Voice Measures Research Articles

Association of Psychosocial Work Factors and Psychological Distress With Voice Disorders Among Secondary School Teachers.

To assess the prevalence, lifetime prevalence of voice disorders, and its association with psychosocial work factors and psychological distress among secondary school teachers. Cross-sectional study. Secondary data from the CLUSTer study were analyzed, which included sociodemographics, psychosocial work factors (Job Content Questionnaire-22), psychological distress (Depression Anxiety and Stress Scale-21), and outcome measure of voice (Voice Handicap Index-10). A total of 1216 teachers were included in this study. Majority of them were females (81.0%), of Malays ethnicity (63.9%), and were married (83.3%). Almost one-third of the participants experienced high occupational stress. Less than one-third of them were having depression (27.9%) and stress (21.8%). More than half had anxiety (53.9%). The prevalence of voice disorders was 11.2% [95% confidence interval (CI): 8.9, 14.1], and the lifetime prevalence of voice disorders was 52.4% (95% CI: 48.8, 56.0). Participants with depression (aOR=2.50, 95% CI: 1.48, 4.22), anxiety (aOR=2.08, 95% CI: 1.05, 4.13), and stress (aOR=1.94, 95% CI: 1.11, 3.40) were associated with voice disorders. Psychosocial work factors such as occupational stress, supervisor support, and coworker support were not associated with voice disorders. Psychological distress is associated with the prevalence of voice disorders among secondary school teachers. These findings can be utilized in developing, designing, and implementing interventions or programs to reduce voice disorders for school teachers.

Effects of LSVT LOUD and EMST in individuals with Parkinson’s disease: A two arm non-randomized clinical trial

Purpose This study compared the effects of Lee Silverman Voice Treatment and Expiratory Muscle Strength Training on swallow, cough, and voice function in individuals with Parkinson’s disease. Method Fifty-eight individuals with mild-moderate Parkinson’s disease (male = 45, M = 69 years, SD = 8) were enrolled in a two-treatment clinical trial and completed four consecutive weeks of either Lee Silverman Voice Therapy or Expiratory Muscle Strength Training. All participants completed standard protocol videofluoroscopic swallow study, spirometry-cough tests, acoustic-voice assessment, and self-rated questionnaires pre- and post-therapy. Data were analysed by masked clinicians using specialised software. Mixed-model repeated measures and t-tests were performed. Result Lee Silverman Voice Treatment resulted in greater effects in acoustic aerodynamic voice measures (loudness, pitch-range, and aerodynamic-efficiency; p < .05) compared to the Expiratory Muscle Strength Training group. There were significant effects on pharyngoesophageal segment maximum opening (p =.01) following Lee Silverman Voice Treatment. Expiratory Muscle Strength Training resulted in significantly greater change in maximum hyoid displacement (Hmax; p = .04) and decreased Hmax duration (p < .01) compared to Lee Silverman Voice Therapy group. No cough measures and self-reported questionnaires significantly differed between groups with both groups improving post-treatment. Conclusion Both Lee Silverman Voice Therapy and Expiratory Muscle Strength Training improved specific swallow efficiency and airway defence capacity despite differences in task and therapeutic dose. Only Lee Silverman Voice Thearpy improved vocal intensity. Both treatments are feasible options for individuals with mild-moderate Parkinson’s disease.

Towards a voice-based severity scale for Parkinson’s disease monitoring

Abstract The unified Parkinson’s disease rating scale, used to monitor the disease progression, is based on visual assessments of motor symptoms. Vocal manifestations of Parkinson’s disease differ from the motor ones, specifically in their rate of change with disease severity. As such, a different scale is needed to provide the voice measures of the disease severity. This study employed a dataset of voice-quality features from repeated recordings of Parkinson’s disease patients. The changes of all voice features across the categories were evaluated using one-way analysis-of-variance and support vector regression. Significant changes and marked non-linearly increasing or decreasing trends were shown for all features, for the three-categories scale. Significant changes and trends were obtained in the 12-categories scale, but only for the mild category and the severe category range of scores. The findings imply a potential for voice-based monitoring for the early and late severity stages of Parkinson’s disease that could be continuously used by patients and provide timely warnings of deterioration.

