The aim of this paper is to study the use of a prototype of wearable device for long term monitoring of gait and balance using inertial sensors. First, it is focused on the design of the device that can be used all day during the patient daily life activities, because it is small, usable and non invasive. Secondly, we present the system calibration to ensure the quality of the sensors data. Afterwodrs, we focus in the experimental methodology for data harvest from extensive types of falls. Finally a statistical analysis allows us to determine the discriminant information to detect falls.
CitationTorrent, M. [et al.]. Ambulatory mobility characterization using body inertial system: an application to fall detection. A: International Work-Conference on Artificial Neural Networks. "10th International Work-Conference on Artificial Neural Networks". Salamanca: Springer Verlag, 2009, p. 1129-1136.
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