COVID-19 was indeed a global epidemic that revolutionized the way of life, especially health-care services. The way health care will be delivered will undergo a dramatic change in the future. The aim is to analyse the increasing usage of health care systems along with digital technology and IoT especially during pandemic.
Design Methodology Approach
This research paper deals with users’ perception and their recommendation status of IoT-based smart health-care monitoring devices based on their perception, experience and level of importance to enhance the quality of life. An effective artificial neural networking (ANN)-based predictive model is designed to classify the user’s perception of usage of IoT-based smart health-care monitoring wearables based on their experience and knowledge.
The model developed has 96.7% accuracy. Among the various predictors chosen as inputs for the model, the findings indicate that self-comfort and trusted data from the device are of high priority. The present study focused only on some common factors derived from previous studies.
Research Limitations Implications
Although the performance of the proposed system was noticed to be good, the size of the sample is also limited to a few responses. Implications for future research and practices are discussed.
This is a novel study that aims to develop an ANN model on analyzing the user’s perception of IoT-based smart health-care wearables with the effect of COVID-19 pandemic. This paper elaborates on the ongoing efforts to restart the health-care services for survivability in the new normal situations.
Ganji, K. and Parimi, S. (2022), "ANN model for users’ perception on IOT based smart healthcare monitoring devices and its impact with the effect of COVID 19", Journal of Science and Technology Policy Management, Vol. 13 No. 1, pp. 6-21. https://doi.org/10.1108/JSTPM-09-2020-0128
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