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Classification of human physical activity based on the raw accelerometry data via spherical coordinate transformation
[article]
2019
bioRxiv
pre-print
Human health is strongly associated with person's lifestyle and levels of physical activity. Therefore, characterization of daily human activity is an important task. Accelerometers have been used to obtain precise measurements of body acceleration. Wearable accelerometers collect data as a three-dimensional time series with frequencies up to 100Hz. Using such accelerometry signal, we are able to classify different types of physical activity. In our work, we present a novel procedure for
doi:10.1101/686519
fatcat:ldf7sm4lifdmzcunl4gwpnhruq