Motion-Fi$^+$+: Recognizing and Counting Repetitive Motions With Wireless Backscattering

Driven by a wide range of real-world applications, several ground-breaking RF-based motion-recognition systems were proposed to detect and/or recognize macro/micro human movements. These systems often suffer from various interferences caused by multiple-users moving simultaneously, resulting in extremely low recognition accuracy. Even if the repetitive motions are fairly well detectable through the wireless signals in theory, in reality they get blended into various other system noises during the motion. Moreover, irregular motion patterns among users will lead to expensive computation cost for motion recognition. To tackle these challenges, we propose a novel wireless sensing system, called
Motion-Fi$\ ^+$+
, which marries battery-free wireless backscattering and device-free sensing in one clean sheet.
Motion-Fi$\ ^+$+
is an accurate, interference tolerable motion-recognition system, which counts repetitive motions without using scenario-dependent templates or profiles and enables multi-user performing certain motions simultaneously because of the relatively short transmission range of backscattered signals and dedicated signal separation method. We implement a backscattering wireless platform to validate our design in various scenarios for over 6 months when different persons, distances and orientations are incorporated. In our experiments, the periodicity in motions could be recognized without any learning or training process, and the accuracy of counting such motions can be achieved within 5 percent count error. With little efforts in learning the patterns, our method could achieve 95.2 percent motion-recognition accuracy for a variety of 7 typical motions. Moreover, by leveraging the periodicity of motions, the recognition accuracy could be further improved to nearly 100 percent with only three repetitions. Our experiments also show that the motions of multiple persons separating by around
$ 2$
meters cause little accuracy reduction in the counting process.