Smart home solutions to support the healthcare of older adults and individuals with disabilities demand reliable and non-invasive sensors.mmWave radar offers a promising alternative to traditional sensors due to its privacy-preserving nature and resilience to environmental conditions.This thesis evaluates the feasibility of mmWave radar-based systems for healthcare-oriented smart home monitoring. This includes evaluating mmWave radar technology and the systems implemented for distinct applications for smart home-based healthcare. The study was conducted in the \ac{HINT} environment using the \ac{TI} IWR6843ISK radar evaluation board. The developed systems targeted functional, safety, security, social, and physiological health monitoring categories, implementing applications for localization, human activity recognition, fall detection, intruder detection, visitor detection and identification, and heart and breath rate measurement.

An updated benchmark model was adopted to comprehensively evaluate the implemented radar-based systems, focusing on sensor features and system-level performance. While demonstrating the potential of the selected mmWave radar, the results highlighted certain limitations.For instance, accurate heart and breath rate monitoring requires specific positioning and deeper chest movements. Applications like human activity recognition and visitor identification, which use deep learning models, require standardization in data collection and have generalization issues. Additionally, the limited field of view of the radar system hinders coverage, requiring multiple units for larger environments. The accuracy of safety systems like fall detection can be improved by implementing better algorithms or using generalized machine-learning techniques. The study also highlights difficulties distinguishing between multiple individuals, mainly when they are close to each other. Additionally, the accuracy of all the systems was less near the boundaries of the radar's field of view.

Hence, this study highlights that mmWave radar technology is feasible for smart home healthcare monitoring while identifying areas requiring further research and development. Future advancements in radar technology and data analysis techniques could address these limitations, paving the way for more robust and comprehensive solutions.