肌电描记器:肌电信号的自动获取和处理:在步态障碍评估的临床背景下的首次实验

N. Ielpo, B. Calabrese, M. Cannataro, A. Palumbo, S. Ciliberti, C. Grillo, M. Iocco
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引用次数: 6

摘要

在物理医学和康复的背景下,步态分析是有效评估运动模式问题的“金标准”。表面肌电图是步态分析协议中的检查之一,允许对行走功能限制进行评估。考虑到卡坦扎罗大学的物理医学和康复科,医生们仅限于对来自下肢肌肉的肌电图信号进行视觉分析,以提取诊断和监测治疗的有用信息。这项工作的目的是为专家提供一个简单而灵活的系统,允许从肌电信号中提取时间和频域的定量合成参数,特别是我们提出了一种新的肌电数据采集和处理系统,称为肌电miner,它允许沿患者康复过程(随访)的不同阶段自动采集和分析肌电信号。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
EMG-Miner: Automatic Acquisition and Processing of Electromyographic Signals: First Experimentation in a Clinical Context for Gait Disorders Evaluation
In the context of physical medicine and rehabilitation, gait analysis is the "gold standard" for an effective assessment of any problems in the locomotor patterns. Surface electromyography is one of the exams within the protocol of the gait analysis, allowing an assessment of functional limitations in the walking. Considering the Physical Medicine and Rehabilitation Unit of the University of Catanzaro, physicians are limited to a visual analysis of the electromyographic signals coming from the muscles of the lower limbs, to extract useful information for diagnosis and monitoring of treatment. The objective of this work is to provide to specialists a simple and flexible system that allows the extraction of quantitative synthetic parameters in time and frequency domain from EMG signals, in particular we propose a novel EMG data acquisition and processing system, referred as EMG-Miner, that allows the automated acquisition and analysis of EMG signals along the different stages of the rehabilitation process (follow-up) of a patient.
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