Predictive Modeling and Early Detection of Parkinson's Disease Using Machine Learning

Parkinson's disease is a progressive neurodegenerative disorder that impacts millions of citizens in the USA, mainly targeting the motor system and causing debilitating symptoms such as rigidity, tremors, and bradykinesia. The diagnosis of Parkinson's disease is presently heavily dependent on clinical evaluations and neurological examinations, targeting the detection of motor dysfunction. The principal aim of this study was to use machine learning as a means for early detection and prediction of Parkinson's disease. The dataset utilized for this study was the Parkinson’s Disease Dataset, retrieved from the UCI Machine Learning Repository, which included comprehensive biomedical voice measurements from a cohort of individuals, 23 of whom are diagnosed with Parkinson’s disease and 8 who are healthy controls. This dataset included a set of features extracted from voice recordings. These include parameters like fundamental frequency (pitch), amplitude variation, jitter, shimmer, and several phonation-related measures known to reflect early vocal impairments associated with the disease in question. This research project deployed three credible and proven algorithms, namely, logistic regression, random forest, and the Support Vector Machines. Besides, this study employed a combination of metrics, including accuracy, precision, recall, F1-score, and ROC-AUC, which are more holistic toward the model performance. According to the metric performance results of the three models, several key insights were drawn into the early detection of Parkinson's Disease. Particularly, it was clear that the Random Forest model had superior accuracy and was the most reliable in classifying positive cases and healthy patients, which could be that this model turned out to be most reliable in an early detection setting. In that respect, predictive modeling in Parkinson's Disease is a capability frontier that has the potential to make much difference in clinical decision-making. Supported by Machine Learning algorithms, clinicians can trace the minute patterns in patient data, which are not easily visible through any other diagnostic means. In such cases, early detection of Parkinson's Disorder with vocal biomarkers or motor assessment may afford healthcare professionals opportunities for early interventions that might retard the disease process.

Thermal, Acoustic, and Self-Perceptual Measures of Pre-Post Vocal Change After Surface Hydration in Speech-Language Pathologists

PurposeNumerous clinical findings support the idea that increased surface laryngeal hydration prevents and manages voice problems in professional voice users. However, empirical evidence for surface laryngeal hydration (nebulized saline solution) through multidimensional voice measures is lacking, especially in speech-language pathologists (SLPs). Hence, the present study investigated the effect of surface hydration using nebulized saline solution on voice quality using thermal, acoustic, and self-perceptual measures in SLPs. MethodsThe study involved 30 SLPs divided into three groups: group I had no voice usage, group II read aloud passage for 1 hour without surface hydration, and group III read aloud passage for 1 hour with surface hydration for 10 minutes. Multidimensional voice outcomes such as thermal (front, right, and left view of the throat), acoustic (Multidimensional Voice Program), and self-perceptual (perceived phonatory effort, perceived vocal tiredness) were measured for the pretest and post test condition in all the group. ResultsPre-post comparison shows that thermal measures showed a significant increase in group II and a significant decrease in group III. Also, fundamental frequency, perturbation, and self-perceptual measures showed a significant increase in group II compared to group III. Further, the between-group post test comparisons revealed a significant decrease in many outcome measures in group III compared to group II. The above results support that surface hydration significantly influenced the voice quality during the vocal loading task. ConclusionThe study confirms the benefits of surface hydration using saline solution in SLPs. Surface hydration preserves vocal quality compared to those not hydrated during vocal loading.

