This contribution proposes a multi-modal system for older adults' health monitoring within the smart home framework that integrates Mixed Reality, a network of IoT sensors, wearable health sensors, and users' feedback to collect data and monitor older adults' health. It provides a comprehensive framework for older adults' health monitoring and safe exercise sessions to enhance their physical and cognitive well-being. The proposed system allows older adults to control the smart home features and benefit from assistive services via a mixed reality application. The system explores exploiting machine learning models to provide personalized physical and cognitive training routines to enhance older adults' quality of life, autonomy, and general well-being. It leverages historical data coming from wearable sensors, smart mixed reality glasses, IoT sensors, and users' feedback to predict the users' health status and activity level and suggest the proper exercise routine accordingly.
Mahroo, A., Sacco, M. (2024). Towards the Integration of Mixed Reality and Machine Learning for Older Adults Personalized Smart Home and Health Monitoring. In 2024 IEEE International Conference on Metrology for eXtended Reality, Artificial Intelligence and Neural Engineering (MetroXRAINE) (pp.95-100). Institute of Electrical and Electronics Engineers Inc. [10.1109/metroxraine62247.2024.10796635].
Towards the Integration of Mixed Reality and Machine Learning for Older Adults Personalized Smart Home and Health Monitoring
Mahroo A.;
2024
Abstract
This contribution proposes a multi-modal system for older adults' health monitoring within the smart home framework that integrates Mixed Reality, a network of IoT sensors, wearable health sensors, and users' feedback to collect data and monitor older adults' health. It provides a comprehensive framework for older adults' health monitoring and safe exercise sessions to enhance their physical and cognitive well-being. The proposed system allows older adults to control the smart home features and benefit from assistive services via a mixed reality application. The system explores exploiting machine learning models to provide personalized physical and cognitive training routines to enhance older adults' quality of life, autonomy, and general well-being. It leverages historical data coming from wearable sensors, smart mixed reality glasses, IoT sensors, and users' feedback to predict the users' health status and activity level and suggest the proper exercise routine accordingly.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.


