Visualizing Wearable Medical Device Research Trends: A Co-occurrence Network-Based Bibliometric Analysis

Abstract

Background. One of the most crucial aspects of someone’s life is health. Therefore, individuals should be conscious about keeping themselves healthy by regular monitoring their health, which can be done with the help of modern medical technologies. Wearable medical devices using wearable sensors are the popular names of emerging technologies in the modern healthcare domain. Aim. This work presents the results of a systematic investigation of extensive research that has occurred for the last two decades in these research streams to provide a comprehensive mapping and temporal distribution of wireless medical device research. Methods. This study presents a relationship between the bibliographic items, their quality, and the quantity representing the most effective research topics on wearable medical devices. The analysis is performed using two useful parameters, namely a bibliometric network and a co-occurrence matrix. Data collection, data standardization, data mapping, and result analysis are the steps involved in the bibliometric analysis technique. In this study, VOSviewer software for bibliometric analysis is applied to the Scopus database. Results. By analysing bibliometric indicators from the Scopus database and using VOSviewer, we represent their distribution in countries, institutions, top researchers, and top journals. Furthermore, we analyse the co-citation of cited authors and the co-occurrence of keywords. The outcomes of the clustering and keyword analysis indicate that the research domain primarily focuses on the Internet of Things, machine learning, wearable sensors, mobile health, electrocardiogram, etc. Conclusions. Statistical investigation in association with the visual exploration presented in this article provides more substantial information than either of them used separately. In the future, this article can illuminate researchers and practitioners to develop a different theory to look at the factors that influence predictability in the research domain of wearable medical devices.