Do I sound sick? Self-perceived and objectively measured voice impairment in acutely decompensated heart failure: fist insights from the AHF-Voice study

Abstract Introduction Acute heart failure (AHF) is a common reason for recurrent hospitalization. Daily smartphone-based recording of vocal biomarkers appears promising for the early detection of impeding AHF. However, the value of patient-reported outcome measures (PROMs), i.e. self-perceived voice alterations during decompensation, is unknown. Methods AHF-Voice is an ongoing monocentric prospective cohort study focusing on voice alterations in patients hospitalized for AHF. Exclusion criteria: listed for heart transplantation, high output HF, cardiogenic shock, history of vocal fold disease or surgery, or life-expectancy &amp;lt;6 months. During hospitalization, medical history &amp; echocardiogram were taken and routine blood sampling was done. Daily voice recordings including sustained vowels and standardized reading were collected using a specially designed smartphone app under supervision. At admission and discharge, the self-perceived level of voice alteration was assessed by the Voice–Handicap Index-12 (VHI-12, 0-48 points) questionnaire and a global voice scale (Likert scale, 0-3 points). For both scales, higher values indicate a more severe voice impairment. Hypervolemia was quantified by body composition analysis. Preprocessing and feature extraction of voice recordings were performed using Praat software. The association of self-perceived voice impairment with surrogates of congestion and vocal biomarkers was assessed by bivariate correlation and linear regression. Results Between Apr 2023 and Feb 2024, 72 hospitalized patients with AHF were included. Four patients withdrew consent, 5 patients were excluded due to limited voice recording quality. Hence, 63 patients were considered for analysis: mean age 75±10 years, 67% men, 91% were in NYHA class III/IV, 49% de novo HF, mean LVEF was 45±16%, and median value of Charlson comorbidity score was 2 [1, 3]. Both measures of self-perceived voice impairment improved between admission and discharge (Table 1A and Figure). Concomitantly, body weight, hypervolemia, NT-proBNP, and vocal biomarkers (total reading time and shimmer) decreased. Bivariate correlation showed that both self-perceived scales of voice impairment were closely correlated, as expected (Spearman’s rho 0.36). Linear regression identified surrogates of congestion and objective voice impairments as predictors for change in both PROMs (Table 1B). However, the explained variance was low, e.g. for change in volume status and NT-proBNP 14% and 1% (VHI-12), and 4% and 7% (Global voice scale), respectively. Conclusion This preliminary analysis in patients with AHF showed that self-perceived voice impairment was sensitive to change during recompensation. Objectively generated voice measures and congestion only partially explained the observed improvement of these PROMs. This might indicate that the self-perceived voice impairment constitutes a complimentary domain of patient well-being and indicator for congestion that should be explored further.

The Self-Assessment, Perturbation, and Resonance Values of Voice and Speech in Individuals with Snoring and Obstructive Sleep Apnea

SummaryNA PurposeThe static and dynamic soft tissue changes resulting in hypopnea and/or apnea in the subjects with obstructive sleep apnea (OSA) occur in the upper airway, which also serves as the voice or speech tract. In this study, we looked for the Voice Handicap Index-10 (VHI-10) and Voice-Related Quality of Life (V-RQOL) scores in addition to perturbation and formant values of the vowels in those with snoring and OSA. MethodsEpworth Sleepiness Scale (ESS), STOP-Bang scores, Body-Mass Index (BMI), neck circumference (NC), modified Mallampati Index (MI), tonsil size, Apnea-Hypopnea Index (AHI), VHI-10 and V-RQOL scores, perturbation and formant values, and fundamental frequency of the voice samples were taken to evaluate. ResultsThe data revealed that not the perturbation and formant values but scores of VHI-10 and V-RQOL were significantly different between the control and OSA subjects and that both were significantly correlated with ESS and NC. Further, a few significant correlations of BMI, and tonsil size with the formant and perturbation values were also found. ConclusionsOur data reveals that i) VHI-10 and V-RQOL were good identifiers for those with OSA, and ii) perturbation and formant values were related to particularly tonsil size, and further BMI. Hence, we could say that in an attempt to use a voice parameter to screen OSA, VHI-10, and V-RQOL appeared to be better than the objective voice measures, which could be variable due to the tonsil size and BMI of the subjects.

Voice biomarkers in middle and later adulthood as predictors of cognitive changes.

