Architecture for real-time heart rate monitoring from a social robot

Abstract

The demographic shift towards an older population has heightened the demand for remote surveillance and assistance for seniors, particularly those living in solitude who could potentially experience stress, fear, depression, and isolation. This work presents how the social robot Mini integrates a software architecture aimed at facilitating the extended independent living of elderly individuals. To accomplish this, the robot acquires data from a wearable device for real-time heart rate monitoring of senior citizens using photoplethysmography signals. These signals are decoded, parsed, processed, and classified to recognise potential heart rate anomalies and address them appropriately. When confronted with abnormally high or low pulse measurements, the robot engages with the user to cross-examine symptoms via a sequence of inquiries. If the user confirms the presence of any symptoms or fails to respond, the robot transmits an alert to caregivers by employing Telegram, a mobile device messaging service, or a dedicated visual online platform. The online platform provides monitoring interfaces designed for caregivers to deliver historical data in a comprehensive format.