BEGIN:VCALENDAR
VERSION:2.0
PRODID:-//project/author//NONSGML v1.0//EN
CALSCALE:GREGORIAN
BEGIN:VEVENT
DTEND:20230515T120000Z
UID:a9e660a9afbdd1a57fc192d55155ea87-461
DTSTAMP:19700101T120015Z
DESCRIPTION:Towards Self-Sustainable Wearable Devices for Reliable Mobile Health Applications
URL;VALUE=URI:https://www.csa.iisc.ac.in/newweb/event/461/towards-self-sustainable-wearable-devices-for-reliable-mobile-health-applications/
SUMMARY:Wearable sensors, along with smart home technologies, have the potential to transform healthcare by enabling cost-effective, reliable, continuous, and data-driven monitoring of users in a free-living environment. Continuous monitoring of user activities and vital signs is exciting, as it can expose health issues otherwise difficult to perceive in an office visit. It can also identify early warnings of adverse health events requiring immediate intervention. Despite the impressive potential of wearable technology, widespread adoption of wearable devices has been limited due to several technology and adaptation challenges. This has led to multiple health societies, including the Movement Disorders Society Task Force on Technology, stating that solving these challenges is crucial to improving wearable devices adoption. First, existing wearables devices are rigid, which makes them uncomfortable to wear for long periods. Second, existing implementations of wearable devices typically consider a single device or sensor at a time. As a result, the development of wearable devices happens in isolated silos with limited cross-compatibility. Third, wearable devices have small batteries that necessitate frequent recharging to prolong their operation. In this talk, I will present solutions towards these challenges. First, I will present our open-source hardware/software platform for wearable health monitoring. The platform uses flexible hybrid electronics to enable devices that conform to the shape of the users body. Then, I will describe an algorithm to enable recharge-free operation of wearable devices that harvest energy from the environment. After that, I will present a hardware accelerator and reliable algorithms for the human activity recognition application.
DTSTART:20230515T120000Z
END:VEVENT
END:VCALENDAR