Paper Info
Title
An Assistive Body Sensor Network Glove for Speech- and Hearing-Impaired Disabilities
Abstract
This paper presents a hand-gesture based interface for facilitating communication among speech- and hearing-impaired disabilities. In the system, a wireless sensor glove equipped with five flex sensors and a 3D accelerometer is used as the input device. By integrating the speech synthesizer onto an automatic gesture recognition system, user's hand gestures can be translated into sounds. In this study, we proposed a hierarchical gesture recognition framework based on the combined use of multivariate Gaussian distribution, bigram and a set of rules for model and feature set selection, deriving from a detailed analysis of misclassified gestures in the confusion matrix. To illustrate the practical use of the framework, a gesture recognition experiment has been conducted on American Sign Language (ASL) finger spelling gestures with two additional gestures representing space and full stop. The recognition model has been validated on the pangram "The quick brown fox jumps over the lazy dog.".
Year
DOI
Venue
2011
10.1109/BSN.2011.13
Body Sensor Networks
Keywords
Field
DocType
assistive body sensor network,practical use,additional gesture,automatic gesture recognition system,hearing-impaired disabilities,gesture recognition experiment,speech synthesizer,hand gesture,combined use,finger spelling gesture,hierarchical gesture recognition framework,recognition model,speech recognition,confusion matrix,input device,gaussian distribution,three dimensional,speech,accuracy,multivariate gaussian distribution,gesture recognition,speech synthesis
Speech synthesis,Confusion matrix,Gesture,Computer science,Gesture recognition,Speech recognition,Bigram,American Sign Language,Wireless sensor network,Input device
Conference
ISBN
Citations 
PageRank 
978-0-7695-4431-1
8
0.68
References 
Authors
6
3
Name
Order
Citations
PageRank
Satjakarn Vutinuntakasame180.68
Jaijongrak, V.-R.280.68
Surapa Thiemjarus319215.64