Surface electromyographic control of a novel phonemic interface for speech synthesis

References

• Alant, E., Life, H., & Harty, M. (2005). Comparison of the learnability and retention between blissymbols and cyberglyphs. International Journal of Language & Communication Disorders, 40, 151–169. doi: 10.1080/13682820400009980.
   PubMed Web of Science ®Google Scholar
• Basmajian, J.V. (1972). Electromyography comes of age. Science, 176, 603–609. doi: 10.1126/science.176.4035.603.
   PubMed Web of Science ®Google Scholar
• Beukelman, D., & Gutmann, M. (1999). Generic message list for AAC users with ALS, from http://aac.unl.edu/ALS_Message_List1.htm..
   Google Scholar
• Beukelman, D.R., Fager, S., Ball, L., & Dietz, A. (2007). AAC for adults with acquired neurological conditions: A review. Augmentative and Alternative Communication, 23, 230–242. doi: 10.1080/07434610701553668.
   PubMed Web of Science ®Google Scholar
• Beukelman, D.R., & Mirenda, P. (2013). Augmentative & alternative communication: Supporting children & adults with complex communication needs (4th ed.). Baltimore: Paul H. Brookes Pub.
   Google Scholar
• Black, R., Waller, A., Pullin, G., & Abel, E. (2008). Introducing the phonicstick: Preliminary evaluation with seven children. Paper presented at the 13th Biennial Conference of the International Society for Augmentative and Alternative Communication, Montreal, CA.
   Google Scholar
• Brunner, P., Ritaccio, A.L., Emrich, J.F., Bischof, H., & Schalk, G. (2011). Rapid Communication with a “P300” Matrix Speller Using Electrocorticographic Signals (ECoG). Frontiers in Neuroscience, 5. doi: 10.3389/fnins.2011.00005.
   Web of Science ®Google Scholar
• Bryen, D.N. (2008). Vocabulary to support socially-valued adult roles. Augmentative and Alternative Communication, 24, 294–301. doi: 10.1080/07434610802467354.
   PubMed Web of Science ®Google Scholar
• Choi, C., Rim, B.C., & Kim, J. (2011). Development and evaluation of an assistive computer interface by sEMG for individuals with spinal cord injuries. Paper presented at the IEEE International Conference on Rehabilitation Robotics, Zurich. doi: 10.1109/icorr.2011.5975386.
   Google Scholar
• Cler, GJ., Nieto-Castanon, A., Guenther, F.H., & Stepp, C.E. (2014). Surface electromyographic control of speech synthesis. Paper presented at the Proceedings of the 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 26–30 August, Chicago, IL. doi: 10.1109/embc.2014.6944958.
   Google Scholar
• Cler, G.J., & Stepp, C.E. (2015). Discrete vs. Continuous mapping of facial electromyography for human-machine-interface control: Performance and training effects. IEEE Transactions on Neural Systems and Rehabilitation Engineering, 23, 572–580. doi: 10.1109/tnsre.2015.2391054.
   PubMed Web of Science ®Google Scholar
• Epstein, S., Missimer, E., & Betke, M. (2014). Using kernels for a video-based mouse-replacement interface. Personal and Ubiquitous Computing, 18, 47–60. doi: 10.1007/s00779-012-0617-z.
   Web of Science ®Google Scholar
• Fager, S., Bardach, L., Russell, S., & Higginbotham, J. (2012). Access to augmentative and alternative communication: New technologies and clinical decision-making. Journal of Pediatric Rehabilitation Medicine, 5(1), 53.
   PubMedGoogle Scholar
• Frey, L.A., White, Jr K.P., & Hutchison, T.E. (1990). Eye-gaze word processing. IEEE Transactions on Systems, Man and Cybernetics, 20, 944–950. doi: 10.1109/21.105094.
   Web of Science ®Google Scholar
• Guenther, F.H., & Brumberg, J.S. (2011). Brain-machine interfaces for real-time speech synthesis. Paper presented at the Proceedings of the 33rd Annual International Conference of the IEEE Engineering in Medicine and Biology Society, Boston, MA. doi: 10.1109/iembs.2011.6091326.
   Google Scholar
• Higginbotham, D.J., Shane, H., Russell, S., & Caves, K. (2007). Access to AAC: Present, past, and future. Augmentative and Alternative Communication, 23, 243–257. doi: 10.1080/07434610701571058.
   PubMed Web of Science ®Google Scholar
• Hill, N.J., Lal, T.N., Schroder, M., Hinterberger, T., Wilhelm, B., Nijboer, F., … Birbaumer, N. (2006). Classifying EEG and ECoG signals without subject training for fast BCI implementation: comparison of nonparalyzed and completely paralyzed subjects. IEEE Transactions on Neural Systems and Rehabilitation Engineering, 14, 183–186. doi: 10.1109/TNSRE.2006.875548.
   PubMed Web of Science ®Google Scholar
• Huo, X., Wang, J., & Ghovanloo, M. (2008). Introduction and preliminary evaluation of the tongue drive system: Wireless tongue-operated assistive technology for people with little or no upper-limb function. Journal of Rehabilitation Research & Development, 45, 921–930. doi: 10.1682/jrrd.2007.06.0096.
   PubMed Web of Science ®Google Scholar
• Koppenhaver, D.A., & Yoder, D.E. (1992). Literacy issues in persons with severe speech and physical impairments. In R. Ross-Gaylord (Ed.), Issues and research in special education (Vol. 2, pp. 156–201). New York, NY: Teachers College Press, Columbia University.
