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1. D. D. Mehta, M. Zañartu, S. W. Feng, H. A. Cheyne II, and R. E. Hillman, “ Mobile voice health monitoring using a wearable accelerometer sensor and a smartphone platform,” IEEE Trans. Biomed. Eng. 59(11), 30903096 (2012).
2. M. Ghassemi, J. H. Van Stan, D. D. Mehta, M. Zañartu, H. A. Cheyne II, R. E. Hillman, and J. V. Guttag, “ Learning to detect vocal hyperfunction from ambulatory neck-surface accelerometer features: Initials results for vocal fold nodules,” IEEE Trans. Biomed. Eng. 61(6), 16681675 (2014).
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6. J. H. Van Stan, D. D. Mehta, and R. E. Hillman, “ The effect of voice ambulatory biofeedback on the daily performance and retention of a modified vocal motor behavior in participants with normal voices,” J. Speech Lang. Hear. Res., in press (2015).
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8. V. Espinoza and M. Zañartu, “ Estudio dináamico de paráametros de filtrado inverso para el seguimiento ambulatorio de la función vocal” (“Dynamic study of inverse filtering parameters for ambulatory monitoring of vocal function”), in IX Congreso Iberoamericano de Acústica, FIA2014, Valdivia, Chile, December 2014.
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The development of ambulatory voice monitoring devices has the potential to improve the diagnosis and treatment of voice disorders. In this proof-of-concept study, real-time biofeedback is incorporated into a smartphone-based platform that records and processes neck surface acceleration. The focus is on utilizing aerodynamic measures of vocal function as a basis for biofeedback. This is done using regressed Z-scores to compare recorded values to normative estimates based on sound pressure level and fundamental frequency. Initial results from the analysis of different voice qualities suggest that accelerometer-based estimates of aerodynamic parameters can be used for real-time ambulatory biofeedback.


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