Wearable technology has enormous promise, particularly for data collection for cutting-edge health research, and its popularity has soared in recent years. This study aims to provide IoT-based wearable devices' effectiveness and potential cybersecurity threats to these innovative technologies. Using the PRISMA-2020 (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) methodology, we conducted a scoping study to understand better the application of inexpensive, consumer-grade wearables for health research from a population health viewpoint. Scopus databases yielded a total of 43 articles. Our findings show that academics and research participants are tremendously interested in this technology, but they are also wary about using wearables. These devices are still vulnerable to cybersecurity assaults such as data privacy and security in healthcare. However, blockchain technology is a potential alternative for integrating with IoT-based wearables to ensure data privacy. Furthermore, according to the findings, wearables have an increasingly diverse range of applications, including COVID-19 prediction, fertility tracking, heat-related sickness, pharmacological effects, and psychological therapies; they also include underrepresented populations, such as those with rare diseases. In low-resource environments, there is a lack of research on wearable devices.

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The use of artificial intelligence (AI) in healthcare is rapidly increasing. Digital health start-ups are bringing new digital technologies and services to the market, allowing for cost savings and service improvements in the healthcare sector. However, successful integration of AI into the healthcare ecosystem is required to realise its full potential. A digital ecosystem approach can be used to achieve this integration. Using bibliometric analysis, this research seeks to provide a clear overview of artificial intelligence in the digital healthcare ecosystem by analysing the published literature in the field. A systematic literature search was conducted on an article extracted from the Scopus database related to artificial intelligence in the digital healthcare ecosystem. A search technique was devised in order to collect relevant publications and bibliographic data (e.g., country, research area, sources, and author). The VOS viewer was used to visualise the co-authorship networks of countries as well as the co-occurrence of author keywords (Leiden University). This study is unique in a way that it presents a comprehensive picture of global efforts of the use of artificial intelligence in the healthcare business ecosystem. Academic researchers, policymakers, and healthcare practitioners who wish to collaborate in these areas in the future will benefit from the insights and research directions of this study