Comparing Wrist Movement Analysis Technologies

Abstract: The wrist is a body part that can be used during repetitive movements in many work environments. There is a need to measure these movements in order to notice harmful repetitive movements in advance. There are many different ways to measure these movements, such as with the use of a depth camera. The goal of this study is to determine if this can be done with high precision compared to other technologies. In order to determine this, an application was created that used several different technologies and libraries to track and pinpoint the hand’s and forearm’s location in each frame. With these locations, together with timestamps from the frames, the angular velocity of the wrist could be calculated. The recordings were made in several different test cases with factors such as background, clothes and lighting changing in each test. In order to compare the depth cameras values, a golden standard had to be set. The depth camera’s recorded values were compared to the golden standard’s recorded values by displaying the values on a graph and by calculating the root mean squared error as well as the mean absolute error. The results indicated that a depth camera can be used to measure wrist movements relatively accurately, even with more advanced movements relative to this study. The result also showed that the depth camera had problems in some test cases.