Gesture Recognition with Ultrasounds and Edge Computing
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AuthorSáez, Borja; Méndez, Javier; Molina, Miguel; Castillo Morales, María Encarnación; Pegalajar Cuéllar, Manuel; Morales Santos, Diego Pedro
IEEE Inst Electrical Electronics Engineers Inc
Edge computingGesture recognitionHuman System Interaction (HSI)Ultrasound
Saez, B., Mendez, J., Molina, M., Castillo, E., Pegalajar, M., & Morales, D. P. (2021). Gesture Recognition With Ultrasounds and Edge Computing. IEEE Access, 9, 38999-39008. [doi:10.1109/ACCESS.2021.3064390]
SponsorshipEuropean Commission 737487 16ESE0161K; European Union's Horizon 2020 Programme (ECSEL); Federal Ministry of Education & Research (BMBF)
The aim of this work is to prove that it is possible to develop a system able to detect gestures based only on ultrasonic signals and Edge devices. A set of 7 gestures plus idle has been defined, being possible to combine them to increase the recognized gestures. In order to recognize them, Ultrasound transceivers will be used to detect the 2 dimensional gestures. The Edge device approach implies that the whole data is processed in the device at the network edge rather than depending on external devices or services such as Cloud Computing. The system presented in this paper has been proven to be able to measure Time of Flight (ToF) signals that can be used to recognize multiple gestures by the integration of two transceivers, with an accuracy between 84.18% and 98.4%. Due to the optimization of the preprocessing correlation technique to extract the ToF from the echo signals and our specific firmware design to enable the parallelization of concurrent processes, the system can be implemented as an Edge Device.