The photoplethysmogram (PPG) signal is widely measured by smart watches and fitness bands for heart rate monitoring. New applications of the PPG are also emerging, such as to detect irregular heart rhythms, identify sleep disturbances, and assess stress. PPG signal processing algorithms must be robust to variable signal quality due to motion artifact and poor sensor contact. Consequently, datasets of PPG signals acquired in daily life are valuable for algorithm development. The aim of this pilot study was to assess the feasibility of acquiring PPG data in daily life.
A single subject was asked to wear a wrist-worn PPG sensor (SmartCare Analytics) for as much time as possible, for six days a week, for four weeks. They kept a diary of daily activities and any sensor maintenance or troubleshooting required. PPG data were transmitted to a smartphone for storage.
The sensor was worn for approximately three quarters of the time, and was primarily removed for charging, as well as activities involving water, and having a break or forgetting the sensor. Whilst wearing the sensor, the most common reason for data loss was Bluetooth disconnection. Signal quality was high for approximately half of the time: it was highest during sleep, followed by sedentary activities, and was particularly low during exercise or activities involving hand movement such as cooking.
In this study it was possible to acquire PPG data during daily living for four weeks. Key lessons were learnt for future studies: the sensor should be waterproof to reduce the need for removal; data should be stored on the device to avoid loss due to disconnections; and data should preferably be acquired during sleep or periods of low activity to maximise quality, although further research should investigate how this would limit utility. The dataset is being made available at https://peterhcharlton.github.io/ppg-diary/ .
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