Real-Time Paddle Stroke Classification and Wireless Monitoring in Open Water Using Wearable Inertial Nodes.

ABSTRACT: This study presents a low-cost wearable system for monitoring and classifying paddle strokes in open-water environments. Building upon our previous work in controlled aquatic and dryland settings, the proposed system consists of ESP32-based embedded nodes equipped with MPU6050 accelerometer-gyroscope sensors. These nodes communicate via the ESP-NOW protocol in a master-slave architecture. With minimal hardware modifications, the system implements gesture classification using Dynamic Time Warping (DTW) to distinguish between left and right paddle strokes. The collected data, including stroke type, count, and motion similarity, are transmitted in real time to a local interface for visualization. Field experiments were conducted on a calm lake using a paddleboard, where users performed a seri

SUBMITTER: Dobra VA 

PROVIDER: S-EPMC12431577 | biostudies-literature | 2025 Aug

REPOSITORIES: biostudies-literature