A Novel Reading and Writing Posture Reminding System based on Kalman Filtering Preprocessing and Neural Network Classification

Nowadays, teenagers’ vision and cervical health are largely affected by their sitting posture but most of them don’t get into good sitting habits. With the development of wearable smart devices, we have come up with a more effective solution to this problem. A posture reminding system designed with two kinds of sensors and processor Arduino is introduced in this paper. We detect attitude angle and distance from torso to desk using two sensors and send the data to a microprocessor. Then by using Kalman filtering algorithm, we realize the data fusion analysis. To make our device smarter, we apply Genetic Algorithm-Back Propagation neural network for posture classification which shows a higher accuracy compared to traditional classification algorithms. Trained by hundreds of sets of data, the accuracy of our system has reached 99.58% which shows this classification scheme is very effective.