Advances in wearable/mobile device technologies make possible long-Term recording of data in our everyday life contexts. Of particular interest is availability of inertial sensors allowing to monitor daily physical activity behavior, which is thought to include useful information on physiology, age/disease related functional capacity, and quality of life. The challenging task in this interdisciplinary research context is to translate the raw data into interpretable information and knowledge that can be further exploited to provide valid hypothesis, objective evaluation and diagnosis. The aim of this paper is to present a methodological framework that brings together monitoring technology, mathematical tools and modern clinical concepts of physiological complexity, with the aim to reveal and quantify aspects of age-/health-related physical behavior embedded in patterns of everyday life activity.
Patterns of human activity behavior: From data to information and clinical knowledge / Paraschiv-Ionescu, A.; Mellone, S.; Colpo, M.; Bourke, A.; Ihlen, E.A.F.; Moufawad El Achkar, C.; Chiari, L.; Becker, C.; Aminian, K.. - ELETTRONICO. - (2016), pp. 841-845. (Intervento presentato al convegno 2016 ACM International Joint Conference on Pervasive and Ubiquitous Computing, UbiComp 2016 tenutosi a Heidelberg; Germany nel 12-16 September 2016) [10.1145/2968219.2968283].
Patterns of human activity behavior: From data to information and clinical knowledge
MELLONE, SABATO;CHIARI, LORENZO;
2016
Abstract
Advances in wearable/mobile device technologies make possible long-Term recording of data in our everyday life contexts. Of particular interest is availability of inertial sensors allowing to monitor daily physical activity behavior, which is thought to include useful information on physiology, age/disease related functional capacity, and quality of life. The challenging task in this interdisciplinary research context is to translate the raw data into interpretable information and knowledge that can be further exploited to provide valid hypothesis, objective evaluation and diagnosis. The aim of this paper is to present a methodological framework that brings together monitoring technology, mathematical tools and modern clinical concepts of physiological complexity, with the aim to reveal and quantify aspects of age-/health-related physical behavior embedded in patterns of everyday life activity.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
