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Classifier Level Fusion of Accelerometer and sEMG Signals for Automatic Fitness Activity Diarization
The human activity diarization using wearable technologies is one of the most important supporting techniques for ambient assisted living, sport and fitness activities, healthcare of elderly people. The activity diarization is performed in two steps: the acquisition of body signals and the classific...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6164365/ https://www.ncbi.nlm.nih.gov/pubmed/30158443 http://dx.doi.org/10.3390/s18092850 |
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author | Biagetti, Giorgio Crippa, Paolo Falaschetti, Laura Turchetti, Claudio |
author_facet | Biagetti, Giorgio Crippa, Paolo Falaschetti, Laura Turchetti, Claudio |
author_sort | Biagetti, Giorgio |
collection | PubMed |
description | The human activity diarization using wearable technologies is one of the most important supporting techniques for ambient assisted living, sport and fitness activities, healthcare of elderly people. The activity diarization is performed in two steps: the acquisition of body signals and the classification of activities being performed. This paper presents a technique for data fusion at classifier level of accelerometer and sEMG signals acquired by using a low-cost wearable wireless system for monitoring the human activity when performing sport and fitness activities, as well as in healthcare applications. To demonstrate the capability of the system of diarizing the user’s activities, data recorded from a few subjects were used to train and test the automatic classifier for recognizing the type of exercise being performed. |
format | Online Article Text |
id | pubmed-6164365 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-61643652018-10-10 Classifier Level Fusion of Accelerometer and sEMG Signals for Automatic Fitness Activity Diarization Biagetti, Giorgio Crippa, Paolo Falaschetti, Laura Turchetti, Claudio Sensors (Basel) Article The human activity diarization using wearable technologies is one of the most important supporting techniques for ambient assisted living, sport and fitness activities, healthcare of elderly people. The activity diarization is performed in two steps: the acquisition of body signals and the classification of activities being performed. This paper presents a technique for data fusion at classifier level of accelerometer and sEMG signals acquired by using a low-cost wearable wireless system for monitoring the human activity when performing sport and fitness activities, as well as in healthcare applications. To demonstrate the capability of the system of diarizing the user’s activities, data recorded from a few subjects were used to train and test the automatic classifier for recognizing the type of exercise being performed. MDPI 2018-08-29 /pmc/articles/PMC6164365/ /pubmed/30158443 http://dx.doi.org/10.3390/s18092850 Text en © 2018 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Biagetti, Giorgio Crippa, Paolo Falaschetti, Laura Turchetti, Claudio Classifier Level Fusion of Accelerometer and sEMG Signals for Automatic Fitness Activity Diarization |
title | Classifier Level Fusion of Accelerometer and sEMG Signals for Automatic Fitness Activity Diarization |
title_full | Classifier Level Fusion of Accelerometer and sEMG Signals for Automatic Fitness Activity Diarization |
title_fullStr | Classifier Level Fusion of Accelerometer and sEMG Signals for Automatic Fitness Activity Diarization |
title_full_unstemmed | Classifier Level Fusion of Accelerometer and sEMG Signals for Automatic Fitness Activity Diarization |
title_short | Classifier Level Fusion of Accelerometer and sEMG Signals for Automatic Fitness Activity Diarization |
title_sort | classifier level fusion of accelerometer and semg signals for automatic fitness activity diarization |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6164365/ https://www.ncbi.nlm.nih.gov/pubmed/30158443 http://dx.doi.org/10.3390/s18092850 |
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