首页|期刊导航|机械制造与自动化|基于生物阻抗谱的肌张力障碍程度评价研究

基于生物阻抗谱的肌张力障碍程度评价研究OA

Evaluation on Muscle Tone Disorder Degree Based on Bioimpedance Spectroscopy

中文摘要英文摘要

提出一种基于生物阻抗谱的肌张力程度识别方法,解决临床中肌张力评估的难题.针对肱二头肌、肱三头肌、腓肠肌,运用IM3570 阻抗分析仪测量各部位的生物阻抗谱,发现肌张力的弛豫阻抗显著小于正常部位的弛豫阻抗值,以患者 1 为例,其肌张部位的弛豫阻抗为 30~50、正常部位的阻抗为 50~100.最后搭建等效电路模型,这个等效电路对应了目标部位的不同生物组织,将前面测到的阻抗谱输入等效电路模型中,提取出关键电学特征参数:细胞内电阻(Ri)、细胞外电阻(Re)和细胞膜电容(Cm).使用提取到的参数对有无肌张力进行了分类,分类结果的准确度可达94.7%.该方法有望用于肌张力的等级分类评估中.

This paper proposes a method for identifying muscle tone disorders based on bioimpedance spectroscopy,which addresses the challenge of classifying muscle tone in clinical practice.With the focus on the biceps brachii,triceps brachii and gastrocnemius muscles,the bioimpedance spectra of these muscle groups were measured using the IM3570 impedance analyzer,disclosing that the relaxation impedance of muscle tone-affected areas was significantly lower than that of normal areas.In the case of patient 1,the relaxation impedance of the muscle tone-affected area was 30-50,while the impedance of the normal area was 50-100.An equivalent circuit model was constructed,which corresponds to the different biological tissues of the target areas.The measured impedance spectra were input into the equivalent circuit model to extract key electrical characteristic parameters:intracellular resistance(Ri),extracellular resistance(Re),and cell membrane capacitance(Cm).Using these extracted parameters,muscle tone presence or absence was classified with an accuracy rate of up to 94.7%.The proposed method holds promise for the classification and assessment of muscle tone levels.

曾兰婷;洪子文;蔡可书;孙婉婷;马姝玥;刘铭洁;许光旭

南京医科大学 康复医学院,江苏 南京 210029南京航空航天大学 机电学院,南京 211106南京医科大学第一附属医院康复医学中心,江苏 南京 211112南京医科大学 康复医学院,江苏 南京 210029南京医科大学 康复医学院,江苏 南京 210029南京医科大学 康复医学院,江苏 南京 210029南京医科大学 康复医学院,江苏 南京 210029||南京医科大学第一附属医院康复医学中心,江苏 南京 211112||南京医科大学附属苏州医院,江苏 苏州 215031

信息技术与安全科学

生物阻抗谱方法IM3570 实验平台搭建等效电路模型搭建临床应用发展趋势

bioimpedance spectroscopy methodIM3570 experimental platform constructionequivalent circuit model constructionclinical applicationdevelopment trend

《机械制造与自动化》 2026 (1)

207-212,6

国家自然科学基金面上项目(62271251)江苏省卫生健康发展研究中心开放课题(JSHD2021003)

10.19344/j.cnki.issn1671-5276.2026.01.039

评论