Obstructive Sleep Apnea and Hypopnea Syndrome (OSAHS) is a widespread non-communicable disease in which the vast majority of cases remains undetected. To solve this problem, we introduced APNIWAVE: An efficient radar-based sleep-apnea screening device for use at home. APNIWAVE is a device that includes an ultra-wideband radar 
sensor, an edge computing module, and Machine Learning algorithms to detect OSAHS by observing the breathing pattern of the screened patients. The developed solution is based on low-cost components, it is very convenient to use and can be particularly used for screening patients at their home, adding in this way zero additional burden to the overloaded third-grade units worldwide. The proposed solution was applied to 11 patients with OSAHS. The data were collected during their entire sleep interval (ranging between 5.5 – 8 hours) and used for the training of five Machine Learning algorithms. The highest classification accuracy was 88% and was achieved using random forest, validating the effectiveness of the developed framework.
Project Τitle: APNIWAVE: An Efficient Radar-Based Sleep-Apnea Screening Device for Use at Home
Project Duration: 19/04/2022 – 31/12/2022
Project Framework & Funding: EIT Health RIS
Scientific coordinator (UNIWA): Stelios MITILINEOS, Professor, EEE Department, UNIWA
Consortium – Partners:
Eight Bells Ltd. Greek Branch
Vascular Research S.A.
Research Publications / Results / Patents:
[1] Uzunidis, D., Liapis, D., Kasnesis, P., Ferles, C., Margaritis, E., Patrikakis, C. Z., Tzanis, G., and Mitilineos, S. A., “APNIWAVE: An efficient radar-based sleep-apnea screening device for use at home”, Proceedings of the 12th International Conference on Modern Circuits and Systems Technologies (MOCAST 2023), pp. 1-5, June 28-30, 2023, Athens, GREECE; DOI: 10.1109/MOCAST57943.2023.10176741.
