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PHAROS 2.0—A PHysical Assistant RObot System Improved
There are great physical and cognitive benefits for older adults who are engaged in active aging, a process that should involve daily exercise. In our previous work on the PHysical Assistant RObot System (PHAROS), we developed a system that proposed and monitored physical activities. The system used...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6832539/ https://www.ncbi.nlm.nih.gov/pubmed/31635278 http://dx.doi.org/10.3390/s19204531 |
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author | Martinez-Martin, Ester Costa, Angelo Cazorla, Miguel |
author_facet | Martinez-Martin, Ester Costa, Angelo Cazorla, Miguel |
author_sort | Martinez-Martin, Ester |
collection | PubMed |
description | There are great physical and cognitive benefits for older adults who are engaged in active aging, a process that should involve daily exercise. In our previous work on the PHysical Assistant RObot System (PHAROS), we developed a system that proposed and monitored physical activities. The system used a social robot to analyse, by means of computer vision, the exercise a person was doing. Then, a recommender system analysed the exercise performed and indicated what exercise to perform next. However, the system needed certain improvements. On the one hand, the vision system captured the movement of the person and indicated whether the exercise had been done correctly or not. On the other hand, the recommender system was based purely on a ranking system that did not take into account temporal evolution and preferences. In this work, we propose an evolution of PHAROS, PHAROS 2.0, incorporating improvements in both of the previously mentioned aspects. In the motion capture aspect, we are now able to indicate the degree of completeness of each exercise, identifying the part that has not been done correctly, and a real-time performance correction. In this way, the recommender system receives a greater amount of information and so can more accurately indicate the exercise to be performed. In terms of the recommender system, an algorithm was developed to weigh the performance, temporal evolution and preferences, providing a more accurate recommendation, as well as expanding the recommendation to a batch of exercises, instead of just one. |
format | Online Article Text |
id | pubmed-6832539 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-68325392019-11-25 PHAROS 2.0—A PHysical Assistant RObot System Improved Martinez-Martin, Ester Costa, Angelo Cazorla, Miguel Sensors (Basel) Article There are great physical and cognitive benefits for older adults who are engaged in active aging, a process that should involve daily exercise. In our previous work on the PHysical Assistant RObot System (PHAROS), we developed a system that proposed and monitored physical activities. The system used a social robot to analyse, by means of computer vision, the exercise a person was doing. Then, a recommender system analysed the exercise performed and indicated what exercise to perform next. However, the system needed certain improvements. On the one hand, the vision system captured the movement of the person and indicated whether the exercise had been done correctly or not. On the other hand, the recommender system was based purely on a ranking system that did not take into account temporal evolution and preferences. In this work, we propose an evolution of PHAROS, PHAROS 2.0, incorporating improvements in both of the previously mentioned aspects. In the motion capture aspect, we are now able to indicate the degree of completeness of each exercise, identifying the part that has not been done correctly, and a real-time performance correction. In this way, the recommender system receives a greater amount of information and so can more accurately indicate the exercise to be performed. In terms of the recommender system, an algorithm was developed to weigh the performance, temporal evolution and preferences, providing a more accurate recommendation, as well as expanding the recommendation to a batch of exercises, instead of just one. MDPI 2019-10-18 /pmc/articles/PMC6832539/ /pubmed/31635278 http://dx.doi.org/10.3390/s19204531 Text en © 2019 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 Martinez-Martin, Ester Costa, Angelo Cazorla, Miguel PHAROS 2.0—A PHysical Assistant RObot System Improved |
title | PHAROS 2.0—A PHysical Assistant RObot System Improved |
title_full | PHAROS 2.0—A PHysical Assistant RObot System Improved |
title_fullStr | PHAROS 2.0—A PHysical Assistant RObot System Improved |
title_full_unstemmed | PHAROS 2.0—A PHysical Assistant RObot System Improved |
title_short | PHAROS 2.0—A PHysical Assistant RObot System Improved |
title_sort | pharos 2.0—a physical assistant robot system improved |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6832539/ https://www.ncbi.nlm.nih.gov/pubmed/31635278 http://dx.doi.org/10.3390/s19204531 |
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