Analysis of Sensors for Movement Analysis

descriptionPublicationkeyboard_double_arrow_right Part of book or chapter of book , Article , Preprint 01 Jan 2023Embargo end date: 01 Jan 2024 English Publisher:Springer Nature Singapore

Authors: Marcos Faundez-Zanuy; Anna Faura-Pujol; Hector Montalvo-Ruiz; Alexia Losada-Fors; Pablo Genovese; Pilar Sanz-Cartagena;

doi: 10.1007/978-981-99-3592-5_4 , 10.48550/arxiv.2408.07281

arXiv: 2408.07281

Analysis of Sensors for Movement Analysis

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Abstract

In this paper we analyze and compare different movement sensors: micro-chip gesture-ID, leap motion, noitom mocap, and specially developed sensor for tapping and foot motion analysis. The main goal is to evaluate the accu-racy of measurements provided by the sensors. This study presents rele-vance, for instance, in tremor/Parkinson disease analysis as well as no touch mechanisms for activation and control of devices. This scenario is especially interesting in COVID-19 scenario. Removing the need to touch a surface, the risk of contagion is reduced.

In: Esposito, A., Faundez-Zanuy, M., Morabito, F.C., Pasero, E. (eds) Applications of Artificial Intelligence and Neural Systems to Data Science. Smart Innovation, Systems and Technologies, vol 360. Springer, Singapore

Related Organizations

Maresme Health Consortium
Spain
Universitat Pompeu Fabra
Spain

Keywords

Signal Processing (eess.SP), FOS: Computer and information sciences, Computer Science - Machine Learning, Computer Science - Robotics, FOS: Electrical engineering, electronic engineering, information engineering, Electrical Engineering and Systems Science - Signal Processing, Robotics (cs.RO), Machine Learning (cs.LG)

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