   Google Scholar
• Kushler, C. (1998). AAC: Using a reduced keyboard. Paper presented at the CSUN '98, Northridge, CA.
   Google Scholar
• Larson, E., Terry, H.P., Canevari, M.M., & Stepp, C.E. (2013). Categorical vowel perception enhances the effectiveness and generalization of auditory feedback in human-machine-interfaces. PLoS One, 8, e59860. doi: 10.1371/journal.pone.0059860.
   PubMed Web of Science ®Google Scholar
• Liu, S.S., Rawicz, A., Rezaei, S., Ma, T., Zhang, C., Lin, K., & Wu, E. (2012). An eye-gaze tracking and human computer interface system for people with ALS and other locked-in diseases. Journal of Medical and Biological Engineering, 32, 37–42. doi: 10.5405/jmbe.836.
   Web of Science ®Google Scholar
• Majaranta, P., MacKenzie, I.S., Aula, A., & Räihä, K.-J. (2006). Effects of feedback and dwell time on eye typing speed and accuracy. Universal Access in the Information Society, 5, 199–208. doi: 10.1007/s10209-006-0034-z.
   Google Scholar
• Nijboer, F., Sellers, E.W., Mellinger, J., Jordan, M.A., Matuz, T., Furdea, A., … Kubler, A. (2008). A P300-based brain-computer interface for people with amyotrophic lateral sclerosis. Clinical Neurophysiology, 119, 1909–1916. doi: 10.1016/j.clinph.2008.03.034.
   PubMed Web of Science ®Google Scholar
• Orhan, U., Hild, K.E., Erdogmus, D., Roark, B., Oken, B., & Fried-Oken, M. (2012). RSVP keyboard: An EEG based typing interface. Paper presented at ICASSP 2012 – 2012 IEEE International Conference on Acoustics, Speech and Signal Processing, March 25–30, Kyoto, Japan. doi: 10.1109/icassp.2012.6287966.
   Google Scholar
• Saxena, S., Nikolic, S., & Popovic, D. (1995). An EMG-controlled grasping system for tetraplegics. Journal of Rehabilitation Research and Development, 32, 17–17.
   Google Scholar
• Sellers, E.W., Krusienski, D.J., McFarland, D.J., Vaughan, T.M., & Wolpaw, J.R. (2006). A P300 event-related potential brain-computer interface (BCI): the effects of matrix size and inter stimulus interval on performance. Biological Psychology, 73, 242–252. doi: 10.1016/j.biopsycho.2006.04.007.
   PubMed Web of Science ®Google Scholar
• Simeral, J.D., Kim, S.P., Black, M.J., Donoghue, J.P., & Hochberg, L.R. (2011). Neural control of cursor trajectory and click by a human with tetraplegia 1000 days after implant of an intracortical microelectrode array. Journal of Neural Engineering, 8, 025027. doi: 10.1088/1741-2560/8/2/025027.
   PubMed Web of Science ®Google Scholar
• Smith, M.M. (2001). Simply a speech impairment? Literacy challenges for individuals with severe congenital speech impairments. International Journal of Disability, Development and Education, 48(4), 331–353. doi: 10.1080/10349120120094257.
   Google Scholar
• Soukoreff, R.W., & MacKenzie, I.S. (2001). Measuring errors in text entry tasks: An application of the Levenshtein string distance statistic. Paper presented at the CHI'01 extended abstracts on Human factors in computing systems. doi: 10.1145/634067.634256.
   Google Scholar
• Trinh, H., Waller, A., Vertanen, K., Kristensson, P.O., & Hanson, V.L. (2012). iSCAN: A phoneme-based predictive communication aid for nonspeaking individuals. Paper presented at the ASSETS’12, Boulder, Colorado. doi: 10.1145/2384916.2384927.
   Google Scholar
• Vernon, S., & Joshi, S.S. (2011). Brain–muscle–computer interface: Mobile-phone prototype development and testing. IEEE Transactions on Information Technology in Biomedicine, 15, 531–538. doi: 10.1109/titb.2011.2153208.
   PubMedGoogle Scholar
• Williams, M.R., & Kirsch, R.F. (2008). Evaluation of head orientation and neck muscle EMG signals as command inputs to a human-computer interface for individuals with high tetraplegia. IEEE Transactions on Neural Systems and Rehabilitation Engineering, 16, 485–496. doi: 10.1109/TNSRE.2008.2006216.
   PubMed Web of Science ®Google Scholar
• Wolpaw, J.R., Birbaumer, N., Heetderks, W.J., McFarland, D.J., Peckham, P.H., Schalk, G., … Vaughan, T.M. (2000). Brain-computer interface technology: A review of the first international meeting. IEEE Transactions on Rehabilitation Engineering, 8, 164–173. doi: 10.1109/tre.2000.847807.
   PubMedGoogle Scholar
• Wolpaw, J.R., Birbaumer, N., McFarland, D.J., Pfurtscheller, G., & Vaughan, T.M. (2002). Brain-computer interfaces for communication and control. Clinical Neurophysiology, 113, 767–791. doi: 10.1016/s1388-2457(02)00057-3.
   PubMed Web of Science ®Google Scholar
• Yorkston, K., Beukelman, D.R., Hakel, M., & Dorsey, M. (2007). Speech Intelligibility Test (SIT) [Computer Software]. Lincoln, NE: Madonna Rehabilitation Hospital.
   Google Scholar