Summary
I am developing a new wearable device to monitor patients suffering from infectious diseases in heavily populated areas to reduce the number of hospitalisations. With the ever-rising population and long waiting times in hospitals, an inexpensive device capable of identifying people at risk can improve the standard of care around the world.
My work looks at a specific infectious disease spread by mosquitos called Dengue. Every year, millions of people get infected during seasonal epidemics in South-East Asia overwhelming regional hospitals making them unable to deliver the required care to every patient. This, in turn, can sometimes lead to missed critical cases, resulting in dangerous health complications. Using the same light-based sensing principle as modern smartwatches, the final device will be able to measure all common health information like heart rate and breathing rate. In addition, things like blood pressure and details about blood components will also be measured as a part of a single system. The disease has similar progress to flu, but peaking just after the period of high fever. It is this time when the potentially deadly Dengue shock can occur in a small number of infections. If a patient enters the shock while outside of a medical facility, the survival rate is slim. Thanks to our research, instead of hospitalizing the patient for the whole duration of the disease, our device can monitor patients at their homes only alerting the professionals if needed.
Publications
Journals
Chanh HQ, Ming DK, Nguyen QH, et al., 2023, Applying artificial intelligence and digital health technologies, Viet Nam, Bulletin of the World Health Organization, Vol:101, ISSN:0042-9686, Pages:487-492
Karolcik S, Ming D, Yacoub S, et al., 2023, A multi-site, multi-wavelength PPG platform for continuous non-invasive health monitoring in hospital settings, Ieee Transactions on Biomedical Circuits and Systems, Vol:17, ISSN:1932-4545, Pages:349-361
Le V-KD, Hai BH, Karolcik S, et al., 2022, vital_sqi: A Python package for physiological signal quality control, Frontiers in Physiology, Vol:13
Karolcik S, Miscourides N, Cacho-Soblechero M, et al., 2020, A High-Performance Raspberry Pi-Based Interface for Ion Imaging Using ISFET Arrays, Ieee Sensors Journal, Vol:20, ISSN:1530-437X, Pages:12837-12847
Conference
Cacho-Soblechero M, Karolcik S, Haci D, et al., 2019, Live Demonstration: A Portable ISFET Platform for PoC Diagnosis Powered by Solar Energy, IEEE Biomedical Circuits and Systems Conference (BioCAS), IEEE, ISSN:2163-4025