Real-Time Detection System for Simulating Fracture Healing Status Based on Piezoelectric Vibration Sensors
To address the issues of traditional imaging methods being unable to detect the healing status of fractures in real-time,as well as the difficulties and potential rejection reactions associated with implantable detection methods,a real-time fracture healing status simulation detection system based on a piezoelectric vibration sensor was designed.The system main includes five components:Fracture healing status simulation,vibration module,vibration signal conditioning module,microcontroller control module,and host computer.Vibration signals under different fracture healing states are collected in a simulated environment and then transmitted to the host computer for processing and real-time detection through the microcontroller control module.Additionally,a comparative analysis of several different algorithms including Naive Bayes,decision tree,and random forest ensemble learning was conducted to evaluate their effectiveness in detection and classification.The results indicate that using the random forest ensemble learning algorithm for fracture healing status simulation detection achieves a response time of no more than 0.2 s,with an accuracy of 98.2%.This not only ensures the real-time capability of the system but also enhances the accuracy of the detection and classification process.
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