Literature DB >> 22875236

Mobile voice health monitoring using a wearable accelerometer sensor and a smartphone platform.

Daryush D Mehta1, Matías Zañartu, Shengran W Feng, Harold A Cheyne, Robert E Hillman.   

Abstract

Many common voice disorders are chronic or recurring conditions that are likely to result from faulty and/or abusive patterns of vocal behavior, referred to generically as vocal hyperfunction. An ongoing goal in clinical voice assessment is the development and use of noninvasively derived measures to quantify and track the daily status of vocal hyperfunction so that the diagnosis and treatment of such behaviorally based voice disorders can be improved. This paper reports on the development of a new, versatile, and cost-effective clinical tool for mobile voice monitoring that acquires the high-bandwidth signal from an accelerometer sensor placed on the neck skin above the collarbone. Using a smartphone as the data acquisition platform, the prototype device provides a user-friendly interface for voice use monitoring, daily sensor calibration, and periodic alert capabilities. Pilot data are reported from three vocally normal speakers and three subjects with voice disorders to demonstrate the potential of the device to yield standard measures of fundamental frequency and sound pressure level and model-based glottal airflow properties. The smartphone-based platform enables future clinical studies for the identification of the best set of measures for differentiating between normal and hyperfunctional patterns of voice use.

Entities:  

Mesh:

Year:  2012        PMID: 22875236      PMCID: PMC3539821          DOI: 10.1109/TBME.2012.2207896

Source DB:  PubMed          Journal:  IEEE Trans Biomed Eng        ISSN: 0018-9294            Impact factor:   4.538


  20 in total

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Journal:  J Voice       Date:  2000-12       Impact factor: 2.009

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Authors:  Harold A Cheyne; Helen M Hanson; Ronald P Genereux; Kenneth N Stevens; Robert E Hillman
Journal:  J Speech Lang Hear Res       Date:  2003-12       Impact factor: 2.297

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Journal:  J Acoust Soc Am       Date:  1991-11       Impact factor: 1.840

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Authors:  Julio C Ho; Matías Zañartu; George R Wodicka
Journal:  J Acoust Soc Am       Date:  2011-03       Impact factor: 1.840

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Journal:  J Speech Hear Res       Date:  1989-06

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Journal:  J Speech Hear Res       Date:  1989-06

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Authors:  G R Wodicka; K N Stevens; H L Golub; E G Cravalho; D C Shannon
Journal:  IEEE Trans Biomed Eng       Date:  1989-09       Impact factor: 4.538

9.  Vocal load as measured by the voice accumulator.

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Journal:  Folia Phoniatr Logop       Date:  1995       Impact factor: 0.849

10.  A newly devised speech accumulator.

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Journal:  ORL J Otorhinolaryngol Relat Spec       Date:  1983       Impact factor: 1.538

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  46 in total

1.  Real-time estimation of aerodynamic features for ambulatory voice biofeedback.

Authors:  Andrés F Llico; Matías Zañartu; Agustín J González; George R Wodicka; Daryush D Mehta; Jarrad H Van Stan; Robert E Hillman
Journal:  J Acoust Soc Am       Date:  2015-07       Impact factor: 1.840

2.  Modeling the effects of a posterior glottal opening on vocal fold dynamics with implications for vocal hyperfunction.

Authors:  Matías Zañartu; Gabriel E Galindo; Byron D Erath; Sean D Peterson; George R Wodicka; Robert E Hillman
Journal:  J Acoust Soc Am       Date:  2014-12       Impact factor: 1.840

3.  Automatic speech and singing classification in ambulatory recordings for normal and disordered voices.

Authors:  Andrew J Ortiz; Laura E Toles; Katherine L Marks; Silvia Capobianco; Daryush D Mehta; Robert E Hillman; Jarrad H Van Stan
Journal:  J Acoust Soc Am       Date:  2019-07       Impact factor: 1.840

4.  Learning to detect vocal hyperfunction from ambulatory neck-surface acceleration features: initial results for vocal fold nodules.

Authors:  Marzyeh Ghassemi; Jarrad H Van Stan; Daryush D Mehta; Matías Zañartu; Harold A Cheyne; Robert E Hillman; John V Guttag
Journal:  IEEE Trans Biomed Eng       Date:  2014-06       Impact factor: 4.538

5.  Fundamental frequency, sound pressure level and vocal dose of a vocal loading test in comparison to a real teaching situation.

Authors:  Matthias Echternach; Manfred Nusseck; Sebastian Dippold; Claudia Spahn; Bernhard Richter
Journal:  Eur Arch Otorhinolaryngol       Date:  2014-07-11       Impact factor: 2.503

6.  Comparison of voice relative fundamental frequency estimates derived from an accelerometer signal and low-pass filtered and unprocessed microphone signals.

Authors:  Yu-An S Lien; Cara E Stepp
Journal:  J Acoust Soc Am       Date:  2014-05       Impact factor: 1.840

7.  Subglottal Impedance-Based Inverse Filtering of Voiced Sounds Using Neck Surface Acceleration.

Authors:  Matías Zañartu; Julio C Ho; Daryush D Mehta; Robert E Hillman; George R Wodicka
Journal:  IEEE Trans Audio Speech Lang Process       Date:  2013-09

8.  Accuracy of the quantities measured by four vocal dosimeters and its uncertainty.

Authors:  Pasquale Bottalico; Ivano Ipsaro Passione; Arianna Astolfi; Alessio Carullo; Eric J Hunter
Journal:  J Acoust Soc Am       Date:  2018-03       Impact factor: 1.840

9.  The Effect of Voice Ambulatory Biofeedback on the Daily Performance and Retention of a Modified Vocal Motor Behavior in Participants With Normal Voices.

Authors:  Jarrad H Van Stan; Daryush D Mehta; Robert E Hillman
Journal:  J Speech Lang Hear Res       Date:  2015-06       Impact factor: 2.297

10.  Relationships between vocal function measures derived from an acoustic microphone and a subglottal neck-surface accelerometer.

Authors:  Daryush D Mehta; Jarrad H Van Stan; Robert E Hillman
Journal:  IEEE/ACM Trans Audio Speech Lang Process       Date:  2016-01-11
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