Evaluation method based on multi-channel surface electromyogram combined with MSS scoring

Abstract

The invention discloses an evaluation method based on multi-channel surface electromyography and MSS scoring, which comprises the following steps: an electromyographic signal acquisition step: arranging a plurality of surface electrodes on the upper limb of a patient to form an acquisition channel, and respectively and correspondingly monitoring a flexor muscle group and an extensor muscle group of a forearm; when the patient executes preset actions at least including fist clenching, finger stretching, wrist bending and wrist stretching, multi-channel surface electromyogram signals are synchronously collected; a signal processing step: preprocessing the electromyographic signals, and extracting electrophysiological feature parameters used for evaluating spasm states; and a function evaluation step: evaluating the upper limb motion function state of the patient based on the electrophysiological characteristic parameters, including performing conjoint analysis on the electrophysiological characteristic parameters and a motion function state scale (MSS) score to generate a comprehensive evaluation result. According to the method, sEMG parameters and MSS scores are combined, and the generated evaluation result not only maintains the objectivity of electrophysiological signals, but also has the interpretability of a clinical scale, and is more beneficial to guiding rehabilitation treatment.

Description

Technical Field

[0001] This invention relates to the field of electromyography (EMG) technology, and more particularly to an assessment method based on multi-channel surface EMG combined with MSS scoring. Background Technology

[0002] Stroke is one of the leading causes of disability in adults, and upper limb spasticity is a common sequela, severely affecting patients' motor function and quality of life. Currently, clinical assessment of spasticity mainly relies on subjective scales such as the Modified Ashworth Scale (MAS) or the Modified Tardieu Scale (MTS). While these methods are simple, they are easily influenced by the assessor's subjective experience, lack objective and quantitative indicators, and are difficult to accurately reflect the coordinated activity and functional status of multiple muscles.

[0003] Surface electromyography (sEMG), as a non-invasive neuromuscular function testing technique, can objectively reflect the electrophysiological activity of muscles. However, while a single sEMG parameter can provide objective data on muscle activity, it is often not directly correlated with the patient's overall motor function status, and its clinical interpretability needs to be strengthened. The Status Motor Function Scale (MSS) is a quantitative scale used in recent years to assess upper limb motor function, especially fine motor function of the hand, after stroke. Its assessment results have good clinical interpretability, but it still falls within the scope of subjective assessment.

[0004] Therefore, how to effectively combine objective sEMG signals with clinically significant MSS scores to form an assessment method that can both quantitatively analyze muscle activity and comprehensively reflect upper limb functional status has become a pressing technical problem in this field. Current technologies lack a systematic approach capable of simultaneously acquiring signals from multiple key muscle groups related to upper limb spasticity following stroke and performing in-depth fusion analysis with clinical functional scores. Summary of the Invention

[0005] To address at least one of the aforementioned technical problems, this invention provides an assessment method based on multi-channel surface electromyography combined with MSS scoring.

[0006] In a first aspect, the present invention provides an assessment method based on multichannel surface electromyography combined with MSS scoring, the method comprising: Electromyography (EMG) signal acquisition steps: Multiple surface electrodes are placed on the patient's upper limb to form acquisition channels, respectively corresponding to the monitoring of the flexor and extensor muscle groups of the forearm; multi-channel surface EMG signals are acquired simultaneously when the patient performs a predetermined action including at least fist clenching, finger extension, wrist flexion, and wrist extension. Signal processing steps: The electromyographic signals are preprocessed and electrophysiological characteristic parameters for assessing spasticity are extracted; Functional assessment steps: Based on the electrophysiological characteristic parameters, assess the patient's upper limb motor function status, including jointly analyzing the electrophysiological characteristic parameters with the Motor Function Status Scale (MSS) score to generate a comprehensive assessment result; the joint analysis includes fusing the electromyographic characteristic parameters and the MSS score according to predetermined rules to obtain a comprehensive index that quantitatively reflects the correlation between spasticity and function.

[0007] Preferably, in the electromyography signal acquisition step, the electrode channels arranged are 8 channels, respectively corresponding to the monitoring of the pronator teres, flexor carpi ulnaris, flexor carpi radialis, flexor pollicis longus, flexor digitorum superficialis, extensor carpi radialis, extensor digitorum commonis, and extensor pollicis longus.

[0008] Preferably, the electrophysiological characteristic parameters include at least two parameters selected from time-domain parameters, frequency-domain parameters, and muscle synergy parameters; The time-domain parameters include root mean square values ​​and integral electromyographic values; The frequency domain parameters include the median frequency and the average power frequency; The muscle synergy parameter includes the synergistic contraction ratio calculated based on the electromyographic values ​​of the agonist and antagonist muscles.

[0009] Preferably, the preprocessing includes bandpass filtering, noise reduction, baseline drift correction, and signal normalization.

[0010] Preferably, the predetermined rules include parameter comparison, level mapping, or weighted calculation.

