Search Results (31)

Objective: This study aims to critically review and synthesize the existing literature on the use of voice analysis in assessing nasal obstruction, with a particular focus on acoustic parameters. Data sources: PubMed, Scopus, Web of Science, Ovid Medline, and Science Direct. Review methods: A comprehensive literature search was conducted without any restrictions on publication year, employing Boolean search techniques. The selection and review process of the studies followed PRISMA guidelines. The inclusion criteria comprised studies with participants aged 18 years and older who had nasal obstruction evaluated using acoustic voice analysis parameters, along with objective and/or subjective methods for assessing nasal obstruction. Results: Of the 174 abstracts identified, 118 were screened after the removal of duplicates. The full texts of 37 articles were reviewed. Only 10 studies met inclusion criteria. The majority of these studies found no significant correlations between voice parameters and nasal obstruction. Among the various acoustic parameters examined, shimmer was the most consistently affected, with statistically significant changes identified in three independent studies. A smaller number of studies reported notable findings for fundamental frequency (F0) and noise-related measures such as NHR/HNR. Conclusion: This systematic review critically evaluates existing studies on the use of voice analysis for assessing and monitoring nasal obstruction and hyponasality. The current evidence remains limited, as most investigations predominantly focus on glottic sound and dysphonia, with insufficient attention to the influence of the vocal tract, particularly the nasal cavities, on voice production. A notable gap exists in the integration of advanced analytical approaches, such as machine learning, in this field. Future research should focus on the use of advanced analytical approaches to specifically extrapolate the contribution of nasal resonance to voice thus defining the specific parameters in the voice spectrogram that can give precise information on nasal obstruction. Full article

Background and Objectives: Paragangliomas of the head and neck are rare neuroendocrine tumors originating from the paraganglia, which might be sympathetic or parasympathetic. Laryngeal paragangliomas are the rarest subtype of these tumors, with only 1.41% of all paragangliomas, arising from the supraglottic or subglottic paraganglia of the larynx. The vast majority of them are benign, but there are some cases in which they turn out to be malignant, and the only way to know with certainty the difference between them is when we identify distant metastases. The aim of this article is to share our experience with a rare case of laryngeal paraganglioma and review the clinical characteristics, methods of diagnostic, necessary investigation prior to the operation, and surgical management of this type of tumor. Materials and Methods: We present the case of a 68-year-old female patient, a non-smoker, who accused dysphagia, dysphonia, foreign body sensation, chronic cough, and hoarseness for six months. We performed a tracheostomy prior to biopsy to secure the airways in case of bleeding and then took a few biopsy samples. The histopathological exam revealed the presence of a laryngeal paraganglioma. An enhanced CT scan was performed in order to describe the localization, size, and invasion of the tumor. We also measured the vanillylmandelic acid from the urine to determine if the tumor produced catecholamines alongside a full cardiology and endocrinology examinations. In order to prevent massive bleeding during the operation, chemoembolization was attempted before surgery, but it was unsuccessful due to an anatomical variation of the left superior thyroid artery. She underwent surgery, first through transoral endoscopic microsurgery; however, we decided to undertake an external approach because of poor bleeding control, even though we had ligated both the superior thyroid artery and the external carotid artery, with a thyrotomy and laryngofissure achieving the complete resection of the tumor. Results: The patient was discharged 10 postoperative days later, with the recommendation of introducing food step-by-step from liquids to solids. She was decannulated after 30 days, with no complications regarding breathing, phonation, or deglutition. Twelve months after the surgery, we did not identify any local relapses of distant metastases. Conclusions: Laryngeal paragangliomas are rare neuroendocrine tumors that arise from the laryngeal paraganglia. Surgery is the best treatment option available, and it can be done by either an external approach or by transoral endoscopy. Enhanced CT or MRI, as well as full cardiological and endocrinological evaluation are mandatory prior to the operation. Measuring the catecholamines levels show the if the tumor is secretory. Controlling the bleeding poses the biggest challenge in performing the resection of the tumor, especially when a transoral endoscopic approach is chosen. Further standardized follow-up guidelines are required in the future. Full article

