posted on 2021-05-01, 00:00authored byOuday Hanosh
Recent rapid advances in sensor technology and Internet of things (IoT) have led to remarkable progress in medical applications and public healthcare. Consequently, there is a huge momentum to develop Health Monitoring Systems (HMSs) that can improve patient care and safety, the accuracy of the information, and the real-time assessment of the human health condition.
Sensors play a crucial role in healthcare technology and HMSs with the aim of improving the quality of human life. The sensors can capture vital signs and other patient information and convert them into electrical signals that can be analyzed for follow-up action by caregivers as appropriate. A key challenge in HMSs is to find low-cost and accurate sensors that can be fitted on to non-intrusive, affordable, reliable, small, lightweight, and easy-to-use devices. The objective of these devices is to help achieve an accurate diagnosis, and to monitor patients not only in clinical settings but also in home environments.
In this dissertation we investigated the use of low-cost, non-contact pyroelectric and thermopile passive infrared sensors for motion detection in health monitoring applications. The research focus is on exploring the use of these sensors for the tasks of
i. convulsive body motion detection targeted at monitoring patients with epilepsy during sleep seeking to prevent sudden and an explained death in epilepsy (SUDEP), and
ii. subtle body motion detection aimed at estimating two vital signs: heart rate and respiratory rate.
We also investigate the design of efficient and low-cost algorithms and their practical implementation to perform the tasks and validate the methods experimentally.