We present an IoT-based monitoring system for healthcare that allows for long-term measurements of blood pressure (BP), heart rate (HR), and body weight (BW), as well as near-infrared spectroscopy (NIRS) for measurement of prefrontal cortex (PFC) activity. To verify the applicability of the system, it was set up in a local fitness gym for a preliminary study. A total of 39 subjects, selected from members of the gym, participated in the study. We analyzed the BP, HR, and BW data, collected from the subjects over one half-year. In addition, to assess the degree of mental stress of the subjects, we analysed left-right asymmetry of the PFC activity using the laterality index at rest (LIR) of the NIRS parameter. Results show that the subjects were able to measure their physiological data by themselves when they visited the gym, after being instructed how to perform the measurements. Furthermore, the results also indicate that ordinary people can continuously monitor physiological functions such as brain function in a non-medical facility, such as a fitness gym.
Keywords: Big data; Health care; IoT; Near infrared spectroscopy; Prevention medicine.