Analysis of intentional head gestures to assist computer access by physically disabled people.
Any human-computer interface requires both a means of transducing information flowing from the person and a way of classifying this information in a form that can be used by an application program. Since several interface devices exploit the head movements of disabled people to control computers, this paper includes a discussion of existing technologies based on head movements. As an alternative to simple techniques based on pointing to classify this information, this paper studies the possibility of using a combination of pointing and movement gestures to control an application program. By using hidden Markov models to classify movements into 'yes', 'no' and spurious gestures, it was possible to control a simple graphics application program. Subsequent analysis showed that the hidden Markov models achieved a 74% success rate.
Harwin
W S
WS
Cambridge University Engineering Department, UK.
Jackson
R D
RD
D000328:Adult; D002547:Cerebral Palsy / Q000534:rehabilitation; D003143:Communication Devices for People with Disabilities; D003196:Computer Graphics; D005260:Female; D005868:Gestures; D006257:Head; D006801:Humans; D007697:Kinesics; D008390:Markov Chains; D015588:Observer Variation; D012656:Self-Help Devices; D012815:Signal Processing, Computer-Assisted; D012984:Software; D014159:Transducers; D014584:User-Computer Interface