IMU-Based Model for Precise Toothbrush Stroke and Orientation Tracking

This paper presents a model designed for precise orientation estimation and stroke distance tracking of toothbrush activity. The model leverages Inertial Measurement Unit (IMU) technology, which includes accelerometers and gyroscopes, to capture detailed motion data during the activity. The proposed Corrective Fusion Filter Technique (CFFT) helps integrate accelerometer and gyroscope data with several corrective steps to estimate orientation precisely, and the combined sensor data accurately measures stroke distance. This filtering method also minimizes sensor noise and drifting issues, enhancing the model's reliability and performance.