Kalman Hidden Markov Model Detect User Gesture on Proximity Capacitive Sensor

This paper presented the Kalman Hidden Markov Model detect user gesture on proximity capacitive sensor. The human interactive gesture signal analyses have been a research topic smart home fields that algorithms build in local device to recognize real time. The Kalman filter algorithms have been a research topic in prediction signal, and Hidden Markov Model also is a dynamic recognition model to object identification and classification. This paper integrated Kalman filter and Hidden Markov Model to detect user gesture in proximity capacitive sensor. The features of Hidden Markov Model used probability concept train and learn identification model, and Kalman filter optimal predicted Hidden Markov Model results. Therefore, the Kalman Hidden Markov Model methods to identify user gesture has satisfactory response.