[0011] Preferably, the functional evaluation step specifically includes: Collaborative pattern analysis sub-step: For the predetermined actions that include at least fist clenching, finger extension, wrist flexion, and wrist extension, calculate the activation intensity ratio or collaborative relationship of the muscles corresponding to multiple acquisition channels during the execution of the action, and generate collaborative pattern features; Functional correlation analysis sub-step: Correlation analysis is performed between the cooperative pattern characteristics and the scoring items of fine motor function of the hands in the MSS scale. Based on the degree to which the cooperative pattern characteristics deviate from the normal reference pattern, the functional impairment level of fine motor function of the hands is quantitatively assessed.

[0012] Preferably, the electromyography (EMG) signal acquisition step includes acquiring EMG signals under passive movement conditions; The signal processing steps include extracting electrophysiological characteristic parameters under passive motion conditions; The functional evaluation steps include: Sub-steps for differentiating between spasticity and contracture: Compare the differences in electrophysiological parameters of the antagonistic muscle under passive movement and at rest; If the resistance to joint movement increases and the electrophysiological characteristics of the antagonistic muscle are not significantly different from those at rest, it is determined that the condition is mainly contracture. If the resistance to joint movement increases and the electrophysiological parameters of the antagonistic muscle are significantly higher than those at rest, it is determined that the condition is mainly characterized by spasticity.

[0013] Preferably, the method is used to evaluate the efficacy of surgical treatment for upper limb spasticity; The electromyography signal acquisition step and the MSS score acquisition step were repeated before surgery, short postoperative period and postoperative follow-up period, respectively. The functional assessment steps include: comparing and analyzing the trends of changes in electrophysiological characteristic parameters and MSS scores before surgery, short postoperative period, and postoperative follow-up period.

[0014] Secondly, the present invention also provides an assessment system based on multi-channel surface electromyography combined with MSS scoring, the system comprising: The signal acquisition unit is used to perform the electromyography signal acquisition steps: multiple surface electrodes are arranged on the patient's upper limb to form acquisition channels, respectively corresponding to the monitoring of the flexor and extensor muscle groups of the forearm; when the patient performs a predetermined action including at least clenching the fist, extending the fingers, flexing the wrist, and extending the wrist, multi-channel surface electromyography signals are acquired simultaneously. The signal processing unit is used to perform the following signal processing steps: preprocessing the electromyographic signal and extracting electrophysiological characteristic parameters for assessing the spastic state; The functional assessment unit is used to perform the functional assessment steps: based on the electrophysiological characteristic parameters, assess the patient's upper limb motor function status, including jointly analyzing the electrophysiological characteristic parameters with the Motor Function Status Scale (MSS) score to generate a comprehensive assessment result; the joint analysis includes fusing the electromyographic characteristic parameters and the MSS score according to predetermined rules to obtain a comprehensive index that quantitatively reflects the correlation between spasticity and function.

[0015] Thirdly, the present invention also provides a computer-readable storage medium storing a computer program, the computer program including program instructions that, when executed by a processor of an electronic device, cause the processor to perform a method as described in the first aspect above and any possible implementation thereof.

[0016] Compared with the prior art, the beneficial effects of the present invention are as follows: This invention utilizes eight-channel sEMG to simultaneously monitor key muscle groups related to flexion, extension, and rotation, providing comprehensive coverage and overcoming the limitations of single-point monitoring or single-movement assessment. It employs multiple electrophysiological parameters, including RMS, iEMG, CR, MPF, and MF, to objectively quantify spasticity from multiple perspectives, including time domain, frequency domain, and coordination modes, reducing subjective bias. By combining objective sEMG parameters with the clinically widely accepted and sensitive MSS score for fine motor skills, the generated assessment results maintain the objectivity of electrophysiological signals while possessing the interpretability of clinical scales, thus facilitating the guidance of rehabilitation treatment. This method can be used for comparative assessment of spasticity function and efficacy tracking before and after rehabilitation intervention in stroke patients, providing a scientific basis for precise rehabilitation and personalized treatment plan development, and has significant clinical promotion and research application value.

[0017] It should be understood that the above general description and the following detailed description are exemplary and explanatory only, and are not intended to limit this disclosure. Attached Figure Description

[0018] To more clearly illustrate the technical solutions in the embodiments of the present invention or the background art, the accompanying drawings used in the embodiments of the present invention or the background art will be described below.

[0019] The accompanying drawings, which are incorporated in and form part of this specification, illustrate embodiments consistent with this disclosure and, together with the specification, serve to illustrate the technical solutions of this disclosure.

[0020] Figure 1 This is a schematic flowchart of an assessment method based on multi-channel surface electromyography combined with MSS scoring, provided in an embodiment of the present invention. Figure 2 This is a schematic diagram illustrating the design principle of the surface electromyography electrode pads provided in an embodiment of the present invention. Figure 3 This is a schematic diagram of the structure of an assessment system based on multi-channel surface electromyography combined with MSS scoring, provided in an embodiment of the present invention. Detailed Implementation

[0021] To enable those skilled in the art to better understand the present invention, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0022] The terms "first," "second," etc., used in the specification, claims, and accompanying drawings of this invention are used to distinguish different objects, not to describe a specific order. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover non-exclusive inclusion. For example, a process, method, system, product, or apparatus that includes a series of steps or units is not limited to the listed steps or units, but may optionally include steps or units not listed, or may optionally include other steps or units inherent to these processes, methods, products, or apparatuses.

