Track Cyclist Performance Monitoring System Using Wireless Sensor Network

Abstract

The right training programs are an important factor to increase the cycling performance among the professional track cyclist. Over the years, the cyclist performance was based on the feedback from bicycle’s kinematics and physiological condition. The advancement in sensor technologies allows the optimization of the training program; by combining both information from the cyclist’s physiological condition and kinematic data from the bicycle. The physiological conditions such as heart rate variability (HRV) and forehead temperate can be combined with bicycle kinematic data such as speed and distance to provide accurate assessment of the track cyclist’s condition and training program intensity. A system that combines data from physiological signal and bicycle kinematic has been developed for this purpose. Wearable physiological body sensors and bicycle kinematic sensors are deployed using wireless sensor network (WSN). HRV provide using photoplethysmography (PPG) technique that capture signal from cyclist’s finger, which provide 3 % error rate refer to heart rate belt. Data handling and communication was developed based on Zigbee protocol whereby the WSN centralized base-station was supported by two repeater node which was used to extend signal coverage in Velodrome to prevent data losses. With two repeater nodes and adjustment on the routing protocol, the packet drops were reduced from 46 to 3 %. The propagation study was carried out in the Velodrome with environment temperature range from 28 to 30 °C and humidity was observed at 85 %. The optimization of network topology by considering the connectivity among the wireless nodes is crucial in order to reduce data losses.