Voice Tremor in Parkinson's Disease: An Acoustic Study

High and Wide: An In Silico Investigation of Frequency, Intensity, and Vibrato Effects on Widely Applied Acoustic Voice Perturbation and Noise Measures

OBJECTIVES

This in silico study explored the effects of a wide range of fundamental frequency (fo), source-spectrum tilt (SST), and vibrato extent (VE) on commonly used frequency and amplitude perturbation and noise measures.

METHOD

Using 53 synthesized tones produced in Madde, the effects of stepwise increases in fo, intensity (modeled by decreasing SST), and VE on the PRAAT parameters jitter % (local), relative average perturbation (RAP) %, shimmer % (local), amplitude perturbation quotient 3 (APQ3) %, and harmonics-to-noise ratio (HNR) dB were investigated. A secondary experiment was conducted to determine whether any fo effects on jitter, RAP, shimmer, APQ3, and HNR were stable. A total of 10 sinewaves were synthesized in Sopran from 100 to 1000 Hz using formant frequencies for /a/, /i/, and /u/-like vowels, respectively. All effects were statistically assessed with Kendall's tau-b and partial correlation.

RESULTS

Increasing fo resulted in an overall increase in jitter, RAP, shimmer, and APQ3 values, respectively (P < 0.01). Oscillations of the data across the explored fo range were observed in all measurement outputs. In the Sopran tests, the oscillatory pattern seen in the Madde fo condition remained and showed differences between vowel conditions. Increasing intensity (decreasing SST) led to reduced pitch and amplitude perturbation and HNR (P < 0.05). Increasing VE led to lower HNR and an almost linear increase of all other measures (P < 0.05).

CONCLUSION

These novel data offer a controlled demonstration for the behavior of jitter (local) %, RAP %, shimmer (local) %, APQ3 %, and HNR (dB) when varying fo, SST, and VE in synthesized tones. Since humans will vary in all of these aspects in spoken language and vowel phonation, researchers should take potential resonance-harmonics type effects into account when comparing intersubject or preintervention and postintervention data using these measures.

Radiological correlates of vocal fold bowing as markers of Parkinson's disease progression: A cross-sectional study utilizing dynamic laryngeal CT

OBJECTIVE

To determine whether arytenoid cartilage position and dynamics change with advancing duration and severity (as graded by MDS-UPDRS part III scores) in Parkinson's disease, in a cross-sectional study design, we performed laryngeal four-dimensional computed tomography (4D-CT) in people with Parkinson's disease and controls.

METHODS

31 people with Parkinson's disease covering a range of disease duration and severity and 19 controls underwent laryngeal 4D-CT whilst repeatedly vocalizing. We measured on each CT volume the glottic area (GA), inter-arytenoid distance (IAD), IAD-Area index (IAI) and arytenoid cartilage velocity ([Formula: see text]).

RESULTS

People with Parkinson's disease had reductions in the mean/effective minimum IAD when compared to controls, while mean/effective minimum GA and mean/effective maximum IAI were increased. Arytenoid cartilage velocities showed no difference. On Spearman correlation analyses, advancing disease duration and severity of PD showed moderately strong and significant correlations with increasing mean/effective minimum GA, increasing mean/effective maximum IAI and decreasing effective minimum IAD. Linear mixed models which considered the effects of intra and inter-individual variation showed that both disease duration (b = -0.011, SEb = 0.053, 95% CI [-0.022, 0], t(27) = -2.10, p = 0.045) and severity (b = -0.069, SEb = 0.032, 95% CI [-0.14,-0.0039], t(27) = -2.17, p = 0.039) were significant predictors for IAD, and also for transformed values of the GA and IAI.

CONCLUSIONS

There are progressive alterations in phonatory posturing as Parkinson's disease advances. The increases in GA despite reductions in IAD are concordant with prior observations of vocal fold bowing. Our study provides a basis for using laryngeal 4D-CT to assess disease progression in Parkinson's disease.

Insight into an unsupervised two-step sparse transfer learning algorithm for speech diagnosis of Parkinson's disease

Speech diagnosis of Parkinson’s disease (PD) as a non-invasive and simple diagnosis method is particularly worth exploring. However, the number of samples of speech-based PD is relatively small, and there exist discrepancies in the distribution between subjects. In order to solve the two problems, a novel unsupervised two-step sparse transfer learning is proposed in this paper to tackle with PD speech diagnosis. In the first step, convolution sparse coding with the coordinate selection of samples and features is designed to learn speech structure from the source domain to replenish sample information of the target domain. In the second step, joint local structure distribution alignment is designed to maintain the neighbor relationship between the respective samples of the training set and test set, and reduce the distribution difference between the two domains at the same time. Two representative public PD speech datasets and one real-world PD speech dataset were exploited to verify the proposed method on PD speech diagnosis. Experimental results demonstrate that each step of the proposed method has a positive effect on the PD speech classification results, and it also delivers superior performance over the existing relative methods.

Objective Acoustic Quantification of Perceived Voice Tremor Severity

Purpose This study compared auditory-perceptual measures of presence/absence and severity of vocal tremor to acoustic markers of vocal tremor. The validity (both concurrent and diagnostic) of various acoustic markers of vocal tremor was also assessed. Method Fifty-six midvowel sustained [a:] recordings were selected to yield a representative convenience sample of vocal tremor. After training with 10 synthesized samples, 4 female audiologists rated these samples on "voice tremor severity" on a continuous 10-cm scale. Afterward, 15 randomly selected recordings were presented a 2nd time for intrarater reliability assessment. Customized audio signal processing in Praat yielded 12 acoustic measures of rate, extent and perturbation of fundamental frequency (f ₀), and intensity level (IL) modulation. Enter-type multiple linear regression analysis was applied to weight and combine these acoustic variables into an acoustic model of vocal tremor severity. Results After removing the vocal tremor severity ratings of 1 of the audiologists because of insufficient intra- and interrater reliability, mean single-measures consistency-type intraclass correlation coefficients equaled .83 within raters and .72 between raters. Correlation between mean ratings and the 12 acoustic markers ranged from .76 for median extent of f ₀ modulation to .11 for rate of IL modulation. Correlation between mean ratings and the acoustic model was .89. Analysis of this model's receiver operating characteristics yielded an area under receiver operating characteristic curve of .93, denoting sensitivity of .87 and specificity of .91. Conclusions This study demonstrated that auditory-perceptual ratings of vocal tremor severity are guided primarily by f ₀ and IL modulation extent, less by modulation perturbation, and least by modulation rate. The acoustic model covering all these modulation properties yielded acceptable results in terms of both concurrent and diagnostic validity. However, external cross-validation of this model is warranted before applying it in clinical voice/speech assessment.