Interactions between voice fundamental frequency and cardiovascular parameters. Preliminary results and physiological mechanisms

Heart Rate Variability in a Vocal Stress Test with Special Consideration of the Objective Voice Function

OBJECTIVE

Many employees, especially in voice-intensive professions, are under psychological stress at work, which is very difficult to objectify. The aim of the study was to analyze correlations between heart rate variability (HRV) parameters and objective voice function using weighted voice parameters (Dysphonia Severity Index [DSI]) in order to determine whether subjects with impaired vocal function show a predominance of sympathetic control during a vocal stress test.

STUDY DESIGN

Prospective.

METHODS

Fifty-three people of working age were examined. After asking for sociodemographic, occupational, and voice-related data, the objective voice function was determined using the DiVAS voice diagnostics system, and a 20-minute vocal stress test was performed. The electrocardiogram was recorded using medilog AR12plus during the vocal stress test and in a 5-minute rest phase before and a 5-minute recovery phase after the test. HRV was analyzed using the Kubios HRV Premium software.

RESULTS

HRV was reduced during the vocal stress test compared to the resting and recovery phase. A Spearman correlation analysis showed significant correlations, particularly between the frequency-related HRV parameters and the DSI. The DSI correlated positively with the high frequency (HF) band (the relative power and the normalized unit). The DSI correlated negatively with the quotient between low frequency and HF and the low frequency normalized unit.

CONCLUSION

During a vocal stress test, adults in working age show a correlation between parameters of objective vocal function and parameters of HRV. The more impaired the objective vocal function, the higher the predominance of sympathetic activation under vocal stress. The voice can therefore be seen as a "warning signal" for the processes in the autonomic nervous system. The use of preventive strategies for stress management and for voice health appears to be particularly beneficial in vocally stressful occupations in order to achieve a positive effect on parasympathetic activity.

Machine Learning-based Voice Assessment for the Detection of Positive and Recovered COVID-19 Patients

Many virological tests have been implemented during the Coronavirus Disease 2019 (COVID-19) pandemic for diagnostic purposes, but they appear unsuitable for screening purposes. Furthermore, current screening strategies are not accurate enough to effectively curb the spread of the disease. Therefore, the present study was conducted within a controlled clinical environment to determine eventual detectable variations in the voice of COVID-19 patients, recovered and healthy subjects, and also to determine whether machine learning-based voice assessment (MLVA) can accurately discriminate between them, thus potentially serving as a more effective mass-screening tool. Three different subpopulations were consecutively recruited: positive COVID-19 patients, recovered COVID-19 patients and healthy individuals as controls. Positive patients were recruited within 10 days from nasal swab positivity. Recovery from COVID-19 was established clinically, virologically and radiologically. Healthy individuals reported no COVID-19 symptoms and yielded negative results at serological testing. All study participants provided three trials for multiple vocal tasks (sustained vowel phonation, speech, cough). All recordings were initially divided into three different binary classifications with a feature selection, ranking and cross-validated RBF-SVM pipeline. This brough a mean accuracy of 90.24%, a mean sensitivity of 91.15%, a mean specificity of 89.13% and a mean AUC of 0.94 across all tasks and all comparisons, and outlined the sustained vowel as the most effective vocal task for COVID discrimination. Moreover, a three-way classification was carried out on an external test set comprised of 30 subjects, 10 per class, with a mean accuracy of 80% and an accuracy of 100% for the detection of positive subjects. Within this assessment, recovered individuals proved to be the most difficult class to identify, and all the misclassified subjects were declared positive; this might be related to mid and short-term vocal traces of COVID-19, even after the clinical resolution of the infection. In conclusion, MLVA may accurately discriminate between positive COVID-19 patients, recovered COVID-19 patients and healthy individuals. Further studies should test MLVA among larger populations and asymptomatic positive COVID-19 patients to validate this novel screening technology and test its potential application as a potentially more effective surveillance strategy for COVID-19.

Body exposure and vocal analysis: validation of fundamental frequency as a correlate of emotional arousal and valence

Introduction

Vocal analysis of fundamental frequency (f0) represents a suitable index to assess emotional activation. However, although f0 has often been used as an indicator of emotional arousal and different affective states, its psychometric properties are unclear. Specifically, there is uncertainty regarding the validity of the indices of f0_mean and f0_{variabilitymeasures} (f0_dispersion, f0_range, and f0_SD) and whether higher or lower f0 indices are associated with higher arousal in stressful situations. The present study therefore aimed to validate f0 as a marker of vocally encoded emotional arousal, valence, and body-related distress during body exposure as a psychological stressor.