The study aimed to investigate and compare the accuracy and robustness of the multiparametric acoustic voice indices (MAVIs), namely the Dysphonia Severity Index (DSI), Acoustic Voice Quality Index (AVQI), Acoustic Breathiness Index (ABI), and Voice Wellness Index (VWI) measures in differentiating normal and dysphonic voices. The study group consisted of 129 adult individuals including 49 with normal voices and 80 patients with pathological voices. The diagnostic accuracy of the investigated MAVI in differentiating between normal and pathological voices was assessed using receiver operating characteristics (ROC). Moderate to strong positive linear correlations were observed between different MAVIs. The ROC statistical analysis revealed that all used measurements manifested in a high level of accuracy (area under the curve (AUC) of 0.80 and greater) and an acceptable level of sensitivity and specificity in discriminating between normal and pathological voices. However, with AUC 0.99, the VWI demonstrated the highest diagnostic accuracy. The highest Youden index equaled 0.93, revealing that a VWI cut-off of 4.45 corresponds with highly acceptable sensitivity (97.50%) and specificity (95.92%). In conclusion, the VWI was found to be beneficial in describing differences in voice quality status and discriminating between normal and dysphonic voices based on clinical diagnosis, i.e., dysphonia type, implying the VWI’s reliable voice screening potential. Full article

Head and neck squamous cell carcinoma (HNSCC) is linked to significant morbidity, adversely affecting survival and functional capacity. Post-treatment challenges such as pain, dysphonia, and dysphagia are common, prompting increased attention in survivorship research. Quality of Life (QoL) questionnaires, especially the MD Anderson Dysphagia Inventory (MDADI), are prevalent outcome measures in clinical studies but often lack parallel objective swallowing function evaluations, leading to potential outcome discrepancies. This study aimed to illuminate the relationship between subjective QoL (EQ-5D-5L and MDADI) measures and objective swallowing function (evaluated via Fiberoptic Endoscopic Evaluation of Swallowing, FEES) in patients with HNSCC. The analysis revealed a notable discordance between objective measures of swallowing function, such as the Penetration–Aspiration Scale (PAS) and residue ratings in the vallecula or piriform sinus, and patients’ subjective QoL assessments (p = 0.21). Despite the lack of correlation, swallowing-related QoL, as measured by the MDADI, was more indicative of disease severity than generic QoL assessments. Generic QoL scores did not demonstrate substantial variation between patients. In contrast, MDADI scores significantly declined with advancing tumor stage, multimodal therapy, and reliance on feeding tubes. However, the clinical significance of this finding was tempered by the less than 10-point difference in MDADI scores. The findings of this study underline the limitations of QoL measures as standalone assessments in patients with HNSCC, given their reliance on patient-perceived impairment. While subjective QoL is a crucial aspect of evaluating therapeutic success and patient-centric outcomes, it may fail to capture critical clinical details such as silent aspirations. Consequently, QoL assessments should be augmented by objective evaluations of swallowing function in clinical research and practice to ensure a holistic understanding of patient well-being and treatment impact. Full article

Laryngeal dystonia (LD), known or termed as spasmodic dysphonia, is a rare movement disorder with an unknown cause affecting the intrinsic laryngeal muscles. Neurophysiological studies point to perturbed inhibitory processes, while conventional genetic studies reveal fragments of genetic architecture in LD. The study’s aims are to (1) describe transcranial magnetic stimulation (TMS) methodology for studying the functional integrity of the corticospinal tract by stimulating the primary motor cortex (M1) for laryngeal muscle representation and recording motor evoked potentials (MEPs) from laryngeal muscles; (2) evaluate the results of TMS studies investigating the cortical silent period (cSP) in LD; and (3) present the standard treatments of LD, as well as the results of new theoretical views and treatment approaches like repetitive TMS and laryngeal vibration over the laryngeal muscles as the recent research attempts in treatment of LD. Neurophysiological findings point to a shortened duration of cSP in adductor LD and altered cSP duration in abductor LD individuals. Future TMS studies could further investigate the role of cSP in relation to standard laryngological measures and treatment options. A better understanding of the neurophysiological mechanisms might give new perspectives for the treatment of LD. Full article

