The Advancement of Artificial Intelligence in Elderly Monitoring
Artificial intelligence (AI) and wireless technology are being used by engineers to monitor elderly individuals in their living spaces, enabling early detection of emerging health problems. Developed by researchers at the University of Waterloo, this new system accurately and continuously tracks an individual’s activities without the need for wearable devices, while also alerting medical experts when intervention is required.
The Significance of AI in Elderly Monitoring
With an increasing elderly population, public healthcare systems face challenges in meeting their urgent needs. Rapid changes in physical and mental conditions make it difficult to track movements and identify problems 24/7, even in long-term care settings. Existing monitoring systems for gait, such as tracking how a person walks, are costly, complex, and impractical for clinics and homes.
The Breakthrough: How the System Works
The new system makes use of low-power waveforms transmitted wirelessly across the monitored space. As the waveforms interact with objects and individuals, they are captured and processed by a receiver. An AI engine then interprets the processed waves for detection and monitoring purposes. Unlike wearable devices, this system can be easily mounted on a ceiling or wall and does not require frequent battery charging or cause discomfort.
The capabilities of the system extend beyond basic monitoring. It can effectively track activities like sleeping, watching TV, eating, and bathroom use. Currently, it can detect a decline in mobility, an increased risk of falls, the possibility of a urinary tract infection, and the onset of various medical conditions.
Commercialization and Future Outlook
Waterloo researchers have partnered with Gold Sentintel, a Canadian company, to commercialize this technology. It has already been implemented in several long-term care homes, providing valuable insights and enhancing the quality of care for elderly individuals. The work on this AI-powered monitoring system is documented in the IEEE Internet of Things Journal.
Lead author Hajar Abedi, along with Ahmad Ansariyan, Dr. Plinio Morita, Dr. Jen Boger, and Dr. Alexander Wong, contributed to the research.