket to obtain the signal of the multifidus muscle thickness changing with contraction, so that the acquired signal has good specificity and stability.

[0045] (2) The acquired signal is pre-amplified, filtered and rectified and then input into the data acquisition module - signal amplifier, and the processor calculates the activation level of the multifidus muscle in real time, such as the electromyographic RMS value or the percentage change in thickness.

[0046] 2. Individualized activation threshold setting (1) Before formal training, guide the current patient to complete a series of low-load, segmental lumbar and back movements, such as mild lumbar extension and slight anterior pelvic tilt. Simultaneously record the multifidus muscle signal. The therapist can confirm the state of "clearly feeling local force in the deep lumbar spine without significant pain" through palpation and the patient's subjective feeling, or determine the end time of this series of movements by setting a duration.

[0047] (2) Select the electromyographic value or thickness change value of the corresponding time period, and take the maximum value after repeated multiple times as the individualized activation threshold of the multifidus muscle of the patient; at the same time, 0.8 to 1 times the activation threshold can be set as the target training range.

[0048] 3. Real-time biofeedback training (1) Select lumbar stability training exercises suitable for the elderly, such as supine bridge, side bridge, and four-point kneeling contralateral extension. In practice, the training exercise options can be selected, and the therapist or patient can choose one or more target training exercises to form a set of exercises for training.

[0049] (2) During training, the processor converts the multifidus activation level into visual feedback in real time: for example, an energy bar or color bar is displayed on a tablet or computer screen. When the multifidus activation is below the threshold, the bar is gray or short; when it is above the threshold, it turns green and increases in height.

[0050] (3) Set sound or vibration feedback: when the activation level is below the threshold for a certain period of time (e.g., 2-3 seconds), a prompt sound is emitted to remind the patient to adjust the movement or reduce compensation; when the activation level is stable above the target training range, a pass prompt is given.

[0051] (4) During the training process, record the duration of each set of selected movements, the percentage of time to reach the target (the percentage of time that the activation level reaches the target training range), peak activation and other indicators.

[0052] 4. Ranking of motion library effectiveness and development of training prescriptions (1) Perform the above-mentioned real-time feedback rehabilitation training on several commonly used movements (such as bridge, single-leg bridge, four-point kneeling contralateral extension, standing hip hinge, etc.), and calculate the average activation level, peak activation level and target achievement time ratio of the multifidus muscle under each movement.

[0053] (2) Sort the movements according to the activation efficiency of the multifidus muscle, and select the 2-3 movements that are most effective for the patient as the priority training movements. Movements with significantly low activation efficiency can be temporarily excluded from early training. The activation efficiency of the multifidus muscle is reflected by the proportion of time to reach the target.

[0054] (3) Based on the patient’s pain level, physical strength and activation status, determine the number of sets, holding time and training cycle for each training session, or directly follow the set frequency of, for example, 2 to 3 times a week, 20 to 30 minutes each time, for 4 to 8 weeks, to form an individualized rehabilitation training prescription.

[0055] The rehabilitation training device based on multifidus muscle activation feedback in the above embodiments can bring the following beneficial effects: (1) Achieve accurate monitoring and real-time feedback of the multifidus muscle in the lumbar region: Multifidus muscle signals are collected by electrode placement or portable ultrasound, and the activation level is displayed in real time during dynamic training. This overcomes the problem of "not being able to see or feel accurately" in traditional training, enabling therapists and patients to clearly understand whether the target muscle is truly involved.

[0056] (2) Effectively inhibit superficial compensation and improve training quality: By setting individualized activation thresholds and providing prompts for insufficient activation of the multifidus muscle during training, patients are guided to actively adjust their movement patterns, reduce excessive reliance on superficial muscle groups such as the erector spinae, and enable training to truly act on key muscles for segmental stability.

[0057] (3) Improve the efficiency of a single training session and promote the rehabilitation process: In the limited training time, biofeedback helps patients enter the "correct exertion state" more quickly, increases the proportion of time to reach the target, and thus achieves better functional improvement and pain relief with the same or less training volume.

[0058] (4) Enhance patients’ self-management ability: Under the guidance of therapists, patients can gradually transition to a self-training mode. Patients can adjust their movements according to the prompts such as screen, sound, and vibration provided by the device. This helps to form a long-term self-training habit and reduce dependence on outpatient rehabilitation.

[0059] (5) Provide objective basis for individualized rehabilitation prescriptions: By recording data on the activation efficiency of multifidus muscle in different movements and multiple training sessions, therapists can select the most suitable combination of movements and training intensity for a particular patient based on quantitative indicators, thus achieving true "precision rehabilitation".

[0060] Example 3: This embodiment provides an application example of the rehabilitation training device based on multifidus muscle activation feedback described in the above embodiments.

[0061] (1) Surface electrodes are attached bilaterally at a distance of 2 cm from the spinous processes of the L4-L5 lumbar vertebrae (e.g. Figure 3 (As shown), connect to a portable electromyography (EMG) acquisition device.

[0062] (2) In the supine position, the patient performs a slight posterior pelvic tilt and a slight lifting of the waist off the bed surface, repeating the action multiple times (e.g., 5 times). The average value of the multifidus muscle RMS value is calculated and set as the activation threshold A, and 0.8A is set as the lower limit of the target training interval.

[0063] (3) When formally conducting rehabilitation training for the target training movements, the current patient performs the standard bridge movement: flexing the hip and knee, placing the soles of the feet on the bed, slowly raising the pelvis to a neutral position, holding for 5-10 seconds, and then slowly lowering it.

[0064] (4) The multifidus muscle activation energy display bar is displayed on the screen in real time: when the energy is below 0.8A, the energy display bar is short and gray; when the energy is above 0.8A, the energy display bar turns green and displays "meets the standard", and the time to meet the standard is recorded.

