Abstract
The detection of tremors can be crucial for the early diagnosis and proper treatment of some disorders such as Parkinson’s disease. A smartphone-based application has been developed for detecting hand tremors. This application runs in background and distinguishes hand tremors from common daily activities. This application can facilitate the continuous monitoring of patients or the early detection of this symptom. The evaluation analyzes 1770 accelerometer samples with cross-validation for assessing the ability of the system for processing unknown data, obtaining a sensitivity of 95.8 % and a specificity of 99.5 %. It also analyzes continuous data for some volunteers for several days, which corroborated its high performance.
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Acknowledgments
This work has been done in the context of the Project “Soluciones tecnológicas para facilitar la práctica de mindfulness: caminando hacia mHealth” with reference TEC2013-50049-EXP and supported by the Spanish Ministry of Economy and Competitiveness. In addition, we acknowledge the “Fondo Social Europeo” and the “Departamento de Industria e Innovación del Gobierno de Aragón” for their joint support with grant number Ref-T81.
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García-Magariño, I., Medrano, C., Plaza, I. et al. A smartphone-based system for detecting hand tremors in unconstrained environments. Pers Ubiquit Comput 20, 959–971 (2016). https://doi.org/10.1007/s00779-016-0956-2
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DOI: https://doi.org/10.1007/s00779-016-0956-2