Parkinson’s disease (PD) affects a large proportion of elderly people. Symptoms include tremors, slow movement, rigid muscles, and trouble speaking. With the aging of the developed world’s population, this number is expected to rise. The early detection of PD and avoiding its severe consequences require a precise and efficient system. Our goal is to create an accurate AI model that can identify PD using human voices. We developed a transformer-based method for detecting PD by retrieving dysphonia measures from a subject’s voice recording. It is uncommon to use a neural network (NN)-based solution for tabular vocal characteristics, but it has several advantages over a tree-based approach, including compatibility with continuous learning and the network’s potential to be linked with an image/voice encoder for a more accurate multi modal solution, shifting SOTA approach from tree-based to a neural network (NN) is crucial for advancing research in multimodal solutions. Our method outperforms the state of the art (SOTA), namely Gradient-Boosted Decision Trees (GBDTs), by at least 1% AUC, and the precision and recall scores are also improved. We additionally offered an XgBoost-based feature-selection method and a fully connected NN layer technique for including continuous dysphonia measures, in addition to the solution network. We also discussed numerous important discoveries relating to our suggested solution and deep learning (DL) and its application to dysphonia measures, such as how a transformer-based network is more resilient to increased depth compared to a simple MLP network. The performance of the proposed approach and conventional machine learning techniques such as MLP, SVM, and Random Forest (RF) have also been compared. A detailed performance comparison matrix has been added to this article, along with the proposed solution’s space and time complexity. Full article

Parkinson’s Disease and Adductor-type Spasmodic Dysphonia are two neurological disorders that greatly decrease the quality of life of millions of patients worldwide. Despite this great diffusion, the related diagnoses are often performed empirically, while it could be relevant to count on objective measurable biomarkers, among which researchers have been considering features related to voice impairment that can be useful indicators but that can sometimes lead to confusion. Therefore, here, our purpose was aimed at developing a robust Machine Learning approach for multi-class classification based on 6373 voice features extracted from a convenient voice dataset made of the sustained vowel/e/ and an ad hoc selected Italian sentence, performed by 111 healthy subjects, 51 Parkinson’s disease patients, and 60 dysphonic patients. Correlation, Information Gain, Gain Ratio, and Genetic Algorithm-based methodologies were compared for feature selection, to build subsets analyzed by means of Naïve Bayes, Random Forest, and Multi-Layer Perceptron classifiers, trained with a 10-fold cross-validation. As a result, spectral, cepstral, prosodic, and voicing-related features were assessed as the most relevant, the Genetic Algorithm performed as the most effective feature selector, while the adopted classifiers performed similarly. In particular, a Genetic Algorithm + Naïve Bayes approach brought one of the highest accuracies in multi-class voice analysis, being 95.70% for a sustained vowel and 99.46% for a sentence. Full article

Biometrics-based authentication has become the most well-established form of user recognition in systems that demand a certain level of security. For example, the most commonplace social activities stand out, such as access to the work environment or to one’s own bank account. Among all biometrics, voice receives special attention due to factors such as ease of collection, the low cost of reading devices, and the high quantity of literature and software packages available for use. However, these biometrics may have the ability to represent the individual impaired by the phenomenon known as dysphonia, which consists of a change in the sound signal due to some disease that acts on the vocal apparatus. As a consequence, for example, a user with the flu may not be properly authenticated by the recognition system. Therefore, it is important that automatic voice dysphonia detection techniques be developed. In this work, we propose a new framework based on the representation of the voice signal by the multiple projection of cepstral coefficients to promote the detection of dysphonic alterations in the voice through machine learning techniques. Most of the best-known cepstral coefficient extraction techniques in the literature are mapped and analyzed separately and together with measures related to the fundamental frequency of the voice signal, and its representation capacity is evaluated on three classifiers. Finally, the experiments on a subset of the Saarbruecken Voice Database prove the effectiveness of the proposed material in detecting the presence of dysphonia in the voice. Full article

