Design And Application Of Smart Gesture Recognition Gloves Based On STM32 Single Chip Computer

With the development of technology and the increase of people's needs,the way of human-computer interaction technology has gradually changed from computer-centric to human-centric.The research of gesture recognition technology has received more and more attention in the field of human-computer interaction.It has become a hot research topic.As an important human-computer interaction method,gesture recognition has broad potential application scenarios and has important research significance.Based on the principles of convenience,reliability,real-time,and stability,this paper uses modular design ideas to design a smart glove based on sensor gesture recognition.In the system,Flex2.2 curvature sensor and MPU-6050 sensor are used to collect finger bending,acceleration and angular velocity information,combine the filtering algorithm to smooth the data at the signal acquisition end.Then the gesture data features are extracted,and the Zigbee wireless transmission module sends the data to the gesture recognition terminal for data fusion.Finally compare with the gesture library to realize the recognition of gestures.And the upper computer of the music player was designed as an application platform.The gesture recognition result is used as a control instruction to perform operations such as track selection,switching,play/pause,and volume adjustment on the music player.The hardware and software implementations of the smart glove system are introduced in detail in the paper.The main work includes device selection,sensor installation,hardware system scheme design and algorithm design based on curvature sensor,MPU-6050 sensor gesture recognition system.In order to improve the recognition effect,this paper designs a regulated power supply and a 50 Hz notch filter to reduce the influence of noise signals on the result of gesture recognition.At the same time,the average filtering algorithm is used to smooth the data,and the number of peaks and valleys of the data is proposed as the feature vector.And combined with Kalman filter algorithm to data fusion of acceleration and angular velocity information.Through the analysis of the experimental data of the designed smart glove system,it was verified that the smart gesture recognition glove based on the STM32 single-chip microcomputer has a good recognition effect,with a recognition rate of over 85% and good stability.It can be used to solve the problem of communication barriers for deaf-mute people.In addition,the system has the characteristics of low cost and flexible use.It can be applied to a wide range of scenarios,with high robustness and scalability.Finally,the follow-up research plan is proposed.