| Autor: |
Juan A. Castro-Garcia, Alberto J. Molina-Cantero, Manuel Merino-Monge, Clara Lebrato-Vazquez, Isabel M. Gomez-Gonzalez |
| Jazyk: |
angličtina |
| Rok vydání: |
2023 |
| Předmět: |
|
| Zdroj: |
IEEE Access, Vol 11, Pp 46665-46677 (2023) |
| Druh dokumentu: |
article |
| ISSN: |
2169-3536 |
| DOI: |
10.1109/ACCESS.2023.3273303 |
| Popis: |
This paper presents the development of a virtual rehabilitation game and mental load with different difficulty blocks. The game was controlled with body tracking and physiological signals - acrlong ECG and acrlong EDA - were recorded throughout the session. Several parameters - acrlong HR (HR), acrlong HRV (HRV), acrlong SCL (SCL), acrlong SCR (SCR), energy expenditure...- were extracted from these signals to check mental load influence on them. Mental load was found to affect the variation in kinetic power and instantaneous heart rate; a Support Vector Machine with linear kernel was trained with these two variables and an 82.3% accuracy rate was obtained. Furthermore, the mental load was reflected in the number of errors made by the volunteers, in the selection time and in the number of rounds in the game. |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
|