Prosody voice measures, especially jitter and shimmer, have been associated with cognitive impairment and hold potential as early indicators of risk for cognitive decline. Prior research suggests that voice measures assessed concurrently with longitudinal cognitive outcomes are associated with 10-year cognitive declines in middle-age and older adults from Midlife in the U.S. (MIDUS) study. Using a subsample from the same study, we expanded previous research to examine voice measures that were (1) collected 8 years before cognitive outcomes, (2) derived from narrative speech in logical memory tests instead of word list recall tests, and (3) independent of the cognitive outcomes. Multilevel analyses controlled for covariates of age, sex, education, neurological conditions, depressive symptoms, and chronic conditions. The results indicated that higher jitter and lower shimmer predicted greater 10-year declines in episodic memory and working memory. These findings extend previous research by highlighting prosody voice measures assessed 8 years earlier as predictors of subsequent cognitive declines over a decade.

Institutional quality and economic growth in upper-middle-income African countries

PurposeTo determine which proxy institutional quality variables are most significant for a country’s economic growth, the paper aims to investigate the effect of institutional quality on economic growth in upper-middle-income African nations between 2002 and 2021.Design/methodology/approachIn an attempt to account for countries' heterogeneity, the study uses a random and fixed effect model estimated by the generalized least squares.FindingsThe empirical findings demonstrate that the institutional quality measures of political stability, voice and accountability, corruption control and violence absence are statistically and favorably significant factors influencing the economic growth of upper-middle-income African countries.Originality/valueThis paper is unique in that it uses both random and fixed effects models to determine the effect of institutional quality on economic growth in the context of upper-middle-income African countries between 2002 and 2021.

The acoustics of voice

Recent decades have seen rapid growth in our understanding of the production and perception of the human voice and of the acoustic features that critically link production and perception in communication. This review describes some of the many acoustic measures of voice (and voice quality) that have been proposed to quantify these features, with attention to major changes over the years in what has been measured and why. Linkages between acoustic measurement systems and voice production and perception will be explored, and the current state of the art will be reviewed.

Influence of Carnatic Vocal Training on Voice Measures in Males

Introduction: Training is an integral part of learning any skill. The vocal training helps singers attain proficiency as they are the most demanding vocal group of all professional voice users. Hence, it is necessary to evaluate the influence of training on the singer’s voice. The current study objective was to investigate the influence of vocal training on voice measures (acoustic and aerodynamic) between male Carnatic singers with lower (6 months–5 years) and higher (6–10 years) training using novel task “mkaram” along with lyrical task. Methods: Group 1 consisted of 30 trained male Carnatic singers with lower vocal training, and group 2, thirty trained male singers with higher training in the age of 18–45 years. The acoustic (frequency-related parameter, cepstral, spectral, perturbation, and noise) and aerodynamic measures (maximum phonation time and s/z ratio) of voice were obtained. The test-retest reliability was conducted on a sample of 10% of the population from each group, with a 2-week interval between the tests. Cross-sectional study design was applied. Results: The statistical analysis revealed significantly decreased frequency-related parameters (semitones) such as the mean fundamental frequency, lowest fundamental frequency, highest fundamental frequency at the low register and the highest fundamental frequency at the middle register in group 2 during “mkaram” task (p ≤ 0.05). Similarly, one of the spectral-related measures 1st harmonic-2nd harmonic (dB) during lyrical task and one of the noise-related measure harmonic-to-noise ratio (dB) at the middle register during “mkaram” task showed a significant decrease in group 2 compared to group 1 (p ≤ 0.05). Test-retest reliability revealed that most of the parameters had “acceptable to excellent” internal consistency (Cronbach’s α >0.7 to 1). Conclusion: Few frequency and noise measures during “mkaram” task and a spectral measure during lyrical task showed to be sensitive in distinguishing the impact of vocal training on the voices of male Carnatic singers. The higher vocal training was found to help the singers to perform more efficiently with enhanced vocal range particularly in the low register and to some extent in the middle register. Indeed, the study highlighted the positive effects of vocal training on male Carnatic singers.

