References
- Christopher and Dana Reeve Foundation. One degree of separation: Paralysis and spinal cord injury in the United States, 2009. [cited, 2011, March 16]:Available at:http://www.christopherreeve.org/site/c.ddJFKRNoFiG/b.5091685/k.58BD/One_Degree_of_Separation.htm
- Wyndaele M, Wyndaele JJ. Incidence, prevalence and epidemiology of spinal cord injury: what learns a worldwide literature survey? Spinal Cord 2006;44:523–529.
- Huo X, Ghovanloo M. Evaluation of a wireless wearable tongue – computer interface by individuals with high-level spinal cord injuries. J Neural Eng 2010;7:12.
- Lund ME, Christiensen HV, Caltenco HA, Lontis ER, Bentsen B, Andreasen Struijk LN. Inductive tongue control of powered wheelchairs. Conf Proc IEEE Eng Med Biol Soc 2010;2010:3361–3364.
- Rebsamen B, Burdet E, Teo C, Zeng Q, Guan C, Ang M, Laugier C. A brain control wheelchair with a P300 based BCI and a path following controller, in Proceedings of the International Conference on Biomedical Robotics and Biomechatronics; 2006. pp 1101–1106.
- Yamamoto M, Ikeda T, Sasaki Y. Real-time analog input device using breath pressure for the operation of powered wheelchair, in Proceedings of the International Conference on Robotics and Automation; 2008. pp 3914–3919.
- Plotkin A, Sela L, Weissbrod A, Kahana R, Haviv L, Yeshurun Y, Soroker N, Sobel N. Sniffing enables communication and environmental control for the severely disabled. Proc Natl Acad Sci USA 2010;107:14413–14418.
- Al-Rousan M, Assaleh K. A wavelet- and neural network-based voice system for a smart wheelchair control. J Franklin Inst 2011;348:90–100.
- Simpson RC, Levine SP. Voice control of a powered wheelchair. IEEE Trans Neural Syst Rehabil Eng 2002;10:122–125.
- Nik H. Hum-Power controller for owered wheelchairs, MSc thesis, George Mason University, 2009.
- Furui S. History and development of speech recognition. In Chen F,Jokinen K editors. Speech technology: theory and applications. New York, NY: Springer; 2010. pp 1–18.
- Derosier R, Farber RS. Speech recognition software as an assistive device: a pilot study of user satisfaction and psychosocial impact. Work 2005;25:125–134.
- Sears A, Karat C, Oseitutu K, Karimullah A, Feng J. Productivity, satisfaction, and interaction strategies of individuals with spinal cord injuries and traditional users interacting with speech recognition software. UAIS 2001;1:4–15.
- Judge S, Robertson Z, Hawley M, Enderby P. Speech-driven environmental control systems – a qualitative analysis of users’ perceptions. Disabil Rehabil Assist Technol 2009;4:151–157.
- Statistics Canada, Participation and activity limitation survey 2006: Analytical report, Technical report, Ministry of Industry, Social and Aboriginal Statistics Division, Ottawa, ON (December, 2007).
- Sasou A, Kojima H. Noise robust speech recognition applied to voice-driven wheelchair. EURASIP J ADV SIG PR 2009:8.
- Lancioni G, Lems S. Using a microswitch for vocalization responses with persons with multiple disabilities. Disabil Rehabil 2001;17:209–221.
- Rudzicz F. Towards a noisy-channel model of dysarthria in speech recognition, in Proceedings of the First Workshop on Speech and Language Processing for Assistive Technologies; 2010. pp. 80–88.
- Falk TH, Chan J, Duez P, Teachman G, Chau T. Augmentative communication based on realtime vocal cord vibration detection. IEEE Trans Neural Syst Rehabil Eng 2010;18:159–163.
- Chan J, Falk TH, Teachman G, Morin-McKee J, Chau T. Evaluation of a non-invasive vocal cord vibration switch as an alternative access pathway for an individual with hypotonic cerebral palsy – a case study. Disabil Rehabil Assist Technol 2010;5:69–78.
- Lu E, Falk T, Teachman G, Chau T. Assessing the viability of a vocal cord vibration switch for four children with multiple disabilities. Open Rehabil J, 2010; 3:55–61.
- Lui M, Falk T, Chau T. Development and assessment of a dual-output vocal cord vibration switch for persons with multiple disabilities. Disabil Rehabil Assist Technol 2011, In Press.
- Patel R. Phonatory control in adults with cerebral palsy and severe dysarthria. Augment Altern Commun 2002;18:2–10.
- Schmidt M, Larsen J, Hsiao F-T. Wind noise reduction using non-negative sparse coding, in Proceedings of the IEEE Workshop on Machine Learning for Signal Processing; 2007. pp. 431–436.
- Winkler T, Pronkine S, Bardeli R, Köhler. J. A study of throat microphone performance in automatic speech recognition in motorcycles, in Proceedings of the NAG/DAGA Conference; 2009. pp. 1659–1662.