[0065] (5) In the initial training stage, patients often have significant tension in the erector spinae muscles and insufficient activation of the multifidus muscles. While the therapist verbally prompts them to "contract their lower abdomen and imagine the sides of the lumbar spine touching each other," the patients observe the changes in the energy display bar and gradually learn to relax the superficial muscles and increase the participation of the multifidus muscles. Example 4: Another embodiment of this application relates to an electronic device, including: at least one processor; and a memory communicatively connected to the at least one processor; wherein the memory stores instructions executable by the at least one processor, the instructions being executed by the at least one processor to enable the at least one processor to acquire multifidus muscle signals during rehabilitation training for a target training movement based on a signal acquisition module located on the surface projection area of ​​the multifidus muscle, calculate the activation level in real time, and output a feedback signal reflecting the relationship between the activation level and the target training zone.

[0066] In practical applications, the electronic device also integrates a display connected to the processor to display visual feedback signals such as the energy bar or color bar. The display and processor can be integrated into tablet computers, mobile phones, small dedicated hosts, or cloud servers, etc. Users can use it in hospital, community, or home environments. The electromyography device can be connected to tablet computers and other devices via Bluetooth or Wi-Fi, thereby realizing the rehabilitation training device based on multifidus muscle activation feedback in the above embodiments.

[0067] The memory and processor are connected via a bus, which can include any number of interconnecting buses and bridges, connecting various circuits of one or more processors and memories. The bus can also connect various other circuits, such as peripheral devices, voltage regulators, and power management circuits, which are well known in the art and will not be described further herein. The bus interface provides an interface between the bus and the transceiver. The transceiver can be a single element or multiple elements, such as multiple receivers and transmitters, providing a unit for communicating with various other devices over a transmission medium. Data processed by the processor is transmitted over the wireless medium via an antenna, which further receives data and transmits it to the processor.

[0068] The processor manages the bus and general processing, and also provides various functions, including timing, peripheral interfaces, voltage regulation, power management, and other control functions. Memory is used to store data used by the processor during operation.

[0069] Those skilled in the art will understand that the above embodiments are specific embodiments for implementing this application, and in practical applications, various changes can be made to them in form and detail without departing from the spirit and scope of this application.

Claims

1. A rehabilitation training device based on multifidus muscle activation feedback, characterized in that, include: The signal acquisition module is located on the surface projection area of ​​the multifidus muscle and is used to acquire multifidus muscle signals during rehabilitation training for targeted training movements. The processor, connected to the signal acquisition module, is used to calculate the activation level in real time based on the multifidus muscle signal and output a feedback signal reflecting the relationship between the activation level and the target training zone.

2. The rehabilitation training device based on multifidus muscle activation feedback according to claim 1, characterized in that, The signal acquisition module includes at least one of an electromyography (EMG) device and an ultrasound device; when the signal acquisition module includes an EMG device, the EMG device is attached to the surface projection area of ​​the multifidus muscle; when the signal acquisition module includes an ultrasound device, the ultrasound device is fixed to the surface projection area of ​​the multifidus muscle.

3. The rehabilitation training device based on multifidus muscle activation feedback according to claim 2, characterized in that, The multifidus muscle signal includes one of the electromyographic signal of the multifidus muscle and the thickness signal of the multifidus muscle; the activation level includes one of the electromyographic RMS value of the multifidus muscle and the percentage change in the thickness of the multifidus muscle.

4. The rehabilitation training device based on multifidus muscle activation feedback according to claim 1, characterized in that, It also includes a preprocessing module, which is connected to the signal acquisition module and the processor, for pre-amplifying, filtering and rectifying the multifidus muscle signal.

5. The rehabilitation training device based on multifidus muscle activation feedback according to claim 1, characterized in that, The signal acquisition module is also used to: acquire multifidus muscle signals during pre-training of the pre-training movement before performing rehabilitation training for the target training movement; the processor is also used to determine the target training interval based on the multifidus muscle signals during the pre-training movement.

6. The rehabilitation training device based on multifidus muscle activation feedback according to claim 5, characterized in that, The processor is used to determine the maximum value of the multifidus muscle signal during the pre-training action as the activation threshold, and to determine the target training interval based on the activation threshold.

7. The rehabilitation training device based on multifidus muscle activation feedback according to claim 5, characterized in that, The processor is used to determine the average value of the multifidus muscle signal during the pre-training action as the activation threshold, and to determine the target training interval based on the activation threshold.

8. The rehabilitation training device based on multifidus muscle activation feedback according to claim 1, characterized in that, The feedback signal includes at least one of visual signals, sound signals, and vibration signals; The visual signal reflects the relationship between the activation level and the target training range through an energy display bar or a color display bar; the sound signal reflects the relationship between the activation level and the target training range through prompt information; and the vibration signal reflects the relationship between the activation level and the target training range through vibration intensity.

9. The rehabilitation training device based on multifidus muscle activation feedback according to claim 1, characterized in that, The processor is also used to: record at least one of the following during rehabilitation training of the target training action: activation level, duration of the target training action, peak activation level, and percentage of time the activation level reaches the target training interval; and to sort different target training actions according to the recorded information to generate a target rehabilitation training plan.

10. An electronic device, characterized in that, include: At least one processor; as well as, A memory communicatively connected to the at least one processor; wherein, The memory stores instructions that can be executed by the at least one processor. The instructions are executed by the at least one processor to enable the at least one processor to acquire multifidus muscle signals during rehabilitation training for the target training movement based on a signal acquisition module located on the surface projection area of ​​the multifidus muscle, calculate the activation level in real time, and output a feedback signal reflecting the relationship between the activation level and the target training zone.

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