Evidence-Based Recommendations for Tablet Recordings From the Bridge2AI-Voice Acoustic Experiments

BackgroundAs part of a larger goal to create best practices for voice data collection to fuel voice AI research, the objective of this study was to investigate the ability of readily available iOS and Android tablets with and without low-cost headset microphones to produce recordings and subsequent acoustic measures of voice comparable to “research quality” instrumentation. MethodsRecordings of 24 sustained vowel samples representing a wide range of typical and disordered voices were played via a head-and-torso model and recorded using a research quality standard microphone/preamplifier/audio interface. Acoustic measurements from the standard were compared to two popular tablets using their built-in microphones and with low-cost headset microphones at different distances from the mouth. ResultsVoice measurements obtained via tablets + headset microphones close to the mouth (2.5 and 5cm) strongly correlated (r’s > 0.90) with the research standard and resulted in no significant differences for measures of vocal frequency and perturbation. In contrast, voice measurements obtained using the tablets’ built-in microphones at typical reading distances (30 and 45cm) tended to show substantial variability in measurement, greater mean differences in voice measurements, and relatively poorer correlations vs. the standard. ConclusionFindings from this study support preliminary recommendations from the Bridge2AI-Voice Consortium recommending the use of smartphones paired with low-cost headset microphones as adequate methods of recording for large-scale voice data collection from a variety of clinical and non-clinical settings. Compared to recording using a tablet directly, a headset microphone controls for recording distance and reduces the effects of background noise, resulting in decreased variability in recording quality. Data Availability StatementData supporting the results reported in this article may be obtained upon request from the contact author.

A Scoping Review on the Intersection Between Voice and Swallowing Measures in Healthy and Disordered Populations.

Voice and swallowing are distinct functions that share anatomical and physiological properties; however, research investigating their intersection is limited. The purpose of this scoping review was to explore the literature surrounding the relationship between voice and swallowing measures in healthy adults and those with non-degenerative disorders. Specifically, we aimed to elucidate whether objective voice measures could be used as correlates of swallowing function. We systematically searched four databases (Embase, PubMed, CINAHL, and Web of Science) for relevant literature using a combination of key words and controlled vocabulary generated from the Yale Mesh Analyzer. The inclusion criteria consisted of peer-reviewed studies in the English language that reported on healthy adults and/or patients with non-degenerative neurological disorders and pulmonary diseases and contained instrumental and/or objective voice and swallowing measures. Two raters completed the abstract screening process followed by independent full-text reviews. Case studies, review studies, gray literature, or abstract-only studies were excluded. Among 5,485 screened studies, 182 were fully reviewed, with only 11 studies meeting the inclusion criteria. Eight studies found an association between voice and swallowing objective measures, whereas the other three did not. Significant voice measures that were related to swallowing safety and/or physiology included maximum fundamental frequency (F0), F0 range, maximum phonation time, biomechanics of effortful pitch glides, and voice onset time. Although there was heterogeneity in the measures used, specific objective voice measures showed promise in clinical practice as a screening tool for dysphagia. Further investigations are needed to validate the clinical utility of these measures across diverse patient populations.

Correlation of Multiple Measures of Voice Evaluation Among Individuals with Muscle Tension Dysphonia: An Exploratory Study.

Primary Muscle Tension Dysphonia (MTD) occurs in the absence of structural or neurologic etiologies. Patients with MTD are frequently encountered in clinics and are evaluated using multiple measures of voice evaluation. Studies reporting on the correlation of multiple measures of voice evaluation among individuals with MTD are minimal, which led to this study. This single-group correlational study involved 48 participants diagnosed with primary MTD at a tertiary care institute. Multidimensional measures of voice (acoustic, aerodynamic, auditory-perceptual, and self-rating) were obtained from the participants. GRBAS scale, Acoustic Voice Quality Index, Acoustic Breathiness Index, Maximum Phonation Duration, S/Z ratio, Voice Handicap Index, and Vocal Fatigue Index were the variables considered. These measures were correlated using Spearman's correlation (ρ) within and between different measures of voice evaluation. Several statistically significant (P < 0.05) correlations were found within and across different measures of voice evaluation. Moderate to very high correlations (ρ between 0.48 and 0.87) were found between auditory-perceptual measures and multiparametric acoustic measures. Weak to moderate correlations (ρ between 0.31 and 0.62) were observed between the VHI and its subsections, with GRBAS, AVQI, and ABI. No statistically significant correlations were observed between aerodynamic measures and other measures of voice evaluation. Results from this study suggest that compared to across measures, the correlation between different variables was stronger within each measure of voice evaluation. These findings highlight the need for a multidimensional voice evaluation in patients with MTD.

