Abstract: The current medical diseases and infections necessitate advanced medical equipment (medical devices) to bridge the gap between existing and predictable diseases. This has been reached through the integration of traditional medical settings with artificial intelligence (AI). AI simulates human intelligence processes through the use of machines, exclusively known as smart systems. The current pandemic coronavirus (COVID-19) disease was announced by the World Health Organization. The pandemic was alleged for having started in Wuhan in Hubei province in the People’s Republic of China in late 2019. It was during this time that a wider acceptance of AI applications in the medical field was witnessed globally; intelligent technologies and their associated algorithms in the healthcare domain were used to save the individuals who were affected by the virus. This has produced what is now called the artificial intelligence of medical things (AIoMT), which has made it possible to collect, analyze, and interpret an unprecedented amount of patient information for effective healthcare and well-being monitoring through various electronic devices. Through these medical devices (or medical things), artificial intelligence and other key support technologies such as big data, mobile internet, cloud computing, microelectronics, and others have made it possible to process the collected patient data in order to provide better insights, thereby transforming the traditional healthcare into an all-round, efficient, and personalized experience. In this chapter, a comprehensive survey has been done on several electronic devices in the AIoMT. The identified and commonly utilized medical devices have been highlighted including electronic signals for AIoMT sensors. Moreover, AIoMT architecture demonstrates a comprehensive evolution using smart sensors to accumulate, aggregate, and regulate data for smart healthcare structures. The chapter further provides a review of the challenges of electronic devices in the AIoMT, like data security threats, data interoperability, and regulatory concerns, among others, which need to be addressed to improve medical standards of operation for not only medical persons but also patients and other medical stakeholders. Lastly, this chapter highlights open research issues of future research in AIoMT.