The scientific literature highlights the significance of human motor variability in understanding motor control, learning, and neurological disorders. Visuomotor tasks in laboratory settings offer a controlled platform for studying motor variability, but the specialized equipment used for these tasks limits their accessibility and generalizability. Thus, this study aimed to develop an accessible, standardized mouse-based task for home-based assessment of motor variability characteristics. Two protocols were conducted: (1) comparing the mouse-based task to a well-established force-sensor lab task (N = 10), and (2) assessing the mouse-based task across various computer setups (N = 31). Results demonstrated high reliability and accuracy of both tasks for the following measures of motor variability: fuzzy entropy and detrended fluctuation analysis (DFA). The mouse-based task exhibited slightly superior absolute reliability, suggesting potential sensitivity advantages for detecting longitudinal changes in motor control. While sampling frequency influenced nonlinear outputs, it did not significantly affect reliability, leading to the choice of 20 Hz for optimal parameter estimation. Correlation analyses revealed that although participants showed different performance during the mouse- and force-sensor-based tasks, their long-term movement adjustment strategies (assessed using the DFA) were similar. In addition, the robustness analysis showed that computer hardware can influence observed variability, with screen size being a key factor. Larger screens may increase error sensitivity and affect variability structure. Overall, the findings highlight the potential of the mouse-based task for home-based motor variability assessment, emphasizing its reliability, accuracy, and adaptability across various computer setups.
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