Long-Term Outcomes of Pediatric Laryngeal Reinnervation.

Pediatric nonselective laryngeal reinnervation (NSLR) has gained popularity in recent years; however, long-term outcomes have not been reported. Patients greater than 1 year post reinnervation were recruited. Families were asked to report Pediatric Voice-Related Quality of Life (PVRQOL) and provide an audio recording of connected speech. PVRQOL and voice measures were compared with preoperative and early postoperative outcomes (<12 months) using analysis of variance (ANOVA) for repeated measures and post hoc tests for linear trend. Sixty-six patient families were contacted. Twelve patients responded with PVRQOL; six (50%) were female. Median age at surgery was 6.4 (range 1.9-15) and at follow-up 13.5 (range 10-18), with a median of 6.8 years (range 3-9.1) since surgery at follow-up. Mean preoperative PVRQOL was 68.1 (95% CI 52.3-84.0), early postoperative 86.5 (73.2-99.7), and long-term 90 (82.7-97.3). ANOVA showed no significant difference between values (p = 0.1228), but post hoc testing showed improving outcomes over time (p-for-trend 0.0304). PVRQOL was stable between early postoperative and long-term values (p = 0.3399). Four voice samples were adequate for analysis. Mean preoperative cepstral peak prominence (CPP) was 5.2 (95% CI 3.4-7.0), early postoperative 8.5 (5.5-11.5), and long-term 6.8 (2.77-10.89, p = 0.3340, p-for-trend 0.2988) Low-to-high spectral ratio was 22.3 preoperatively (14.0-30.5), 23.0 early postoperative (17.4-28.7), and 28.8 long-term (17.4-40.2, p = 0.1174, p-for-trend 0.0364). Cepstral spectral index of dysphonia (CSID) was 83.0 preoperatively (44.1-121.8), 39.4 early postoperative (20.4-58.3), and 45.53 long-term (-0.05-91.1, p = 0.4457, p-for-trend 0.1464). Years after NSLR, PVRQOL, low-to-high spectral ratio, and CSID show no evidence of degradation over time. 4 Laryngoscope, 134:5006-5009, 2024.

Consistency of the Signature of Phonotraumatic Vocal Hyperfunction Across Different Ambulatory Voice Measures.

Although different factors and voice measures have been associated with phonotraumatic vocal hyperfunction (PVH), it is unclear what percentage of individuals with PVH exhibit such differences during their daily lives. This study used a machine learning approach to quantify the consistency with which PVH manifests according to ambulatory voice measures. Analyses included acoustic parameters of phonation as well as temporal aspects of phonation and rest, with the goal of determining optimally consistent signatures of PVH. Ambulatory neck-surface acceleration signals were recorded over 1 week from 116 female participants diagnosed with PVH and age-, sex-, and occupation-matched vocally healthy controls. The consistency of the manifestation of PVH was defined as the percentage of participants in each group that exhibited an atypical signature based on a target voice measure. Evaluation of each machine learning model used nested 10-fold cross-validation to improve the generalizability of findings. In Experiment 1, we trained separate logistic regression models based on the distributional characteristics of 14 voice measures and durations of voicing and resting segments. In Experiments 2 and 3, features of voicing and resting duration augmented the existing distributional characteristics to examine whether more consistent signatures would result. Experiment 1 showed that the difference in the magnitude of the first two harmonics (H1-H2) exhibited the most consistent signature (69.4% of participants with PVH and 20.4% of controls had an atypical H1-H2 signature), followed by spectral tilt over eight harmonics (73.6% participants with PVH and 32.1% of controls had an atypical spectral tilt signature) and estimated sound pressure level (SPL; 66.9% participants with PVH and 27.6% of controls had an atypical SPL signature). Additionally, 77.6% of participants with PVH had atypical resting duration, with 68.9% exhibiting atypical voicing duration. Experiments 2 and 3 showed that augmenting the best-performing voice measures with univariate features of voicing or resting durations yielded only incremental improvement in the classifier's performance. Females with PVH were more likely to use more abrupt vocal fold closure (lower H1-H2), phonate louder (higher SPL), and take shorter vocal rests. They were also less likely to use higher fundamental frequency during their daily activities. The difference in the voicing duration signature between participants with PVH and controls had a large effect size, providing strong empirical evidence regarding the role of voice use in the development of PVH.

