WEARABLE-BASED KINEMATIC ANALYSIS OF CRICKET BOWLING

Abstract: This work presents a low-cost wearable sensor system for real-time kinematic analysis of cricket bowling. The system integrates MPU6050 IMU sensors placed on the wrist, elbow, and spine, along with a MAX30100 heart-rate sensor and DHT11 temperature–humidity sensor. Data is captured through an ESP8266 NodeMCU and transmitted to a cloud platform for processing. Machine learning algorithms classify bowling phases and detect technique deviations, while a synchronized 30-FPS camera provides visual verification. A web dashboard displays real-time biomechanics, physiological status, and automated performance reports. The system provides an affordable alternative to high-end motion-capture solutions, supporting injury prevention and performance improvement.

Keywords: Data Visualization, Kinematic Analysis, Machine Learning, Wearable Inertial Sensors, Cloud Storage.