Wearable devices can track a multitude of parameters such as heart rate, body temperature, blood oxygen saturation, acceleration, blood glucose and many more (Kamiŝalić et al., 2018). Moreover, they are becoming increasingly popular with a steep increase in market presence in 2020 alone (IDC, 2020). Applications for wearable devices vary from tracking cardiovascular risks (Bayoumy et al., 2021) to identifying COVID-19 onset (Mishra et al., 2020). Therefore, there is a great need for scientists to easily go through data acquired from different wearables and to be able to share them while protecting user privacy. In order to solve this problem and empower scientists working with biosignals, we developed the devicely package. It processes the data into a tabular format and contains tools for data de-identification. It allows scientists to focus on what they want: the analysis of biosignals guided by privacy principles.
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