## 4 Discussion  
We developed an automated analysis program for behavioral patterns of non-human primates on the basis of depth image video. The program developed in this study was able to measure selected behavioral patterns of non-human primates in a home cage with a single low-cost depth image camera. The program measured \"sitting\" and \"standing\" according to the information of the depth image, and measured \"pacing\" according to the movement of the center of objects. Non-human primates are important experimental models for a wide range of scientific fields. Therefore, conducting a quantitative analysis of their behavior is of great relevance. Since primates move in three-dimensional space, have joints that move freely, and use hands, motion capture data using conventional methods are consequently very difficult to analyze. Recently, markerless motion capture systems have been developed not only for humans, but also for various experimental animals, such as flies, mice, and rats [9, 10, 20, 21, 26, 27]. In previous studies, motion capture of non-human primates was achieved using a Kinect camera and skeleton image [9]. Although researcher intervention was necessary, the motion capture of primates was effectively accomplished using this method. However, these studies had the disadvantage of requiring a large number of  
Figure 7: Comparison of measurement analysis from the automated program against two observers for each subject. cameras and a specific measurement space. To provide an alternative method, this study proposed measuring the behavioral patterns of primates in a private cage in which they were housed with a single depth image camera. In this study, the analysis results of the automated program were not statistically different from those measured by the two observers. Therefore, our automated program is highly reliable for measuring and classifying selected behaviors of non-human primate in their home cages. Behavioral research is also important in many studies of degenerative brain diseases [28]. In many diseases, symptoms related to behavior, such as hyperactivity, bradykinesia, tremor, and gait disorder, progressively emerge. When developing animal models of disease, it is crucial to reproduce behavioral symptoms similar to that of humans, and it is also important to quantitatively evaluate the symptoms. These behavioral symptoms are generally diagnosed through questionnaires or observer evaluations in humans. However, since these methods are not applicable to primates, a method of evaluating behaviors that reflects the emotions and intentions of primates is needed. In many previous studies, behavioral evaluations were performed to assess the motor and cognitive abilities of animal models, and, in some cases, behavioral measurement results were used as an indicator of modeling [4, 5, 29]. Our automated program correctly classified selected behavior, and may be used as a powerful evaluation tool in disease models, such as Parkinson's and ataxia, characterized by prominent behavioral symptoms. Moreover, since our cost effective system is a relatively simple and easy to install on each cage, one of applications would be monitoring multiple cages simultaneously in a large animal facility. The automated program developed in this study could not measure the small movements of body parts, such as the hands or head. The program categorized and measured the selected large movements such as sitting, standing, pacing based on the height information obtained from the depth image and the movement speed of the center of an object. In addition, it is not able to measure the rotation of an object using the automated program in this study since the algorithm in the program tracks and only calculates the center of the object. To classify a rotation in the further study, it is necessary to detect the overall shape of an object and measure the relative movement of the front with regard to the tail. In addition, this automated program was limited in that only a single object could be measured at a time.