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

Author

Zhu, Chun ; Cheng, Qi ; Sheng, Weihua

Author_Institution

Sch. of Electr. & Comput. Eng., Oklahoma State Univ., Stillwater, OK

fYear

2008

fDate

23-26 Aug. 2008

Firstpage

253

Lastpage

258

Abstract

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.

Keywords

gesture recognition; hidden Markov models; home automation; intelligent sensors; hand gesture classification; hierarchical hidden Markov model; human intention recognition; single inertial sensor; smart assisted living system; Design engineering; Hidden Markov models; Human computer interaction; Human robot interaction; Humanoid robots; Intelligent robots; Mobile robots; Positron emission tomography; Senior citizens; Wearable sensors;

fLanguage

English

Publisher

ieee

Conference_Titel

Automation Science and Engineering, 2008. CASE 2008. IEEE International Conference on

Conference_Location

Arlington, VA

Print_ISBN

978-1-4244-2022-3

Electronic_ISBN

978-1-4244-2023-0

Type

conf

DOI

10.1109/COASE.2008.4626513

Filename

4626513