Human intention recognition in Smart Assisted Living Systems using a Hierarchical Hidden Markov Model

In this paper, we propose a smart assisted living (SAIL) System and design a hierarchical hidden Markov model (HHMM) based algorithm for human intention recognition. We focus on the problem of classifying hand gestures by using a single inertial sensor worn on a finger of the subject. The variation of context information, which is modeled by an HMM is used to improve the accuracy of hand gesture recognition in our previous work. The obtained results prove the effectiveness of our method.

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