Abstract
Nowadays, video games are not considered only mere hobbies. The use of these tools is increased in last years. On the other hand, gamification and usability techniques have empowered the improvement of communication between player/user and Aided Communication Devices (ACD). New ACDs provide a novel approach to capture biomechanical features or indicators. This work consists of a novel methodology development to capture biomechanical indicators throughout multiplatform video games. The present work has an exploratory nature to measure, hand-wrist articulation features estimated from the smartphone’s accelerometer. The intention of the study is to answer some hypothesis for instance, if the device is crucial to evaluate player’s movement capabilities or if the age of the person as a key biomarker. Once these indicators have been tested, it will be able to use them in studies of neurodegenerative diseases, where involuntary tremor is one of the most important observable correlates.
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This work is being funded by grants TEC2016 – 77791 – C4 – 4 – R (MINECO, Spain) and CENIE _ TECA – PARK_55_02 INTERREG V – A Spain – Portugal (POCTEP).
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Palacios-Alonso, D., Lázaro-Carrascosa, C., Mas-García, R., Ferrández Vicente, J.M., Gómez-Rodellar, A., Gómez-Vilda, P. (2019). Distinguishing Aging Clusters and Mobile Devices by Hand-Wrist Articulation: A Case of Study. In: Ferrández Vicente, J., Álvarez-Sánchez, J., de la Paz López, F., Toledo Moreo, J., Adeli, H. (eds) Understanding the Brain Function and Emotions. IWINAC 2019. Lecture Notes in Computer Science(), vol 11486. Springer, Cham. https://doi.org/10.1007/978-3-030-19591-5_2
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