Evaluating the Impact of Exercise on Arm Tremor in Archers: A Secondary Data Analysis

Abstract

Arm tremor during the aiming phase of archery can undermine shot precision by disrupting the stability of the bow arm. Understanding whether exercise can reduce tremor is therefore relevant for optimizing performance. This study investigates exercise-related modulation of tremor using a publicly accessible motion dataset containing synchronized accelerometer and EMG recordings. A secondary data analysis was conducted on an open-source dataset originally hosted in Mendeley Data and analyzed through a Kaggle computational workflow. Tremor characteristics were examined through descriptive statistics, correlation analysis, and regression-based EMG prediction models. The strongest association was observed between movement sequence—a proxy for exercise progression—and acceleration in the x-axis, showing a moderate negative correlation (r ≈ –0.58), suggesting a decline in tremor amplitude with repeated or continued exercise trials. EMG prediction based on acceleration demonstrated limited accuracy, indicating that neuromuscular activation is only partially explained by kinematic variability. The findings support the premise that structured exercise may enhance upper-limb stability in archery, although limitations inherent to secondary datasets warrant cautious interpretation. This analysis provides quantitative evidence linking exercise to tremor reduction and highlights the potential of open-access biomechanical datasets for advancing sport science research.