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A General System for Dataset Generation from Smartwatch Sensors for Biomedical Research

2023; Springer International Publishing; Linguagem: Inglês

10.1007/978-981-99-2680-0_47

2367-3370

Rishabh Jain, Manav Mago, Vibham Kumar Dubey, V. P. Nathasha, Rahul Shukla, Ashish Kumar Sahani,

Mobile Health and mHealth Applications

This paper describes a novel Android Wear OS application, designed to enable researchers to conveniently collect sensor data from commonly available Wear OS smartwatches for dataset generation. The application was primarily developed to ensure the reliability of data collection during physical exercises. The application thus proposed implements a reliable dataset generation architecture, which researchers can extend and modify to adapt to their workflows. In the application, data is collected from sensors present on the smartwatch and then transferred to a paired smartphone. Thus, the application eliminates the need for a third device or service (such as cloud storage) for dataset generation. Data obtained from the smartwatch is stored in a predetermined folder/directory in the smartphone in CSV format making it convenient for performing data analysis. The application is tested by recording data from multiple subjects in the lab environment as well as outside the lab. The quality of data was confirmed by plotting it in normal working time, and during physical exercise and the changes are properly observed, which ensures that the data we are collecting is correct. Since the use of smartwatches has become prevalent for studying and diagnosing diseases, the application will be very useful for researchers across the globe for creating datasets for biomedical research.