Fall prediction and prevention using miniature mm-wave radar sensors for elderly care - Fjordbøge,Phoenix; Onufriciuc,Cristiana Adelina (2025)
100 000 elderly fall each year, costing the healthcare system up to 750 million SEK. Beyond the financial part, these accidents could lead to serious injuries such as head trauma or hip replacements, and in the worst case, even death. This project aims to find a preventive technique that will make life easier for the elderly while saving money and resources for society. The aim is to gather data and create a device that can alert users of fall-related situations and inform them when it is safe to take a step. Different scenarios have already been covered in previous iterations of this study, but this one focuses on stair ascent, decline descent, and transitions between varying surfaces. To accomplish this, a mm-wave radar was used to gather data. The sensor was placed in two positions, downward and forward, and these orientations were used for each area of research. The results showed that the sensor could be used to detect optimal foot elevation during stair ascent, and it could also detect surface transitions. Although further testing is needed to evaluate if it could be used to help with declines. In conclusion, a predictive model could be developed using the data obtained from stair ascent and surface transitions to help minimize falling in these scenarios.
Keywords: Fall prediction; Fall prevention; Bachelor's thesis; mm-wave radar sensor