loading
Papers Papers/2022 Papers Papers/2022

Research.Publish.Connect.

Paper

Paper Unlock

Authors: Ana Pereira 1 ; Duarte Folgado 1 ; Ricardo Cotrim 2 and Inês Sousa 1

Affiliations: 1 Associaç ão Fraunhofer Portugal Research, Rua Alfredo Allen 455/461, Porto, Portugal ; 2 Plux Wireless Biosignals S. A., Avenida 5 Outubro 70, 1050-59, Lisboa, Portugal

Keyword(s): Physiotherapy, Inertial Sensors, Electromyography, Body Area Networks, Automatic Segmentation.

Abstract: The efficacy of home-based physiotherapy depends on the correct and systematic execution of prescribed exercises. Biofeedback systems enable to accurately track exercise execution and prevent patients from unconsciously introduce incorrect postures or improper muscular loads on the prescribed exercises. This is often achieved using inertial and surface electromyography (sEMG) sensors, as they can be used to monitor human motion variables and muscular activation. In this work, we propose to use machine learning techniques to automatically assess if a given exercise was properly executed. We present two major contributions: (1) a novel sEMG segmentation algorithm based on a syntactic approach and (2) a feature extraction and classification pipeline. The proposed methodology was applied to a controlled laboratory trial, for a set of 3 different exercises often prescribe by physiotherapists. The findings of this study support it is possible to automatically segment and classify exercise repetitions according to a given set of common deviations. (More)

CC BY-NC-ND 4.0

Sign In Guest: Register as new SciTePress user now for free.

Sign In SciTePress user: please login.

PDF ImageMy Papers

You are not signed in, therefore limits apply to your IP address 3.144.243.184

In the current month:
Recent papers: 100 available of 100 total
2+ years older papers: 200 available of 200 total

Paper citation in several formats:
Pereira, A.; Folgado, D.; Cotrim, R. and Sousa, I. (2019). Physiotherapy Exercises Evaluation using a Combined Approach based on sEMG and Wearable Inertial Sensors. In Proceedings of the 12th International Joint Conference on Biomedical Engineering Systems and Technologies (BIOSTEC 2019) - BIOSIGNALS; ISBN 978-989-758-353-7; ISSN 2184-4305, SciTePress, pages 73-82. DOI: 10.5220/0007391300730082

@conference{biosignals19,
author={Ana Pereira. and Duarte Folgado. and Ricardo Cotrim. and Inês Sousa.},
title={Physiotherapy Exercises Evaluation using a Combined Approach based on sEMG and Wearable Inertial Sensors},
booktitle={Proceedings of the 12th International Joint Conference on Biomedical Engineering Systems and Technologies (BIOSTEC 2019) - BIOSIGNALS},
year={2019},
pages={73-82},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0007391300730082},
isbn={978-989-758-353-7},
issn={2184-4305},
}

TY - CONF

JO - Proceedings of the 12th International Joint Conference on Biomedical Engineering Systems and Technologies (BIOSTEC 2019) - BIOSIGNALS
TI - Physiotherapy Exercises Evaluation using a Combined Approach based on sEMG and Wearable Inertial Sensors
SN - 978-989-758-353-7
IS - 2184-4305
AU - Pereira, A.
AU - Folgado, D.
AU - Cotrim, R.
AU - Sousa, I.
PY - 2019
SP - 73
EP - 82
DO - 10.5220/0007391300730082
PB - SciTePress