A Study on Analytical Method of Handwritten Rhythm Lines for Movement Analysis (2) ~Capturing the Zigzag~

Abstract

This study aims to investigate approaches toward automating the analysis of handwritten waveform recordings of “rhythm lines” in the Kestenberg Movement Profile (KMP), a movement analysis method grounded in psychoanalytic theory. Tension Flow Attributes (TFA), one of the analysis categories of KMP, has six items, and in previous studies, a fuzzy set-based feature judgment support tool has been developed to judge four items. In this paper, we focus on the remaining two items, “Flow Adjustment (meandering of lines)” and “Even Flow (parallelism with Neutral Line),” and investigate a method for quantitatively extracting and judging the shape features of the rhythm lines. In the proposed method, an algorithm was introduced to objectively evaluate zigzagging and parallelism by calculating the amount of change, direction, parallelism, and other features from the waveform coordinate data using Microsoft Excel. The results showed that quantitative analysis support is possible and suggested that the proposed method contributes to the establishment of a foundation for objective analysis of all six TFA items.