[0023] In this document, the term "embodiment" means that a particular feature, structure, or characteristic described in connection with an embodiment may be included in at least one embodiment of the invention. The appearance of this phrase in various places throughout the specification does not necessarily refer to the same embodiment, nor is it a separate or alternative embodiment mutually exclusive with other embodiments. It will be explicitly and implicitly understood by those skilled in the art that the embodiments described herein can be combined with other embodiments.

[0024] Traditional assessments of upper limb spasticity after stroke primarily rely on clinical scales such as the Modified Ashworth Scale (MAS) and the Fugl-Meyer Assessment (FMA). However, these scales are inherently subjective, heavily dependent on the assessor's experience, and unable to quantify the neuromuscular electrophysiological activity underlying spasticity. For example, the MAS can only provide a rough grading of muscle tone, failing to distinguish between spasticity (excessive stretch reflex due to central nervous system injury) and contracture (structural shortening of soft tissue), and also failing to accurately reflect the patient's muscle recruitment and control during voluntary movement attempts. These limitations result in imprecise assessments, hindering the development of individualized rehabilitation or surgical plans and the objective quantification of treatment outcomes.

[0025] See Figure 1 To solve the above problems, Figure 1 This is a schematic flowchart illustrating an assessment method based on multi-channel surface electromyography combined with MSS scoring, provided as an embodiment of the present invention. Figure 1 As shown, the method includes: S10, Electromyography (EMG) signal acquisition steps: Multiple surface electrodes are placed on the patient's upper limb to form acquisition channels, respectively corresponding to the monitoring of the flexor and extensor muscle groups of the forearm; when the patient performs a predetermined action including at least clenching the fist, extending the fingers, flexing the wrist, and extending the wrist, multi-channel surface EMG signals are acquired simultaneously. S20, Signal processing step: Preprocess the electromyographic signal and extract electrophysiological characteristic parameters for assessing spasticity. S30. Functional assessment steps: Based on the electrophysiological characteristic parameters, assess the patient's upper limb motor function status, including jointly analyzing the electrophysiological characteristic parameters with the Motor Function Status Scale (MSS) score to generate a comprehensive assessment result; the joint analysis includes fusing the electromyographic characteristic parameters and the MSS score according to predetermined rules to obtain a comprehensive index that quantitatively reflects the correlation between spasticity and function.

[0026] Electromyography (EMG) signal acquisition steps: See Figure 2 In accordance with the relevant specifications for surface electromyography (EMG) assessment systems, surface electrodes are placed on specific muscle groups in the patient's upper limb. The patient is then instructed to perform a series of standardized, predetermined movements under specific commands, including clenching the fist, extending the fingers, flexing the wrist, and extending the wrist. The EMG signals from all channels are recorded simultaneously during the acquisition process to ensure temporal consistency of the data. This step aims to capture the electrical activity characteristics of spastic muscles under different states, including passive stretching, active contraction, and sustained movement.

[0027] Specifically, during data collection, electrodes were placed on the anterior and dorsal surfaces of the forearm (recording simultaneously). Subjects performed forearm pronation (pronator teres); wrist flexion (flexor carpi ulnaris and flexor carpi radialis); fist clenching (flexor pollicis longus and flexor digitorum superficialis); wrist extension (extensor carpi radialis); and finger extension (extensor digitorum commonis and extensor pollicis longus), for a total of three times. In the active task, subjects performed forearm pronation, wrist flexion, fist clenching, wrist extension, and finger extension, holding each movement with maximum effort for 1 minute. Each contraction was repeated three times, with a 60-second rest between each contraction to minimize fatigue. In the passive task, subjects were instructed to completely relax and perform passive movements of the wrist and finger joints (full range of motion), holding each movement for 1 second, with a 3-second interval between movements. Data from the first flexion-extension process was extracted for subsequent analysis.

[0028] Signal processing steps: The acquired raw sEMG signals are preprocessed to eliminate power line interference, motion artifacts, and baseline drift. Subsequently, key electrophysiological parameters are extracted from the purified signals. For example, surface electromyography (sEMG) of the forearm flexor and extensor muscle groups is recorded separately, and the root mean square (RMS) and integrated electromyography (iEMG) values ​​are analyzed. Time-domain parameters such as RMS and iEMG directly reflect the muscle activation level and overall electrical activity intensity.

[0029] Functional assessment steps: The extracted objective electrophysiological parameters (such as RMS, iEMG) are jointly analyzed with the subjective but systematic Motor Function Status Scale (MSS) scores. The MSS scale comprehensively assesses fine motor function from the shoulder to the fingers. Predetermined rules can include parameter comparison, ordinal mapping, or weighted calculation.

