Erica Chen, Young Yul Kim, Ethan Heng, Jason Liu, Tianyi Yao, Romeo Garza
Various devices on the market assess the functional dexterity (Functional Dexterity Test) of Cerebral Palsy patients. However, none of them are suitable for everyday clinical use; they are either too expensive and immobile, or they lack in accuracy. Our project aims to design and implement a lightweight, portable, and reliable motion path tracking and analyzing device that is accurate enough for clinical use. Our device should achieve 3 key functionalities: object tracking, 3D location calculation, and motion path reconstruction. During FDT, patients pick up a peg, rotate it, and place it back in a certain location. Throughout the process, our device recognizes the peg the patient is holding, calculates the 3D location of the peg, and reconstructs the motion path. We incorporate the Microsoft Kinect with the inertial measurement units to measure the position, and the linear and rotational velocities. The inertial measurement units inside the peg transmit data wirelessly using Wi-Fi, and the data of the Kinect and the IMU are statistically processed to accurately predict the actual motion path taken. The resulting motion path from the given data is successfully close to the actual path within 1 cm. Even when some intermediate points are missing, the predicted values from the statistical processing are within 3cm from the actual path. This project suggests a potential solution for a clinically viable assessment system at a much lower price than the existing solutions. In the future, this project will allow the quantitative analysis of the resulting parameters. These may be research further for their relevance to the disease and its treatment.