Improved leg tracking with data association considering gait phase during turning motion in walk tests

Falling is a common problem in the growing elderly population and fall-risk assessment systems are needed for community-based fall prevention programs. In particular, the timed up & go test (TUG) is the clinical test most often used to evaluate elderly individual ambulatory ability in many clinical institutions or local communities. This paper presents an improved leg tracking method using a laser range sensor (LRS) for a gait measurement system to evaluate the motor function in walk tests such as TUG. The system tracks both legs and measures the trajectory of both legs. However, both legs might be close to each other and one leg might be hidden from the sensor. This is especially the case during the turning motion in the TUG, where the time that a leg is hidden from the LRS is longer than that during straight walking and the moving direction rapidly changes. These situations are likely to lead to false tracking and deteriorate the measurement accuracy of the leg positions. To solve these problems, a novel data association method considering the gait phase is proposed. From the experimental results with young people, we confirm that the proposed methods can reduce the chances of false tracking. In addition, we verify the measurement accuracy of the leg trajectory compared with a three-dimensional motion analysis system (VICON).