[0030] This embodiment overcomes the shortcomings of traditional scales, such as strong subjectivity and one-sidedness of single physiological parameters, by deeply integrating objective quantitative data from sEMG with detailed functional assessments from MSS. It can not only more accurately assess the severity of spasticity but also directly link the improvement of spasticity with the enhancement of actual motor function, providing unprecedented, comprehensive, and objective scientific evidence for clinical diagnosis, treatment planning, and efficacy evaluation.

[0031] In surface electromyography (EMG), arbitrary electrode placement can lead to poor data comparability. Incomplete or inaccurate muscle monitoring will fail to accurately reflect the complex synergistic and antagonistic relationships that cause wrist and finger spasticity. For example, monitoring only the wrist flexors while ignoring the pronator or finger flexors cannot explain the patient's possible abnormal "pronation-wrist flexion-finger flexion" synergistic pattern, affecting the accuracy of the assessment.

[0032] To achieve accurate assessment, in one embodiment, an 8-channel electrode arrangement was strictly defined to fully cover the core muscles of the forearm. Specifically, the electrodes were placed to correspond to the following muscles, with 8 electrode channels, respectively monitoring the pronator teres, flexor carpi ulnaris, flexor carpi radialis, flexor pollicis longus, flexor digitorum superficialis, extensor carpi radialis, extensor digitorum commonis, and extensor pollicis longus.

[0033] Pronator teres: Monitoring forearm pronation is crucial for assessing pronation spasticity.

[0034] Flexor carpi ulnaris and flexor carpi radialis: Activation of the ulnar and radial sides during wrist flexion was monitored to assess wrist flexion spasticity.

[0035] Flexor pollicis longus and flexor digitorum superficialis: These are key muscles for assessing spastic grasping of the hand, as they monitor the flexion of the thumb and the other four fingers.

[0036] Extensor carpi radialis: Monitors wrist extension. As an antagonist to the wrist flexor muscle group, its activation level can reflect the coordination between antagonist muscles.

[0037] Extensor digitorum commonis and extensor pollicis longus: monitor finger and thumb extension, assess finger extension function, and form an antagonistic pair with the flexor muscles.

[0038] During implementation, electrodes must be precisely attached to the muscle belly of the aforementioned muscles to ensure repeatability and comparability of each test. A standardized eight-channel arrangement ensures the systematic and repeatable nature of signal acquisition. It can simultaneously monitor the electrical activity of the major flexor, extensor, and rotator muscle groups of the forearm, providing a comprehensive and reliable raw data foundation for subsequent analysis of abnormal muscle synergy patterns and accurate differentiation between spasticity and contracture.

[0039] Traditional sEMG analysis often focuses on time-domain parameters (such as RMS), which only reflect muscle activation intensity and provide limited information. It cannot assess muscle fatigue (related to endurance) or the coordination patterns between different muscle groups (related to movement quality), information crucial for a comprehensive understanding of motor dysfunction in spastic patients. Therefore, in one embodiment, the electrophysiological parameters include at least two parameters selected from time-domain parameters, frequency-domain parameters, and muscle synergy parameters. The time-domain parameters include root mean square values ​​and integral electromyographic values; The frequency domain parameters include the median frequency and the average power frequency; The muscle synergy parameter includes the synergistic contraction ratio calculated based on the electromyographic values ​​of the agonist and antagonist muscles.

[0040] Temporal parameters: The root mean square (RMS) and integrated electromyography (iEMG) values ​​were mainly extracted. For example, during passive activity, the RMS value of the flexor muscles on the affected side was significantly higher than that on the healthy side and the normal value, directly quantifying the level of resting muscle tone; during active activity, the RMS value was significantly lower than that on the healthy side, reflecting a decrease in voluntary motor recruitment ability.

[0041] Frequency domain parameters: Median frequency (MF) and mean power frequency (MPF) are extracted. These parameters shift towards lower frequencies during sustained muscle contraction and are the gold standard for assessing muscle fatigue. Typically, the frequency domain of the flexor digitorum superficialis muscles changes when a patient clenches their fist continuously. By comparing the MF and MPF slopes of the affected side, the unaffected side, and normal subjects, the ease of muscle fatigue can be objectively assessed.

[0042] Muscle synergy parameters: The synergistic contraction rate (CR) is calculated using the formula: CR = antagonist IEMG / (agonist IEMG + antagonist IEMG) * 100%. Furthermore, during synergy testing, analyzing the activation ratio between the target agonist muscle and non-target muscles (such as antagonists and synergists) during specific movements (e.g., clenching a fist) can reveal abnormal synergistic movement patterns. For example, when a patient clenches their fist, their wrist extensor muscles (radial extensor carpi radialis) also show abnormally high activation, which is a typical spastic synergistic pattern.

