A depth sensor is convenient for systematic and comprehensive data collection towards yielding real-time posture and gesture detection that possibly work in automated interventions. Recently, the direct measurement technique by utilizing a depth sensor equipped with a modelling software is the alternative tool to facilitate a real-time DHM (Digital Human Modelling). Microsoft Kinect appears as a low-cost motion sensing device which gathers the 3-D human motion data with real-time data and intervention features. However, the accurate real-time data collecting is necessary due to the object placement which respects to the sensor location in order helps and ensures decreased measurement errors and increased depth resolutions. This study aims to obtain the effective sensor setup according to the devices’ performances by examining its variables (object-to-sensor distance, horizontal field of view (FOV), and light intensity) to reach the acceptable gesture confidence level using a Kinect SDK V2.0. The standing posture with a hand overhead and seating posture with lifted hand were selected as the investigated gestures. An ANOVA analysis was performed to determine if three variables and their interactions were significant factors in the Kinect’s ability to determine the placement set up to the target. The result showed that distance and horizontal FOV were statistically significant variables. Thus, it proposes to place the sensor within 2 or 3 m away from the investigated object and to limit the horizontal FOV to 0 or 10° based on standing posture and 1 or 2 m away from the investigated object and to limit the horizontal FOV to 0 or 20° according to the particular posture – seating posture. Eventually, this proposal could be set as the reference in setting up a direct measurement studio for acquiring the human body movement data.