• Deep learning and change detection for fall recognition 

      Tasoulis S.K., Mallis G.I., Georgakopoulos S.V., Vrahatis A.G., Plagianakos V.P., Maglogiannis I.G. (2019)
      Early fall detection is a crucial research challenge since the time delay from fall to first aid is a key factor that determines the consequences of a fall. Wearable sensors allow a reliable way for daily-life activities ...
    • Home Supporting Smart Systems for Elderly People 

      Boumpa E., Kakarountas A. (2020)
      Smart devices are becoming more and more, over time, familiar tools to our lives. This, coupled with the need to support elderly people in their daily routine and their desire for aging-in-place, has led researchers to ...
    • Portable gait analysis sensor model for Parkinson's disease 

      Piromalis D., Kounelis M., Kolovos D.P., Kokkotis C., Tsatalas T., Bellis G., Tsaopoulos D., Giakas G., Chronakis A., Koutsouraki E., Tsotsolas N., Randhawa P., Patel A. (2022)
      As part of a research project, a small gait analysis device is being developed that will be used outside of home by the patients themselves. Its main purpose will be to record accurate gait measurements in patients with ...
    • A Review of Machine Learning and TinyML in Healthcare 

      Tsoukas V., Boumpa E., Giannakas G., Kakarountas A. (2021)
      Healthcare is the field that can benefit from the large amount of raw data generated from portable and wearable devices. This data must be sent to the Cloud for processing due to the computationally intensive nature of ...
    • Security and Privacy Concerns for Healthcare Wearable Devices and Emerging Alternative Approaches 

      Boumpa E., Tsoukas V., Gkogkidis A., Spathoulas G., Kakarountas A. (2022)
      The wide use of wearable devices rises a lot of concerns about the privacy and security of personal data that are collected and stored by such services. This concern is even higher when such data is produced by healthcare ...