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PLHI-MC10: A dataset of exercise activities captured through a triple synchronous medically-approved sensor
Most human activity recognition datasets that are publicly available have data captured by using either smartphones or smartwatches, which are usually placed on the waist or the wrist, respectively. These devices obtain one set of acceleration and angular velocity in the x-, y-, and z-axis from the...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8397882/ https://www.ncbi.nlm.nih.gov/pubmed/34485637 http://dx.doi.org/10.1016/j.dib.2021.107287 |
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author | Mahajan, Yohan Bhimireddy, Ananth Abid, Areeba Gichoya, Judy W. Purkayastha, Saptarshi |
author_facet | Mahajan, Yohan Bhimireddy, Ananth Abid, Areeba Gichoya, Judy W. Purkayastha, Saptarshi |
author_sort | Mahajan, Yohan |
collection | PubMed |
description | Most human activity recognition datasets that are publicly available have data captured by using either smartphones or smartwatches, which are usually placed on the waist or the wrist, respectively. These devices obtain one set of acceleration and angular velocity in the x-, y-, and z-axis from the accelerometer and the gyroscope planted in these devices. The PLHI-MC10 dataset contains data obtained by using 3 BioStamp nPoint® sensors from 7 physically healthy adult test subjects performing different exercise activities. These sensors are the state-of-the-art biomedical sensors manufactured by MC10. Each of the three sensors was attached to the subject externally on three muscles-Extensor Digitorum (Posterior Forearm), Gastrocnemius (Calf), and Pectoralis (Chest)-giving us three sets of 3 axial acceleration, two sets of 3 axial angular velocities, and 1 set of voltage values from the heart. Using three different sensors instead of a single sensor improves precision. It helps distinguish between human activities as it simultaneously captures the movement and contractions of various muscles from separate parts of the human body. Each test subject performed five activities (stairs, jogging, skipping, lifting kettlebell, basketball throws) in a supervised environment. The data is cleaned, filtered, and synced. |
format | Online Article Text |
id | pubmed-8397882 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Elsevier |
record_format | MEDLINE/PubMed |
spelling | pubmed-83978822021-09-02 PLHI-MC10: A dataset of exercise activities captured through a triple synchronous medically-approved sensor Mahajan, Yohan Bhimireddy, Ananth Abid, Areeba Gichoya, Judy W. Purkayastha, Saptarshi Data Brief Data Article Most human activity recognition datasets that are publicly available have data captured by using either smartphones or smartwatches, which are usually placed on the waist or the wrist, respectively. These devices obtain one set of acceleration and angular velocity in the x-, y-, and z-axis from the accelerometer and the gyroscope planted in these devices. The PLHI-MC10 dataset contains data obtained by using 3 BioStamp nPoint® sensors from 7 physically healthy adult test subjects performing different exercise activities. These sensors are the state-of-the-art biomedical sensors manufactured by MC10. Each of the three sensors was attached to the subject externally on three muscles-Extensor Digitorum (Posterior Forearm), Gastrocnemius (Calf), and Pectoralis (Chest)-giving us three sets of 3 axial acceleration, two sets of 3 axial angular velocities, and 1 set of voltage values from the heart. Using three different sensors instead of a single sensor improves precision. It helps distinguish between human activities as it simultaneously captures the movement and contractions of various muscles from separate parts of the human body. Each test subject performed five activities (stairs, jogging, skipping, lifting kettlebell, basketball throws) in a supervised environment. The data is cleaned, filtered, and synced. Elsevier 2021-08-20 /pmc/articles/PMC8397882/ /pubmed/34485637 http://dx.doi.org/10.1016/j.dib.2021.107287 Text en © 2021 The Authors. Published by Elsevier Inc. https://creativecommons.org/licenses/by/4.0/This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Data Article Mahajan, Yohan Bhimireddy, Ananth Abid, Areeba Gichoya, Judy W. Purkayastha, Saptarshi PLHI-MC10: A dataset of exercise activities captured through a triple synchronous medically-approved sensor |
title | PLHI-MC10: A dataset of exercise activities captured through a triple synchronous medically-approved sensor |
title_full | PLHI-MC10: A dataset of exercise activities captured through a triple synchronous medically-approved sensor |
title_fullStr | PLHI-MC10: A dataset of exercise activities captured through a triple synchronous medically-approved sensor |
title_full_unstemmed | PLHI-MC10: A dataset of exercise activities captured through a triple synchronous medically-approved sensor |
title_short | PLHI-MC10: A dataset of exercise activities captured through a triple synchronous medically-approved sensor |
title_sort | plhi-mc10: a dataset of exercise activities captured through a triple synchronous medically-approved sensor |
topic | Data Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8397882/ https://www.ncbi.nlm.nih.gov/pubmed/34485637 http://dx.doi.org/10.1016/j.dib.2021.107287 |
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