Abstract
The ageing of the population has increased the need for remote monitoring and support for older adults, especially those who live alone and may experience stress, fear, depression, and isolation. In this work, the Mini social robot implements an architecture designed to help the elderly live independently for longer. To achieve this, the robot uses information from a wearable device to monitor the heart rate of older adults in real-time using photoplethysmography signals. These signals are decoded, parsed, processed, and classified to identify potential abnormalities and respond accordingly. In the case of abnormally high or low pulse values, the robot interacts with the user to check for symptoms by asking a series of questions. If the user responds positively to any of the questions or does not respond at all, the robot alerts the contact persons via Telegram, a widely used and user-friendly messaging application.
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Acknowledgements
The research leading to these results has received funding from the projects: PID2021-123941OA-I00, PID2021-128525OB-I00 and TED2021-130935B-I00 funded by Agencia Estatal de Investigación (AEI), Spanish Ministerio de Ciencia e Innovación. Also, this work was supported by Generalitat Valenciana CIGE/ 2021/136, Regional Development and “NextGenerationEU”/PRTR, SBPLY/21/ 180501/000186 from Junta de Comunidades de Castilla-La Mancha. Daniele Padovano holds a predoctoral scholarship 2022-PRED-20642.
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Martinez-Rodrigo, A., Castillo, J.C., Carrasco-Martínez, S., Padovano, D., Costa, A. (2023). Intelligent Heart Rate Monitoring from a Social Robot. In: Novais, P., et al. Ambient Intelligence – Software and Applications – 14th International Symposium on Ambient Intelligence. ISAmI 2023. Lecture Notes in Networks and Systems, vol 770. Springer, Cham. https://doi.org/10.1007/978-3-031-43461-7_5
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