Abstract. In recent years, the rapid aging of the population and the high incidence of fall accidents have been problems. Although conventional physical function assessments have been conducted by interviews with physicians or physical fitness tests, research and developments have been recently conducted on a system to be used in medical facilities by using motion capture systems or inertial measurement units to enable detailed and easy assessment. However, contact sensors constrain people’s movements during measurements. Furthermore, they may feel nervous during measurement at experimental sites or hospitals, and this causes different movements from usual. Thus, we have been suggesting a physical function assessment system that realizes the measurement of natural daily activities by introducing non-contact sensors into the living space. In conducting physical function evaluation in a living space, it is necessary to consider the set of conditions, such as sensor placement, from the viewpoint of privacy protection. In addition, because of the wide variety of living space designs, the determination of sensor positions is currently tailor-made to take into account measurable motion and privacy, so there is room for optimization. However, to begin with, there are few examples of measurement in actual living spaces, and standards of home-based sensing such as the actual measurable indices, and installation conditions are unclear. Therefore, the purpose of this study was to propose an optimization system for the placement of sensors in the living space for physical function evaluation. We proposed a system that simulates the amount of data on walking motions that can be obtained under each condition and the optimal placement of the RGB-D sensors based on that data. In this study, sensor placement was optimized based on the following three evaluation items: (1) residents do not feel discomfort, (2) walking motions can be measured, and (3) the sensor does not interfere with residents’ walking. The system was validated using floor plan information published in CASAS Smart Home Data sets, and we discussed its usefulness and issues.