Developing an Analytical Technique Using Finger Motion Data for Forecasting Cognitive Function

Recently, there has been a surge in investigations indicating an association between cognitive functionality and dexterity in hand movements. Nevertheless, research encom-passing the entirety of human fingertip motions has been scarce, and there is an absence of a well-established analyt-ical approach. Our research team has been in the process of devising a system for measuring finger movements that combines image identification with touch panel manipulation. Thus, the objective of this study is to suggest a method for analyzing dexterity in hand movements utilizing the data on fingertip motions procured through our innovative system. Our principal concept revolves around examining irregularly spaced time-based data of fingertip motions and subjecting it to scrutiny using a state-space model. The proposed methodology progresses through a series of steps: (Step 1) Loading and organizing the data. (Step 2) Converting coordinate data. (Step 3) Individually comparing data features. Furthermore, in a case study, we derive data from two types of tapping tasks (specifically, standard tasks and n-back tasks) and offer practical instances of examining four parameters: response time and speed of hand movement, differential distance, and angles. Subsequently, we engage in discussions, delineating differences from pertinent studies and areas in which this methodology could be enhanced. This strategy is anticipated to establish innovative benchmarks for dexterity in hand movements, potentially assisting in the prompt identification of indications of cognitive decline in the elderly.