RT Conference Proceedings
T1 Gait recognition and fall detection with inertial sensors
A1 Delgado-Escaño, Rubén
A1 Castro, Francisco M.
A1 Marín-Jiménez, Manuel J.
A1 Guil-Mata, Nicolás
K1 Reconocimiento óptico de formas (Informática)
AB In contrast to visual information that is recorded by cameras placed somewhere, inertial information can be obtained from mobile phones that are commonly used in daily life. We present in this talk a general deep learning approach for gait and soft biometrics (age and gender) recognition. Moreover, we also study the use of gait information to detect actions during walking, specifically, fall detection.  We perform a thorough experimental evaluation of the proposed approach on different datasets: OU-ISIR Biometric Database, DFNAPAS, SisFall, UniMiB-SHAR and ASLH. The experimental results show that inertial information can be used for gait recognition and  fall detection with state-of-the-art results.
YR 2019
FD 2019-11-26
LK https://hdl.handle.net/10630/18911
UL https://hdl.handle.net/10630/18911
LA eng
NO Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech.
DS RIUMA. Repositorio Institucional de la Universidad de Málaga
RD 20 ene 2026