Authors:
Ana Rocha
1
;
Diogo Santos
2
;
Florentino Sánchez
2
;
Gonçalo Aguiar
2
;
Henrique Ramos
2
;
Miguel Ferreira
2
;
Tiago Bastos
2
;
Ilídio C. Oliveira
1
and
António Teixeira
1
Affiliations:
1
Institute of Electronics and Informatics Engineering of Aveiro (IEETA), Department of Electronics, Telecommunications and Informatics, Intelligent Systems Associate Laboratory (LASI), University of Aveiro, Aveiro, Portugal
;
2
Department of Electronics, Telecommunications and Informatics, University of Aveiro, Aveiro, Portugal
Keyword(s):
Gestures, Human Communication, Smart Environments, Bed, Wearable Sensors, Smartwatch.
Abstract:
Gestures can be a suitable way of supporting communication for people with communication difficulties, especially in the bedroom scenario. In the scope of the AAL APH-ALARM project, we previously proposed a gesture-based communication solution for the bedroom context, which relies on a smartwatch for gesture recognition. In this contribution, our main aim is to explore better wearable alternatives to the smartwatch regarding the form factor and comfort of use, as well as cost. We compare a smartwatch and a simpler, smaller, less expensive wearable device from MbientLab, both integrating an accelerometer and a gyroscope, in terms of gesture classification performance. The results obtained based on data acquired from six subjects and the support vector machines algorithm show that, overall, both explored devices lead to a model with promising and similar results (mean accuracy and F1 score of 98%, and mean false positive rate of 2%), being thus possible to rely on a smaller and lower c
ost wearable device, such as the MbientLab sensor module, for recognizing the considered arm gestures.
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