PhD thesis defense to be held on September 14, 2023, at 13:30 (Multimedia Amphitheater, NTUA Central Library)

Picture Credit: Dimitrios Karagiannis

Thesis title: Development of Low-Power Devices for the Internet of Medical Things (IoMT)

Abstract: The subject of the present PhD thesis is the development of low-power devices for the Internet of Medical Things (IoMT) that support remote interaction with healthcare professionals, and collection of patients’ health data. The software and hardware of these devices have been developed aiming at low-power consumption in order to achieve improved user experience and patient compliance.
First, a smart pillbox that manages and stores medication is proposed aiming to support medication adherence, as patients usually deviate from their prescribed treatment. The foldable design and the low-power operation of the proposed pillbox connected with the IoMT platform, enable portability, continuous support and remote treatment adjustments. With photos provided by the patient, using a camera integrated in the 3D printed pillbox, dangerous interactions between drugs included in the treatment with other drugs, food, or supplements that the patient may consume can be detected and avoided. Patients can send a video to a smartphone app, describing their symptoms in order to report adverse drug reactions during treatment. Post analysis of the video by cloud services can lead to useful keywords extraction. The medication adherence improvement provided by the platform was evaluated through an experimental procedure in which participants used the developed IoMT pillbox and a dummy pillbox. During both cases, the participants followed a dense medication schedule including remote treatment adjustments. The experimental procedure results demonstrated excellent user acceptance. The comparison of errors (wrong or no pill intake) between IoMT and dummy pillbox did not demonstrate any statistically significant difference, but the total delay of pill intake was higher with the dummy pillbox.
Moreover, this PhD thesis suggests an IoMT fall detection device that has been developed with hardware/software co-design in order to achieve minimum power consumption during operation. The operation algorithm of the device manages embedded functionalities of the integrated accelerometer and enables the fall detection while the rest of the circuit is turned off. This IoMT platform utilizes cloud services that provide remote information in the event of a patient fall. Compared with similar low-power implementations that enable fall detection, the proposed device operates with Wi-Fi connection, without the need of a local server or extra equipment. Moreover, the platform supports a notification mechanism during fall detection, a cancelation mechanism of the emergency signal and battery monitoring for continuous device operation.

Supervisor: Professor Konstantina S. Nikita

PhD Student: Dimitrios Karagiannis