@misc{10481/67926,
year = {2021},
url = {http://hdl.handle.net/10481/67926},
abstract = {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.},
organization = {European Commission

737487
16ESE0161K},
organization = {European Union's Horizon 2020 Programme (ECSEL)},
organization = {Federal Ministry of Education & Research (BMBF)},
publisher = {IEEE Inst Electrical Electronics Engineers Inc},
keywords = {Edge computing},
keywords = {Gesture recognition},
keywords = {Human System Interaction (HSI)},
keywords = {Ultrasound},
title = {Gesture Recognition with Ultrasounds and Edge Computing},
doi = {10.1109/ACCESS.2021.3064390},
author = {Sáez, Borja and Méndez, Javier and Molina, Miguel and Castillo Morales, María Encarnación and Pegalajar Cuéllar, Manuel and Morales Santos, Diego Pedro},
}