Traditional treadmill systems are deficient in human-computer interaction interface design and health data monitoring. This study designs and develops a treadmill health monitoring system based on intelligent sensing technology, which realizes real-time monitoring and evaluation of users’ health status through multi-sensor data acquisition and fusion analysis technology. The research adopts Bluetooth 4.0 technology to establish a wireless transmission network, combines the improved time synchronization algorithm to reduce energy consumption and improve accuracy, and applies the D-S evidence theory and the improved support vector machine algorithm to carry out multi-sensor data fusion and health status analysis. The system can monitor, display and analyze several physiological parameters in real time, such as heart rate, body temperature, blood pressure, pulse and sweat ion concentration. The test results show that the error of the heart rate value measured by the system is within ±5 beats/minute compared with professional sphygmomanometer; the error of the body temperature measurement results is between -0.3℃ and 0.456℃ compared with mercury thermometer; the error of the blood pressure measurement is within ±6mmHg for systolic pressure and ±8mmHg for diastolic pressure compared with professional sphygmomanometer. The experiment proves that the system has high accuracy and reliability, and through the comprehensive monitoring and analysis of multi-physiological parameters, it can effectively improve the health monitoring level during the use of treadmill, and provide users with scientific fitness guidance and health risk warning.
