Study on Stumbles of the Elderly from a Depth Perception Dependency Test In this paper, we investigate the relationship between the depth perception and an approaching motion toward an object. We propose the depth perception dependency test, which is the combination of tests of a motion and depth perception based on the situation that an object is placed on the humanxe2x80x99s pathway. Firstly, as the motion test, we set the ball approach motion and asked elderly participants to approach and contact a ball by their foot, because this motion is easy to measure and requires localization skill and motion planning skill. The swingsupport legs positions at the toeoff time of the swing leg just before contacting the ball was analyzed. Secondly, as the depth perception test, the pseudo3D image test was proposed. The coordinate transformation model for the calculation of the depth perception ability was also proposed. Through the proposed test and the proposed model, it was clarified that the participants who are regarded as perceiving the strong visual illusion perceive the objects closer than its real position, and their swing leg toe off positions in the ball approaching motion were significantly farther than other participants. Thus, it can be concluded that there was a relationship between the depth perception and the approaching motion that is thought to be a higher risk of stumbles.

Evaluation Of Physical Therapy Through Analysis Of Depth Images The support through robots in orthopaedic rehabilitation is an opportunity to relieve physiotherapists. However, to be able to provide a control in the robotpatient cooperation in the therapy process a certain standard in interpreting the exercise has to be established. In this paper we present an evaluation approach of the health subject performance in a tibiofemoral rehabilitation on the example of squat exercises. The proposed method utilizes only depth images for the performance evaluation and any humanrobot interaction system for the performance correction. Thus, this method can be easily applied to a mobile service robot in the robotaided physical therapy. The patient is observed while performing the exercise and the motion is evaluated and segmented using Motion History Images. Concrete, depth images are used to monitor local points of interest on the performer during the exercise. The proposed approach was evaluated on custom image sequences with a multitude of varying subjects and shows the suitable performance for assisting in the correctness of the exercise execution.