Abstract
Nowadays, wearable devices enable us to collect biological data from a massive number of people. However, the reliability of the collected data varies due to various factors such as band tightness and incorrect attachment. In this paper, we investigate the band tightness estimation by using an inertial sensor of a wrist-worn device. First, we analyze the relationship between the band tightness and the data reliability through a preliminary experiment. Then, we design the band tightness estimation as a classification problem based on frequency domain features. The evaluation results show the effectiveness of the frequency domain features, achieving the accuracy of 81.7% for the 3-class band tightness classification.
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This paper is partially supported by Innovation Platform for Society 5.0 from Japan Ministry of Education, Culture, Sports, Science and Technology.
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Hayashi, M., Yoshikawa, H., Uchiyama, A., Higashino, T. (2020). Preliminary Investigation on Band Tightness Estimation of Wrist-Worn Devices Using Inertial Sensors. In: O'Hare, G., O'Grady, M., O’Donoghue, J., Henn, P. (eds) Wireless Mobile Communication and Healthcare. MobiHealth 2019. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 320. Springer, Cham. https://doi.org/10.1007/978-3-030-49289-2_20
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DOI: https://doi.org/10.1007/978-3-030-49289-2_20
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