IoMT-based biomedical measurement systems for healthcare monitoring: a review

Biomedical measurement systems (BMS) have provided new solutions for healthcare monitoring and the diagnosis of various chronic diseases. With a growing demand for BMS in the field of medical applications, researchers are focusing on advancing these systems, including Internet of Medical Things (IoMT)-based BMS, with the aim of improving bioprocesses, healthcare systems and technologies for biomedical equipment. This paper presents an overview of recent activities towards the development of IoMT-based BMS for various healthcare applications. Different methods and approaches used in the development of these systems are presented and discussed, taking into account some metrological aspects related to the requirement for accuracy, reliability and calibration. The presented IoMT-based BMS are applied to healthcare applications concerning, in particular, heart, brain and blood sugar diseases as well as internal body sound and blood pressure measurements. Finally, the paper provides a discussion about the shortcomings and challenges that need to be addressed along with some possible directions for future research activities.</p

Smart system and mobile interface for healthcare: stress and diabetes

In this thesis, a system with multi-channel measurement capabilities was designed and implemented, associated with the monitoring of stress levels, through a proposed algorithm that correlates heart rate, respiratory rate, and galvanic skin response. Experimental validation tests were carried out, as well as experiments with patients suffering from diabetes. To this end, measurements were made not only of stress-related parameters, but also of parameters such as blood glucose levels and blood pressure levels, seeking to extract correlations between stress and diabetes status. In addition, body temperature was another parameter acquired, in order to assess its importance and relation to stress and diabetes. The proposed multichannel system also features RFID technology for authentication purposes, as well as Wi-Fi access for internet connection and storage of the acquired data in a database structured for that purpose, thus enabling remote access. To allow the assessment of stress levels and diabetes progress, a mobile application was also developed, which also allows the visualisation of the analysed data.In this thesis, a system with multi-channel measurement capabilities was designed and implemented, associated with the monitoring of stress levels, through a proposed algorithm that correlates heart rate, respiratory rate, and galvanic skin response. Experimental validation tests were carried out, as well as experiments with patients suffering from diabetes. To this end, measurements were made not only of stress-related parameters, but also of parameters such as blood glucose levels and blood pressure levels, seeking to extract correlations between stress and diabetes status. In addition, body temperature was another parameter acquired, in order to assess its importance and relation to stress and diabetes. The proposed multichannel system also features RFID technology for authentication purposes, as well as Wi-Fi access for internet connection and storage of the acquired data in a database structured for that purpose, thus enabling remote access. To allow the assessment of stress levels and diabetes progress, a mobile application was also developed, which also allows the visualisation of the analysed data