A Study on Voice Measures in Patients with Parkinson’s Disease

This research aims to identify acoustic features which can distinguish patients with Parkinson's disease (PD patients) and healthy speakers. Thirty PD patients and 30 healthy speakers were recruited in the experiment, and their speech was collected, including three vowels (/i/, /a/, and /u/) and nine consonants (/p/, /pʰ/, /t/, /tʰ/, /k/, /kʰ/, /l/, /m/, and /n/). Acoustic features like fundamental frequency (F0), Jitter, Shimmer, harmonics-to-noise ratio (HNR), first formant (F1), second formant (F2), third formant (F3), first bandwidth (B1), second bandwidth (B2), third bandwidth (B3), voice onset, voice onset time were analyzed in our experiment. Two-sample independent t test and the nonparametric Mann-Whitney U (MWU) test were carried out alternatively to compare the acoustic measures between the PD patients and healthy speakers. In addition, after figuring out the effective acoustic features for distinguishing PD patients and healthy speakers, we adopted two methods to detect PD patients: (1) Built classifiers based on the effective acoustic featuresand (2) Trained support vector machine classifiers via the effective acoustic features. Significant differences were found between the male PD group and the male health control in vowel /i/ (Jitter and Shimmer) and /a/ (Shimmer and HNR). Among female subjects, significant differences were observed in F0 standard deviation (F0 SD) of /u/ between the two groups. Additionally, significant differences between PD group and health control were also found in the F3 of /i/ and /n/, whereas other acoustic features showed no significant differences between the two groups. The HNR of vowel /a/ performed the best classification accuracy compared with the other six acoustic features above found to distinguish PD patients and healthy speakers. PD can cause changes in the articulation and phonation of PD patients, wherein increases or decreases occur in some acoustic features. Therefore, the use of acoustic features to detect PD is expected to be a low-cost and large-scale diagnostic method.

Validity of Acoustic Measures Obtained Using Various Recording Methods Including Smartphones With and Without Headset Microphones.

The goal of this study was to assess various recording methods, including combinations of high- versus low-cost microphones, recording interfaces, and smartphones in terms of their ability to produce commonly used time- and spectral-based voice measurements. Twenty-four vowel samples representing a diversity of voice quality deviations and severities from a wide age range of male and female speakers were played via a head-and-thorax model and recorded using a high-cost, research standard GRAS 40AF (GRAS Sound & Vibration) microphone and amplification system. Additional recordings were made using various combinations of headset microphones (AKG C555 L [AKG Acoustics GmbH], Shure SM35-XLR [Shure Incorporated], AVID AE-36 [AVID Products, Inc.]) and audio interfaces (Focusrite Scarlett 2i2 [Focusrite Audio Engineering Ltd.] and PC, Focusrite and smartphone, smartphone via a TRRS adapter), as well as smartphones direct (Apple iPhone 13 Pro, Google Pixel 6) using their built-in microphones. The effect of background noise from four different room conditions was also evaluated. Vowel samples were analyzed for measures of fundamental frequency, perturbation, cepstral peak prominence, and spectral tilt (low vs. high spectral ratio). Results show that a wide variety of recording methods, including smartphones with and without a low-cost headset microphone, can effectively track the wide range of acoustic characteristics in a diverse set of typical and disordered voice samples. Although significant differences in acoustic measures of voice may be observed, the presence of extremely strong correlations (rs > .90) with the recording standard implies a strong linear relationship between the results of different methods that may be used to predict and adjust any observed differences in measurement results. Because handheld smartphone distance and positioning may be highly variable when used in actual clinical recording situations, smartphone + a low-cost headset microphone is recommended as an affordable recording method that controls mouth-to-microphone distance and positioning and allows both hands to be available for manipulation of the smartphone device.