[0043] This embodiment achieves a comprehensive assessment of the "strength, endurance, and coordination" of spastic muscle function through multi-dimensional parameter extraction. It not only answers the question of "how tense the muscle is," but also the crucial questions of "how long the muscle can sustain the tension" and "whether the coordination between muscles is normal," providing precise guidance for developing a comprehensive rehabilitation program that includes strength training, endurance training, and coordination training.

[0044] Raw sEMG signals are highly susceptible to various interferences, such as 50Hz power frequency interference, baseline drift caused by changes in skin impedance, and motion artifacts from the movement of other body parts. Without effective preprocessing, the extracted feature parameters will contain a large amount of noise, leading to distorted evaluation results and poor reliability. To ensure data quality, a rigorous preprocessing procedure is specified in one embodiment, including bandpass filtering, noise reduction, baseline drift correction, and signal normalization, all of which are automatically performed in the signal analysis software, as detailed below: Bandpass filtering (e.g., 10Hz-500Hz): preserves the effective frequency components of sEMG while eliminating low-frequency baseline drift and high-frequency noise.

[0045] Notch filtering (e.g., 50Hz notch filtering): specifically removes power frequency interference.

[0046] Denoising and baseline drift correction: Advanced algorithms (such as wavelet transform) are used to further smooth the signal and correct the baseline.

[0047] Signal standardization: This is a crucial step in ensuring comparability between individuals and data. Maximum voluntary contraction (MVC) standardization can be employed, requiring patients to complete a single contraction with maximum effort. The RMS value during this process is used as the 100% reference value, and all RMS values ​​collected in the test are expressed as a percentage of MVC (%MVC). This standardization process allows data from different patients and even different time points to be compared. This minimizes non-physiological interference, ensuring high comparability of data collected from different individuals and at different time points, providing high-quality data for accurate subsequent analysis and long-term efficacy tracking.

[0048] When conducting data analysis, objective sEMG parameters and subjective MSS scores are usually simply listed side by side, thus providing only scattered information. Clinicians still need to rely on their personal experience to make comprehensive judgments. The lack of a unified, quantitative conclusive indicator is not conducive to rapid decision-making and comparison of results between different cases or different medical institutions.

[0049] Therefore, in one embodiment, predetermined rules are defined to deeply fuse two types of data to generate a comprehensive evaluation result: the predetermined rules include parameter comparison, level mapping or weighted calculation.

[0050] Grade Mapping and Parameter Comparison: First, map sEMG parameters to spasticity grades. For example, passive activity RMS values ​​can be categorized as: 0-5uv (normal), 5-14uv (mild), 15-24uv (moderate), and >25uv (severe). Simultaneously, the total MSS score is categorized into functional grades (e.g., <30 points for severe impairment, 30-50 points for moderate impairment, etc.). Then, the spasticity grade is compared with the functional grade. If the severity matches (e.g., both are "severe"), it indicates that the functional impairment is primarily caused by spasticity; if the functional grade is significantly worse than the spasticity grade, it suggests the possible presence of other problems (e.g., sensory loss, cognitive impairment).

[0051] Weighted calculation to generate a comprehensive index: A more advanced rule is to perform weighted calculations. For example, define a "Spasticity-Function Index (SFI)": SFI = A * (1 - Postoperative passive RMS / Preoperative passive RMS) + B * (Postoperative MSS gain / Maximum possible gain). Where A and B are weighting coefficients (determined through regression analysis, e.g., A=0.6, B=0.4), and the maximum possible gain is (82 - Preoperative MSS score). The closer the index value is to 1, the better the therapeutic effect. It uses a single number to comprehensively reflect the degree of spasticity relief and functional recovery.

[0052] In addition, a comprehensive assessment index can be constructed, such as: Comprehensive improvement rate = (preoperative RMS - postoperative RMS) / preoperative RMS * W1 + (postoperative MSS - preoperative MSS) / (82 - preoperative MSS) * W2 (where W1 and W2 are weights set according to clinical importance), thereby generating a single, quantitative result to reflect the correlation between spasticity and function.

[0053] By employing predetermined data fusion rules, this embodiment condenses multi-dimensional assessment information into one or more easily interpretable comprehensive indicators. This greatly simplifies the clinical decision-making process, quantifies and standardizes assessment results, and facilitates large-scale clinical research, efficacy statistics, and medical quality control.

[0054] While the MSS scale can provide a detailed assessment of fine motor skills (such as finger interlocking and lateral pinching) ("whether or not it can be completed"), it cannot reveal the underlying neuromuscular control mechanisms ("why it cannot be completed"). Patients may be unable to complete the movements due to abnormal muscle coordination caused by spasticity, or they may be unable to complete them due to muscle weakness. Without knowing the root cause, rehabilitation training lacks specificity.

