Proceedings on Automation in Medical Engineering
Vol. 3 No. 1 (2026): Proc AUTOMED
A novel validation method for high-precision IMU-based handwriting trace reconstruction
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Copyright (c) 2026 Proceedings on Automation in Medical Engineering
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Abstract
The accurate reconstruction of handwriting gestures is crucial for both clinical and research applications. This study validates a Sensorized Ink Pen (SIP) reconstruction algorithm using an electromagnetic sensor as ground truth. Orientation, acceleration, and velocity signals were compared using RMSE metrics. Analyses were performed for “On-Sheet” and “In-Air” movements exhibiting larger discrepancies for rapid “In-Air” movements. Results show that the SIP reconstruction achieves mean positional errors of 3.5 mm. This validation framework ensures reliability for future handwriting-based assessments and machine-learning applications.