Speech, voice, and language outcomes following deep brain stimulation: A systematic review.

Deep brain stimulation (DBS) reliably ameliorates cardinal motor symptoms in Parkinson's disease (PD) and essential tremor (ET). However, the effects of DBS on speech, voice and language have been inconsistent and have not been examined comprehensively in a single study. We conducted a systematic analysis of literature by reviewing studies that examined the effects of DBS on speech, voice and language in PD and ET. A total of 675 publications were retrieved from PubMed, Embase, CINHAL, Web of Science, Cochrane Library and Scopus databases. Based on our selection criteria, 90 papers were included in our analysis. The selected publications were categorized into four subcategories: Fluency, Word production, Articulation and phonology and Voice quality. The results suggested a long-term decline in verbal fluency, with more studies reporting deficits in phonemic fluency than semantic fluency following DBS. Additionally, high frequency stimulation, left-sided and bilateral DBS were associated with worse verbal fluency outcomes. Naming improved in the short-term following DBS-ON compared to DBS-OFF, with no long-term differences between the two conditions. Bilateral and low-frequency DBS demonstrated a relative improvement for phonation and articulation. Nonetheless, long-term DBS exacerbated phonation and articulation deficits. The effect of DBS on voice was highly variable, with both improvements and deterioration in different measures of voice. This was the first study that aimed to combine the outcome of speech, voice, and language following DBS in a single systematic review. The findings revealed a heterogeneous pattern of results for speech, voice, and language across DBS studies, and provided directions for future studies.

Application of Patient-Reported Outcome Measurements in Adult Tumor Clinical Trials in China: Cross-Sectional Study.

International health policies and researchers have emphasized the value of evaluating patient-reported outcomes (PROs) in clinical studies. However, the characteristics of PROs in adult tumor clinical trials in China remain insufficiently elucidated. This study aims to assess the application and characteristics of PRO instruments as primary or secondary outcomes in adult randomized clinical trials related to tumors in China. This cross-sectional study identified tumor-focused randomized clinical trials conducted in China between January 1, 2010, and June 30, 2022. The ClinicalTrials.gov database and the Chinese Clinical Trial Registry were selected as the databases. Trials were classified into four groups based on the use of PRO instruments: (1) trials listing PRO instruments as primary outcomes, (2) trials listing PRO instruments as secondary outcomes, (3) trials listing PRO instruments as coprimary outcomes, and (4) trials without any mention of PRO instruments. Pertinent data, including study phase, settings, geographic regions, centers, participant demographics (age and sex), funding sources, intervention types, target diseases, and the names of PRO instruments, were extracted from these trials. The target diseases involved in the trials were grouped according to the American Joint Committee on Cancer Staging Manual, 8th Edition. Among the 6445 trials examined, 2390 (37.08%) incorporated PRO instruments as part of their outcomes. Within this subset, 26.82% (641/2390) listed PRO instruments as primary outcomes, 52.72% (1260/2390) as secondary outcomes, and 20.46% (489/2390) as coprimary outcomes. Among the 2,155,306 participants included in these trials, PRO instruments were used to collect data from 613,648 (28.47%) patients as primary or secondary outcomes and from 74,287 (3.45%) patients as coprimary outcomes. The most common conditions explicitly using specified PRO instruments included thorax tumors (217/1280, 16.95%), breast tumors (176/1280, 13.75%), and lower gastrointestinal tract tumors (173/1280, 13.52%). Frequently used PRO instruments included the European Organisation for Research and Treatment of Cancer Quality of Life Core Questionnaire-30, the visual analog scale, the numeric rating scale, the Traditional Chinese Medicine Symptom Scale, and the Pittsburgh Sleep Quality Index. Over recent years, the incorporation of PROs has demonstrated an upward trajectory in adult randomized clinical trials on tumors in China. Nonetheless, the infrequent measurement of the patient's voice remains noteworthy. Disease-specific PRO instruments should be more effectively incorporated into various tumor disease categories in clinical trials, and there is room for improvement in the inclusion of PRO instruments as clinical trial end points.