ระบบอัจฉริยะตรวจจับโรคสมองเสื่อมจากตับด้วยเทคนิคการเคาะนิ้ว

Abstract

This engineering project aims to develop a finger movement analysis system based on the Finger Tapping Test (FTT) for the assessment and early screening of Hepatic Encephalopathy (HE). The system records finger tapping videos from participants and processes the video data using Python programming language. Computer Vision techniques combined with MediaPipe are utilized to detect hand landmarks and identify the positions of the thumb and index finger in each frame. The finger position data are used to calculate the distance between fingers and analyze finger tapping patterns, including tapping count, tapping frequency, and movement rhythm consistency. These parameters are applied to compare differences among healthy controls, cirrhosis patients, and patients with Hepatic Encephalopathy. The obtained results can be presented in the form of parameter values and motion graphs. In addition, the system can be used to analyze the relationship between FTT results and the severity of Hepatic Encephalopathy or clinical assessment scores such as the Psychometric Hepatic Encephalopathy Score (PHES), which are important indicators for evaluating