A Fuzzy Logic-Based Personalized Method to Classify Perceived Exertion in Workplaces Using a Wearable Heart Rate Sensor
| Autor: | Francisco Acosta-Escalante, José Adán Hernández-Nolasco, Pablo Pancardo |
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| Rok vydání: | 2018 |
| Předmět: |
Article Subject
Computer Networks and Communications Computer science 05 social sciences Human factors and ergonomics Wearable computer TK5101-6720 030229 sport sciences Perceived exertion Fuzzy logic Computer Science Applications 03 medical and health sciences 0302 clinical medicine Physical work Human–computer interaction Heart rate Telecommunication 0501 psychology and cognitive sciences 050107 human factors |
| Zdroj: | Mobile Information Systems, Vol 2018 (2018) |
| ISSN: | 1875-905X 1574-017X |
| DOI: | 10.1155/2018/4216172 |
| Popis: | Knowing the perceived exertion of workers during their physical activities facilitates the decision-making of supervisors regarding the worker allocation in the appropriate job, actions to prevent accidents, and reassignment of tasks, among others. However, although wearable heart rate sensors represent an effective way to capture perceived exertion, ergonomic methods are generic and they do not consider the diffuse nature of the ranges that classify the efforts. Personalized monitoring is needed to enable a real and efficient classification of perceived individual efforts. In this paper, we propose a heart rate-based personalized method to assess perceived exertion; our method uses fuzzy logic as an option to manage imprecision and uncertainty in involved variables. We applied some experiments to cleaning staff and obtained results that highlight the importance of a custom method to classify perceived exertion of people doing physical work. |
| Databáze: | OpenAIRE |
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