Design and Evaluation of Individualized Rehabilitation Program Based on Intelligent Monitoring System

With the increasing demand for children’s rehabilitation, traditional rehabilitation treatment methods are unable to meet the needs in terms of personalization and real-time feedback, making it difficult to continuously optimize and quantify the treatment effect. To address this problem, this study proposes a personalized rehabilitation program that combines an intelligent monitoring and feedback system. First, the system uses accelerometers and bioelectric sensors to monitor children’s athletic performance in real time, recording movement trajectories, gait analysis, and muscle activity. Through Bluetooth technology, the monitoring data is instantly transmitted to the cloud platform for processing. Then, the data is deeply analyzed using Convolutional Neural Network (CNN) and Long Short-Term Memory Network (LSTM) to evaluate the children’s rehabilitation progress and generate personalized treatment recommendations. Based on these analysis results, the system provides real-time feedback to children and therapists through voice reminders and image guidance, helping them adjust their rehabilitation strategies in a timely manner. The final experimental results showed that the experimental group using the intelligent monitoring and feedback system had significant improvements in athletic ability indicators such as cadence, stride, gait cycle and exercise intensity. The cadence increased from 70 steps/min to 96 steps/min, the stride length increased from 0.6 m to 0.84 m, the gait cycle shortened from 1.2 s to 1.02 s, and the exercise intensity increased significantly. In terms of treatment compliance, the experimental group’s compliance increased from 60% to 90%, while the control group’s compliance increased from 65% to 75%. In addition, the experimental group’s mental health score increased from 45 points to 70 points, and feedback participation increased from 60% to 85%. The above data concluded that personalized rehabilitation programs based on intelligent monitoring and feedback systems have significant advantages in improving children’s motor skills, enhancing treatment compliance, and improving mental health, demonstrating high clinical application value and potential.