[0055] Therefore, in one embodiment, the focus is on using synergistic analysis of sEMG to dissect the root causes of fine motor dysfunction in the hand. Preferably, the functional assessment step specifically includes: Collaborative pattern analysis sub-step: For the predetermined actions that include at least fist clenching, finger extension, wrist flexion, and wrist extension, calculate the activation intensity ratio or collaborative relationship of the muscles corresponding to multiple acquisition channels during the execution of the action, and generate collaborative pattern features; Functional correlation analysis sub-step: Correlation analysis is performed between the cooperative pattern characteristics and the scoring items of fine motor function of the hands in the MSS scale. Based on the degree to which the cooperative pattern characteristics deviate from the normal reference pattern, the functional impairment level of fine motor function of the hands is quantitatively assessed.

[0056] Specifically, in the synergistic pattern analysis sub-step, patients are required to perform the corresponding fine motor skills on the MSS scale, such as "thumb against index fingertip." During this process, sEMG signals of eight muscles are recorded simultaneously, and the activation intensity ratio of each muscle is calculated. In the normal pattern, specific muscles such as the flexor pollicis longus and flexor digitorum superficialis should be primarily activated. However, spastic patients may exhibit abnormal synergistic pattern characteristics. For example, when attempting to counteract each other's fingers, the wrist flexors (flexor carpi ulnaris and radial carpi radialis) and finger flexors are over-activated simultaneously, causing the hand to clench into a fist and making it impossible to complete the counteracting action.

[0057] The functional correlation analysis sub-step involves performing a correlation analysis between the aforementioned abnormal synergistic pattern characteristics and the corresponding hand scoring items on the MSS scale (such as the "thumb against index finger pad" score). This allows for the quantification of the degree of abnormality; for example, "synergistic deviation" can be defined as the integral of the deviation between the activation intensity of the abnormal synergistic muscles and the normal reference value. Based on this deviation, the functional impairment level of this fine motor skill can be quantitatively assessed. The goal of treatment is not only to improve the patient's "score" but also to normalize their muscle synergistic pattern.

[0058] This embodiment moves the evaluation from "outcome assessment" to "mechanism diagnosis," enabling precise identification of specific abnormal muscle activity patterns that lead to fine motor dysfunction. This provides rehabilitation therapists with clear treatment targets, allowing them to design more targeted rehabilitation training programs (such as inhibiting abnormal synergy and promoting selective movement), thereby fundamentally improving hand function.

[0059] Clinically, manual examination alone (such as the modified Ashworth scale) is insufficient to distinguish whether limited joint range of motion is due to spasticity (dynamic, reversible) caused by central nervous system injury, or contracture (static, structural) caused by long-term soft tissue shortening. The treatment strategies for these two conditions are drastically different (the former focuses on neuromodulation such as medication and nerve blocks, while the latter focuses on traction, bracing, or even surgical release), and misdiagnosis can lead to ineffective or even harmful treatment.

[0060] Therefore, this embodiment mainly utilizes the characteristics of sEMG under passive movement for accurate identification. Specifically, the electromyography signal acquisition step includes acquiring electromyography signals under passive movement conditions; The signal processing steps include extracting electrophysiological characteristic parameters under passive motion conditions; The functional evaluation steps include: Sub-steps for differentiating between spasticity and contracture: Compare the differences in electrophysiological parameters of the antagonistic muscle under passive movement and at rest; If the resistance to joint movement increases and the electrophysiological characteristics of the antagonistic muscle are not significantly different from those at rest, it is determined that the condition is mainly contracture. If the resistance to joint movement increases and the electrophysiological parameters of the antagonistic muscle are significantly higher than those at rest, it is determined that the condition is mainly characterized by spasticity.

[0061] In this embodiment, with the patient's muscles completely relaxed, the examiner passively moves the patient's wrist or finger joints at a standard speed (passive movement: 1 second of passive movement of the entire joint followed by 1 second of rest). During this process, electromyographic signals are collected during passive movement, and electrophysiological characteristic parameters (such as RMS values) of the antagonist muscles (e.g., wrist flexor muscles during passive wrist extension) are extracted. If the examiner feels increased joint movement resistance, but sEMG shows no significant difference in the RMS value of the antagonist muscles compared to the resting state, remaining at a low level (e.g., <10uv), this indicates that the resistance mainly originates from the physical shortening of soft tissues such as muscles and tendons, rather than neuroreflexive contraction. "When the joint resistance measured by passive stretching increases, but the electromyographic signal of the antagonist muscles shows no significant difference compared to the resting state, it is a contracture." Therefore, contracture is determined to be the primary cause in this case. If the joint movement resistance increases, and sEMG shows that the RMS value of the antagonist muscles is significantly higher than the resting state (e.g., from 5uv at rest to 30uv during passive stretching), this indicates that the resistance mainly originates from involuntary muscle contraction caused by hyperextension of the stretch reflex. Since "the electromyographic signal is significantly increased, which indicates spasm," the condition is determined to be primarily spasm.

[0062] This embodiment provides an objective and quantitative diagnostic tool that solves a major problem in clinical practice. It can clearly guide clinicians to choose the correct treatment direction, avoid ineffective use of antispasmodic drugs for patients with contractures, or inappropriate forceful traction on patients with contractures, thereby achieving precision medicine, improving treatment efficiency, and reducing patient suffering.