Methods

N = 73 female participants first underwent a 3-min, non-activating neutral reference condition, followed by a 7-min activating body exposure condition. Participants completed questionnaires on affect (i.e., arousal, valence, body-related distress), and their voice data and heart rate (HR) were recorded continuously. Vocal analyses were performed using Praat, a program for extracting paralinguistic measures from spoken audio.

Results

The results revealed no effects for f0 and state body dissatisfaction or general affect. F0_mean correlated positively with self-reported arousal and negatively with valence, but was not correlated with HR_mean/maximum. No correlations with any measure were found for any f0_{variabililtymeasures}.

Discussion

Given the promising findings regarding f0_mean for arousal and valence and the inconclusive findings regarding f0 as a marker of general affect and body-related distress, it may be assumed that f0_mean represents a valid global marker of emotional arousal and valence rather than of concrete body-related distress. In view of the present findings regarding the validity of f0, it may be suggested that f0_mean, but not f0_{variabilitymeasures}, can be used to assess emotional arousal and valence in addition to self-report measures, which is less intrusive than conventional psychophysiological measures.

Feasibility of Incorporating Voice Technology and Virtual Assistants in Cardiovascular Care and Clinical Trials

PURPOSE OF REVIEW

With the rising cost of cardiovascular clinical trials, there is interest in determining whether new technologies can increase cost effectiveness. This review focuses on current and potential uses of voice-based technologies, including virtual assistants, in cardiovascular clinical trials.

RECENT FINDINGS

Numerous potential uses for voice-based technologies have begun to emerge within cardiovascular medicine. Voice biomarkers, subtle changes in speech parameters, have emerged as a potential tool to diagnose and monitor many cardiovascular conditions, including heart failure, coronary artery disease, and pulmonary hypertension. With the increasing use of virtual assistants, numerous pilot studies have examined whether these devices can supplement initiatives to promote transitional care, physical activity, smoking cessation, and medication adherence with promising initial results. Additionally, these devices have demonstrated the ability to streamline data collection by administering questionnaires accurately and reliably. With the use of these technologies, there are several challenges that must be addressed before wider implementation including respecting patient privacy, maintaining regulatory standards, acceptance by patients and healthcare providers, determining the validity of voice-based biomarkers and endpoints, and increased accessibility.

SUMMARY

Voice technology represents a novel and promising tool for cardiovascular clinical trials; however, research is still required to understand how it can be best harnessed.

Aerodynamic and Acoustic Voice Measures Before and After an Acute Public Speaking Stressor

Purpose The goal of this study was to determine if differences in stress system activation lead to changes in speaking fundamental frequency, average oral airflow, and estimated subglottal pressure before and after an acute, psychosocial stressor. Method Eighteen vocally healthy adult females experienced the Trier Social Stress Test (TSST) to activate the hypothalamic-pituitary-adrenal axis. The TSST includes public speaking and performing mental arithmetic in front of an audience. At seven time points, three before the stressor and four after the stressor, the participants produced /pa/ repetitions, read the Rainbow Passage, and provided a saliva sample. Measures included (a) salivary cortisol level, (b) oral airflow, (c) estimated subglottal pressure, and (d) speaking fundamental frequency from the second sentence of the Rainbow Passage. Results Ten of the 18 participants experienced a hypothalamic-pituitary-adrenal axis response to stress as indicated by a 2.5-nmol/L increase in salivary cortisol from before the TSST to after the TSST. Those who experienced a response to stress had a significantly higher speaking fundamental frequency before and immediately after the stressor than later after the stressor. No other variable varied significantly due to the stressor. Conclusions This study suggests that the idiosyncratic and inconsistent voice changes reported in the literature may be explained by differences in stress system activation. In addition, laryngeal aerodynamic measures appear resilient to changes due to acute stress. Further work is needed to examine the influence of other stress systems and if these findings hold for dysphonic individuals.

Worldwide Healthy Adult Voice Baseline Parameters: A Comprehensive Review

The voice results in acoustic signals analyzed and synthetized at first for telecommunication matters, and more recently investigated for medical purposes. In particular, voice signal characteristics can evidence individual health conditions useful for screening, diagnostic and remote monitoring aims. Within this frame, the knowledge of baseline features of healthy voice is mandatory, in order to balance a comparison with their unhealthy counterpart. However, the baseline features of the human voice depend on gender, age-range and ethnicity and, as far as we know, no work reports as those features spread worldwide. This paper intends to cover this lack. Our database research yielded 179 relevant published studies, retrieved using digital libraries of IEEE Xplore, Scopus, Web of Science, Iop Science, Taylor and Francis Online, and Scitepress. These relevant studies report different features, among which here we consider the most investigated ones, within the most investigated age-range. In particular, the features are the fundamental frequency, the jitter, the shimmer, the harmonic-to-noise ratio, and the cepstral peak prominence, the most investigated age-range is within 20-40 years and, related to the ethnicity, 20 countries are considered.