Hand-eye coordination assessment using leap motion

• Main Author: Bacani, Rainiell Bugay
• Format: text
• Language: English
• Published: Animo Repository 2022
• Subjects: Eye-hand coordination—Computer programs; Electrical and Computer Engineering
• Online Access: https://animorepository.dlsu.edu.ph/etdm_ece/14; https://animorepository.dlsu.edu.ph/cgi/viewcontent.cgi?article=1011&context=etdm_ece
• Institution: De La Salle University

Hand-eye coordination (HEC) is one of the basic skills people use in their everyday lives. However, existing methods of HEC assessment can be stressful, painful, and costly. This paper proposed an HEC assessment system using a hand-tracking device called Leap Motion as an alternative to test hand-eye coordination. A Windows-based application was developed using Unity platform, taking inspiration from existing and scientifically-proven computer-based cognitive assessment tools, improved by Leap Motion technology and gamification principles. An experiment was conducted with 30 healthy individuals and six patients with developmental coordination disorder (DCD). They were asked to undergo the assessment using the Leap Motion controller, then using a common mouse device for comparison. The data gathered reached over 0.9 in Cronbach's alpha test which show high correlation and good reliability. Participants with no DCD performed better than the patients with DCD. The difference in scores were more significant when they used the Leap Motion controller, indicating that it can detect problems in hand-eye coordination than the mouse. Majority of the participants found the test experience engaging, motivating, and easy to understand. Future work in the subject can improve the conclusiveness of the results through a more robust implementation with bigger and more focused test groups. Nonetheless, the proposed solution can pave the way for a cheaper and more engaging rehabilitation process.