[0063] Assessing the efficacy of surgical treatments (such as T1 root resection) requires multidimensional, long-term objective evidence. Assessments at a single time point or relying solely on scales cannot fully reveal the immediate and long-term effects of surgery on neuromuscular function, and it is difficult to answer key questions such as "Did the surgery truly reduce spasticity?", "Did it affect useful muscle strength?", and "Is the functional improvement lasting?".

[0064] Therefore, the assessment method based on multi-channel surface electromyography combined with MSS score provided in this embodiment of the invention can be used to evaluate the efficacy of surgical treatment for upper limb spasticity. The electromyography signal acquisition step and the MSS score acquisition step were repeated before surgery, short postoperative period and postoperative follow-up period, respectively. The functional assessment steps include: comparing and analyzing the trends of changes in electrophysiological characteristic parameters and MSS scores before surgery, short postoperative period, and postoperative follow-up period.

[0065] Specifically, this can be achieved through the following steps when applying it: Multi-time point data collection: At three key time points—preoperatively, shortly after surgery (e.g., 2 weeks), and during the postoperative follow-up period (e.g., an average of 6.3 months)—the electromyography signal acquisition steps and MSS score acquisition steps were strictly repeated according to a unified standard.

[0066] Comparative Analysis and Trend Interpretation: A systematic comparative analysis of data from three time points is conducted, focusing on their changing trends. sEMG parameter trends: Passive activity RMS / iEMG: Values ​​at 2 weeks post-operation and during follow-up were significantly lower than pre-operation values ​​(e.g., RMS decreased from 29.6uv to 8.7uv), indicating that the surgery successfully reduced static muscle tone (relieving spasm).

[0067] Active movement RMS / iEMG: decreased slightly 2 weeks postoperatively, but no significant reduction was observed during follow-up compared to preoperative levels. This indicates that the surgery effectively reduced abnormal tension while preserving the muscle recruitment capacity required for voluntary movement.

[0068] MSS score trend: The total MSS score continued to improve significantly from preoperative to 2 weeks postoperatively and then to the follow-up period, proving that motor function was substantially and continuously improved as spasticity was relieved and rehabilitation progressed.

[0069] Trends in range of motion (ROM): Objective indicators such as wrist joint range of motion also improved postoperatively.

[0070] This embodiment provides a complete closed loop for efficacy assessment, dynamically and comprehensively demonstrating the effects of surgical intervention. It not only confirms the direct effect of surgery in relieving spasticity but also assesses the long-term impact on useful muscle strength and functional recovery, providing a strong chain of scientific evidence for optimizing surgical plans, developing postoperative rehabilitation programs, and determining long-term efficacy.

[0071] See Figure 3 In one embodiment, the present invention also provides an assessment system based on multi-channel surface electromyography combined with MSS scoring, the system comprising: The signal acquisition unit 100 is used to perform the electromyography signal acquisition steps: multiple surface electrodes are arranged on the patient's upper limb to form acquisition channels, respectively corresponding to the monitoring of the flexor and extensor muscle groups of the forearm; when the patient performs a predetermined action including at least clenching the fist, extending the fingers, flexing the wrist, and extending the wrist, multi-channel surface electromyography signals are acquired simultaneously. The signal processing unit 200 is used to perform the following signal processing steps: preprocessing the electromyographic signal and extracting electrophysiological characteristic parameters for assessing the spastic state; The functional assessment unit 300 is used to perform the functional assessment steps: based on the electrophysiological characteristic parameters, assess the patient's upper limb motor function status, including jointly analyzing the electrophysiological characteristic parameters with the Motor Function Status Scale (MSS) score to generate a comprehensive assessment result; the joint analysis includes fusing the electromyographic characteristic parameters and the MSS score according to predetermined rules to obtain a comprehensive index that quantitatively reflects the correlation between spasticity and function.

[0072] It is understood that the system provided in this embodiment has functions or includes modules that can be used to execute the methods described in the above method embodiments. The specific implementation can be referred to the description of the above method embodiments, and for the sake of brevity, it will not be repeated here.

[0073] The present invention also provides a computer-readable storage medium storing a computer program, the computer program including program instructions that, when executed by a processor of an electronic device, cause the processor to perform a method as described in any of the above possible implementations.

[0074] Those skilled in the art will recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementations should not be considered beyond the scope of this invention.

Claims

1. An evaluation method based on multi-channel surface electromyography combined with MSS score, characterized in that, The method comprises: A myoelectric signal acquisition step: arranging a plurality of surface electrodes on the upper limbs of a patient to form acquisition channels, respectively corresponding to monitoring the flexor group and the extensor group of the forearm; synchronously acquiring multi-channel surface myoelectric signals when the patient performs predetermined actions including at least clenched fist, extended fingers, wrist flexion, and wrist extension; A signal processing step: pre-processing the myoelectric signals and extracting electrophysiological characteristic parameters for evaluating the spasticity state; A function evaluation step: evaluating the upper limb motor function state of the patient based on the electrophysiological characteristic parameters, including jointly analyzing the electrophysiological characteristic parameters and the motor function state scale MSS score to generate a comprehensive evaluation result; the joint analysis includes fusing the myoelectric characteristic parameters and the MSS score through a predetermined rule to obtain a comprehensive index quantitatively reflecting the correlation between spasticity and function.

