Biosensor –Based vital signs data aggregation and analytics for monitoring of patients in Internet of Medical Things (IoMT) enabled e-healthcare platform

Abstract

Abstract Lack of proper patient health monitoring and data aggregation scheme in healthcare facilities has become an issue of serious concern the world over. Biosensors have become a handy way for the transmission of data from patients to healthcare providers. The use of Biosensors is also an innovation in healthcare management which involves observing vital physiological signs of patients with the aim of predicting ailments to mitigate them and prevent acute complications. In this study, a system architecture for proper monitoring of patients’ health using Internet of Medical things (IoMT) as an approach is developed. The Design Science research methodology was adopted in this research. The methodology involves the construction and evaluation of the artefacts that address a significantly recognized problem. In the adopted approach, real time data are sent to a local server via communication channels (Wi-Fi technology) and then transmitted to the IoT server via a designated network using a Wi-Fi module. For a robust transmission of physiological parameters to the cloud, a Blynk IoT- server was used as platform. Two main sensors DS18B20 an AD8232 ECG were used in measuring body temperature and heart rate respectively, with XAMPP server as the local server platform. Our results include a developed prototype and a mechanism where real-time numerical data is transmitted to the report platform which is later transformed into ordered numbers. The innovation in this work involves reading real time data from sensors attached to patients in IoMT-enabled environments and using a simple linear regression model to convert these real time data to ordered numbers which indicate severity of the physiological signals. These ordered numbers are transformed to visuals to enable ease of view. To the best of our knowledge, this approach has not been implemented by previous research studies. Based on our findings, we recommend that: the prototype system be deployed in healthcare facilities and the designed web applications be plugged into existing web domains of hospitals to enable timely intervention by the medical experts.