Objective Evaluation of Presbyphonia: Spectroacoustic Study on 142 Patients with Praat

Mezzedimi, Chiara; Francesco, Marta Di; Livi, Walter; Spinosi, Maria Carla; Felice, Claudio De

doi:10.1016/j.jvoice.2016.05.022

Cited by 45 publications

(50 citation statements)

References 12 publications

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“…Age of the patients may also be of importance as to acoustic analyses. 34,35 This has also been shown in the present study regarding jitter, shimmer, and NHR. Acoustic measurement absolute values were presently generally scored different among males and females which previously as also have been shown to be the case.…”

Section: E32supporting

confidence: 89%

Acoustic Voice Analysis and Maximum Phonation Time in Relation to Voice Handicap Index Score and Larynx Disease

et al. 2020

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Among larynx disease patients acoustic and MPT analyses segregated with all determined analyses between patients and control conditions except the dysfunctional group, but also to some extent between various patient groups. VHI scores correlated to jitter, shimmer and NHR scores among cancer and degenerative/inflammatory disease patients. Acoustic analyses potentially add information useful to laryngological patient studies.

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Section: E32supporting

confidence: 89%

Acoustic Voice Analysis and Maximum Phonation Time in Relation to Voice Handicap Index Score and Larynx Disease

et al. 2020

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“…Early studies based on the qualitative/perceptual evaluation of voice recordings have demonstrated that physiologic ageing leads to several changes in specific characteristics of the human voice [ 1 ]. Indeed, as a result of physiologic ageing, voices progressively manifest increased breathiness and hoarseness, reduced speech intensity as well as maximum phonation time [ 2 , 3 , 4 , 15 ]. Experimental studies using spectral analysis have confirmed age-related changes in voice by providing new objective measures in the time-domain as well as in the frequency-domain.…”

Section: Discussionmentioning

confidence: 99%

“…Human voice represents a complex biological signal resulting from the dynamic interaction of vocal folds adduction/vibration with pulmonary air emission and flow through resonant structures [ 1 ]. Physiologic ageing leads to specific changes in the anatomy and physiology of all structures involved in the production and modulation of the human voice [ 2 , 3 , 4 , 5 , 6 , 7 , 8 , 9 , 10 , 11 , 12 , 13 , 14 ]. Hence, a possible approach to evaluate the effect of physiological ageing in humans would include the analysis of voice.…”

Section: Introductionmentioning

confidence: 99%

Machine-Learning Analysis of Voice Samples Recorded through Smartphones: The Combined Effect of Ageing and Gender

Asci

Costantini

Leo

et al. 2020

Sensors

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Background: Experimental studies using qualitative or quantitative analysis have demonstrated that the human voice progressively worsens with ageing. These studies, however, have mostly focused on specific voice features without examining their dynamic interaction. To examine the complexity of age-related changes in voice, more advanced techniques based on machine learning have been recently applied to voice recordings but only in a laboratory setting. We here recorded voice samples in a large sample of healthy subjects. To improve the ecological value of our analysis, we collected voice samples directly at home using smartphones. Methods: 138 younger adults (65 males and 73 females, age range: 15–30) and 123 older adults (47 males and 76 females, age range: 40–85) produced a sustained emission of a vowel and a sentence. The recorded voice samples underwent a machine learning analysis through a support vector machine algorithm. Results: The machine learning analysis of voice samples from both speech tasks discriminated between younger and older adults, and between males and females, with high statistical accuracy. Conclusions: By recording voice samples through smartphones in an ecological setting, we demonstrated the combined effect of age and gender on voice. Our machine learning analysis demonstrates the effect of ageing on voice.

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“…4 Furthermore, acoustical characteristics comprise changes of the harmonic and vocal range, tremor, and a number of perturbation parameters such as jitter or shimmer. 5,6 Glottal incompetence is commonly seen as the hallmark of laryngoscopy in presbyphonic patients. The underlying anatomical reason is sarcopenia, the loss of muscle mass, quality, and strength.…”

Section: Introductionmentioning

confidence: 99%

Functional Electrical Stimulation for Presbyphonia: A Prospective Randomized Trial

Gugatschka

Feiner

Mayr³

et al. 2020

The Laryngoscope

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The aim of this prospective study was to examine the effects of transcutaneous functional electrical stimulation (FES) in a group of elderly women with presbyphonia. Study Design: Prospective randomized study. Methods: Fourteen participants were enrolled prospectively and attributed randomly to two different treatment groups, where one group (n = 7) received 8 weeks of training (5 days a week), whereas the other group (n = 7) received 4 weeks of ineffective stimulation, followed by 4 weeks of effective training. Stimulation protocols were established during baseline examination and confirmed with endoscopy to ensure a glottal reaction. Numerous acoustical, vocal, patient-centered, and respiratory parameters were obtained at several time points. Results: Neither 4 weeks nor 8 weeks of functional electrical transcutaneous stimulation led to changes of vocal, acoustical, or respiratory parameters, apart from patient-centered items (Voice Handicap Index 12, Voice-Related Quality of Life), which improved over time. However, there were no differences between the two arms for both items. Conclusions: Transcutaneous FES over 4 weeks and 8 weeks did not lead to significantly improved objective voice and acoustical parameters, which could be caused by the fact that the muscles of interest cannot be targeted specifically enough. However, we found a significant improvement of subjective voice perception and voice-related quality of life in both groups. We explain this finding with an observer-expectancy effect secondary to the very time-consuming and elaborate study procedures.

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Objective Evaluation of Presbyphonia: Spectroacoustic Study on 142 Patients with Praat

Cited by 45 publications

References 12 publications

Acoustic Voice Analysis and Maximum Phonation Time in Relation to Voice Handicap Index Score and Larynx Disease

Acoustic Voice Analysis and Maximum Phonation Time in Relation to Voice Handicap Index Score and Larynx Disease

Machine-Learning Analysis of Voice Samples Recorded through Smartphones: The Combined Effect of Ageing and Gender

Functional Electrical Stimulation for Presbyphonia: A Prospective Randomized Trial

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