2. The method of claim 1, wherein the method is based on multi-channel surface electromyography combined with MSS score. In the myoelectric signal acquisition step, the arranged electrode channels are 8 channels, respectively corresponding to monitoring the pronator teres muscle, the flexor carpi ulnaris muscle, the flexor carpi radialis muscle, the long flexor muscle of the thumb, the superficial flexor muscle of the fingers, the extensor carpi radialis muscle, the extensor digitorum communis muscle, and the extensor longus muscle of the thumb.

3. The method of claim 1, wherein the method is based on multi-channel surface electromyography combined with MSS score. The electrophysiological characteristic parameters include at least two parameters selected from time domain parameters, frequency domain parameters, and muscle synergy parameters; The time domain parameters include root mean square value and integrated myoelectric value; The frequency domain parameters include median frequency and average power frequency; The muscle synergy parameter includes a synergistic contraction ratio calculated based on the myoelectric values of the agonist and the antagonist muscles.

4. The method of claim 1, wherein the method is based on multi-channel surface electromyography combined with MSS score. The pre-processing includes band-pass filtering, denoising, baseline drift correction, and signal standardization.

5. The method of claim 1, wherein, The predetermined rule includes parameter comparison, grade mapping, or weighted calculation.

6. The method of claim 1, wherein, The function evaluation step specifically includes: A synergistic mode analysis sub-step: for the predetermined actions including at least clenched fist, extended fingers, wrist flexion, and wrist extension, the activation intensity proportion or synergistic relationship of the muscles corresponding to the plurality of acquisition channels during action execution is calculated respectively, generating a synergistic mode feature; A function correlation analysis sub-step: correlating the synergistic mode feature with the score items in the MSS scale for hand fine motor function, quantitatively evaluating the dysfunction grade of hand fine motor function based on the degree of deviation of the synergistic mode feature from the normal reference mode.

7. The method of claim 1, wherein the method is based on multi-channel surface electromyography combined with MSS score. The myoelectric signal acquisition step includes acquiring myoelectric signals in a passive motion state; The signal processing step includes extracting electrophysiological characteristic parameters in a passive motion state; The function evaluation step includes: A spasm and contracture differentiation sub-step: comparing the electrophysiological characteristic parameters of the antagonist muscle in the passive motion state with the parameter difference in the resting state; If the joint activity resistance increases, and the electrophysiological characteristic parameters of the antagonist muscle have no significant difference compared with the resting state, it is determined that contracture is dominant; If the joint activity resistance increases, and the electrophysiological characteristic parameters of the antagonist muscle are significantly higher than those in the resting state, it is determined that spasm is dominant.

8. The method of claim 1, wherein the method is based on multi-channel surface electromyography combined with MSS score. The method is used for evaluating the efficacy of surgical treatment on upper limb spasticity; The myoelectric signal acquisition step and the MSS score acquisition step are repeatedly performed before surgery, in the short term after surgery, and in the follow-up period after surgery, respectively; The function evaluation step includes: comparative analysis of the change trends of the electrophysiological characteristic parameters and the MSS score before surgery, in the short term after surgery, and in the follow-up period after surgery.

9. An evaluation system based on multi-channel surface electromyography combined with MSS score, characterized in that, The system comprises: The signal acquisition unit is configured to perform an electromyography signal acquisition step, including: arranging a plurality of surface electrodes on an upper limb of a patient to form acquisition channels, respectively corresponding to monitoring flexor and extensor muscle groups of a forearm; and synchronously acquiring multi-channel surface electromyography signals when the patient performs predetermined actions including at least clenching a fist, extending a finger, bending a wrist, and extending a wrist. The signal processing unit is configured to perform a signal processing step, including: pre-processing the electromyography signals, and extracting electrophysiological characteristic parameters for evaluating a spasticity state. The function evaluation unit is configured to perform a function evaluation step, including: evaluating a motor function state of the upper limb of the patient based on the electrophysiological characteristic parameters, including: jointly analyzing the electrophysiological characteristic parameters and a motor function state scale MSS score to generate a comprehensive evaluation result; and the joint analysis includes fusing the electromyography characteristic parameters and the MSS score through a predetermined rule to obtain a comprehensive index quantitatively reflecting a correlation between spasticity and function.

10. A computer-readable storage medium, characterized in that, The computer readable storage medium stores a computer program, and the computer program includes program instructions. When the program instructions are executed by a processor of an electronic device, the processor performs the evaluation method based on multi-channel surface electromyography combined with an MSS score according to any one of claims 1 to 8.

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