EMG-Miner: Automatic Acquisition and Processing of Electromyographic Signals: First Experimentation in a Clinical Context for Gait Disorders Evaluation

التفاصيل البيبلوغرافية
العنوان: EMG-Miner: Automatic Acquisition and Processing of Electromyographic Signals: First Experimentation in a Clinical Context for Gait Disorders Evaluation
المؤلفون: S. Ciliberti, Barbara Calabrese, Mario Cannataro, C. Grillo, M. Iocco, Nicola Ielpo, A. Palumbo
المصدر: CBMS
بيانات النشر: IEEE, 2014.
سنة النشر: 2014
مصطلحات موضوعية: medicine.medical_specialty, Signal processing, Rehabilitation, medicine.diagnostic_test, Computer science, Speech recognition, medicine.medical_treatment, Context (language use), Electromyography, Physical medicine and rehabilitation, Data acquisition, Gait analysis, Frequency domain, medicine, Detection theory
الوصف: 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.
URL الوصول: https://explore.openaire.eu/search/publication?articleId=doi_________::b2c4abbc1be88ebf3b4c31c5b32a0834
https://doi.org/10.1109/cbms.2014.41
رقم الأكسشن: edsair.doi...........b2c4abbc1be88ebf3b4c31c5b32a0834
قاعدة البيانات: OpenAIRE