LoFall: LoRa-Based Long-Range Through-Wall Fall Detection.

Fall detection is an essential measure for the safety of elders. While traditional contact-based methods support acceptable detection performance, the recent advance in wireless sensing could enable contact-free fall detection. However, two severe limitations are short sensing range and weak through-wall capability, which hampers wide applications in smart homes. This paper proposes a novel system LoFall, which is the first time to utilize the LoRa signal to realize contact-free long-range through-wall fall detection. We address unique technical challenges, such as proposing a novel strategy of candidate signal search to reduce the calculation time of fall detection and designing a weighted feature fusion algorithm based on fuzzy entropy to improve the accuracy of through-wall fall detection. Comprehensive experiments are conducted to evaluate LoFall. Results show that it can achieve a total accuracy of 93.3% for through-wall fall detection, and support the furthest detection range of up to 10 m.