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A multi-sensory dataset for the activities of daily living
The article describes a multi-sensory dataset related to the Activities of Daily Living (ADL). These are the activities that contribute to an assessment of the overall status of elderly or people with special needs, possibly suffering from mild cognitive impairments. Typical basic ADLs include walki...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7452700/ https://www.ncbi.nlm.nih.gov/pubmed/32904359 http://dx.doi.org/10.1016/j.dib.2020.106122 |
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author | Ruzzon, Marco Carfì, Alessandro Ishikawa, Takahiro Mastrogiovanni, Fulvio Murakami, Toshiyuki |
author_facet | Ruzzon, Marco Carfì, Alessandro Ishikawa, Takahiro Mastrogiovanni, Fulvio Murakami, Toshiyuki |
author_sort | Ruzzon, Marco |
collection | PubMed |
description | The article describes a multi-sensory dataset related to the Activities of Daily Living (ADL). These are the activities that contribute to an assessment of the overall status of elderly or people with special needs, possibly suffering from mild cognitive impairments. Typical basic ADLs include walking, such postural transitions as getting up or sitting down, as well as behaviours related to feeding, such as drinking or eating with knife and fork, or personal hygiene, e.g., teeth brushing. The collection process adopted for building this dataset considers nine ADL-related activities, which have been performed in different locations and involving the usage of both left and right arms. The dataset acquisition involved 10 volunteers performing 186 ADL instances, for a grand total of over 1860 examples. The dataset contains data from six 9-axis Inertial Measurement Units (IMUs), worn by each volunteer (two for each arm, one on the back and one on the right thigh). The dataset features an accurate data labelling done via manual annotation performed thanks to videos recorded by an RGB camera. The videos recorded during the experiments have been used only for labelling purposes, and they are not published. |
format | Online Article Text |
id | pubmed-7452700 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Elsevier |
record_format | MEDLINE/PubMed |
spelling | pubmed-74527002020-09-03 A multi-sensory dataset for the activities of daily living Ruzzon, Marco Carfì, Alessandro Ishikawa, Takahiro Mastrogiovanni, Fulvio Murakami, Toshiyuki Data Brief Computer Science The article describes a multi-sensory dataset related to the Activities of Daily Living (ADL). These are the activities that contribute to an assessment of the overall status of elderly or people with special needs, possibly suffering from mild cognitive impairments. Typical basic ADLs include walking, such postural transitions as getting up or sitting down, as well as behaviours related to feeding, such as drinking or eating with knife and fork, or personal hygiene, e.g., teeth brushing. The collection process adopted for building this dataset considers nine ADL-related activities, which have been performed in different locations and involving the usage of both left and right arms. The dataset acquisition involved 10 volunteers performing 186 ADL instances, for a grand total of over 1860 examples. The dataset contains data from six 9-axis Inertial Measurement Units (IMUs), worn by each volunteer (two for each arm, one on the back and one on the right thigh). The dataset features an accurate data labelling done via manual annotation performed thanks to videos recorded by an RGB camera. The videos recorded during the experiments have been used only for labelling purposes, and they are not published. Elsevier 2020-08-02 /pmc/articles/PMC7452700/ /pubmed/32904359 http://dx.doi.org/10.1016/j.dib.2020.106122 Text en © 2020 The Authors http://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 | Computer Science Ruzzon, Marco Carfì, Alessandro Ishikawa, Takahiro Mastrogiovanni, Fulvio Murakami, Toshiyuki A multi-sensory dataset for the activities of daily living |
title | A multi-sensory dataset for the activities of daily living |
title_full | A multi-sensory dataset for the activities of daily living |
title_fullStr | A multi-sensory dataset for the activities of daily living |
title_full_unstemmed | A multi-sensory dataset for the activities of daily living |
title_short | A multi-sensory dataset for the activities of daily living |
title_sort | multi-sensory dataset for the activities of daily living |
topic | Computer Science |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7452700/ https://www.ncbi.nlm.nih.gov/pubmed/32904359 http://dx.doi.org/10.1016/j.dib.2020.106122 |
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