Introduction: The aim of this study is to evaluate the clinical and radiological results of cervical disc arthroplasty (CDA) in patients with cervical spondylotic myelopathy (CSM) using the CP ESP^® disc prosthesis. Materials and Methods: Prospectively collected data of 56 patients with CSM have been analyzed. The mean age at surgery was 35.6 years (range: 25–43 years). The mean follow-up was 28.2 months (range: 13–42 months). The range of motion (ROM) of the index segments, as well as upper and lower adjacent segments, was measured before surgery and at final follow-up. The C2-C7 sagittal vertical axis (SVA), C2-C7 cervical lordosis (CL), and T1 slope minus cervical lordosis (T1s-CL) were analyzed as well. Pain intensity was measured preoperatively and during follow-up using an 11-point numeric rating scale (NRS). Modified Japanese Orthopaedic Association (mJOA) score was assessed preoperatively and during follow-up for the clinical assessment of myelopathy. Surgical and implant-associated complications were analyzed as well. Results: The NRS pain score improved from a mean of 7.4 (±1.1) preoperatively to a mean of 1.5 (±0.7) at last follow-up (p < 0.001). The mJOA score improved from a mean of 13.1 (±2.8) preoperatively to a mean of 14.8 (±2.3) at last follow-up (p < 0.001). The mean ROM of the index levels increased from 5.2° (±3.0) preoperatively to 7.3° (±3.2) at last follow-up (p < 0.05). Four patients developed heterotopic ossifications during follow-up. One patient developed permanent dysphonia. Conclusions: CDA showed good clinical and radiological outcome in this cohort of young patients. The motion of index segments could be preserved. CDA may be a viable treatment option in selected patients with CSM. Full article

Adductor spasmodic dysphonia is a type of adult-onset focal dystonia characterized by involuntary spasms of laryngeal muscles. This paper applied machine learning techniques for the severity assessment of spasmodic dysphonia. To this aim, 7 perceptual indices and 48 acoustical parameters were estimated from the Italian word /a’jwɔle/ emitted by 28 female patients, manually segmented from a standardized sentence and used as features in two classification experiments. Subjects were divided into three severity classes (mild, moderate, severe) on the basis of the G (grade) score of the GRB scale. The first aim was that of finding relationships between perceptual and objective measures with the Local Interpretable Model-Agnostic Explanations method. Then, the development of a diagnostic tool for adductor spasmodic dysphonia severity assessment was investigated. Reliable relationships between G; R (Roughness); B (Breathiness); Spasmodicity; and the acoustical parameters: voiced percentage, F2 median, and F1 median were found. After data scaling, Bayesian hyperparameter optimization, and leave-one-out cross-validation, a k-nearest neighbors model provided 89% accuracy in distinguishing patients among the three severity classes. The proposed methods highlighted the best acoustical parameters that could be used jointly with GRB indices to support the perceptual evaluation of spasmodic dysphonia and provide a tool to help severity assessment of spasmodic dysphonia. Full article

Parkinson’s disease (PD) is a complex degenerative brain disease that affects nerve cells in the brain responsible for body movement. Machine learning is widely used to track the progression of PD in its early stages by predicting unified Parkinson’s disease rating scale (UPDRS) scores. In this paper, we aim to develop a new method for PD diagnosis with the aid of supervised and unsupervised learning techniques. Our method is developed using the Laplacian score, Gaussian process regression (GPR) and self-organizing maps (SOM). SOM is used to segment the data to handle large PD datasets. The models are then constructed using GPR for the prediction of the UPDRS scores. To select the important features in the PD dataset, we use the Laplacian score in the method. We evaluate the developed approach on a PD dataset including a set of speech signals. The method was evaluated through root-mean-square error (RMSE) and adjusted R-squared (adjusted R²). Our findings reveal that the proposed method is efficient in the prediction of UPDRS scores through a set of speech signals (dysphonia measures). The method evaluation showed that SOM combined with the Laplacian score and Gaussian process regression with the exponential kernel provides the best results for R-squared (Motor-UPDRS = 0.9489; Total-UPDRS = 0.9516) and RMSE (Motor-UPDRS = 0.5144; Total-UPDRS = 0.5105) in predicting UPDRS compared with the other kernels in Gaussian process regression. Full article

Laryngeal cancer is an important oncological entity in which prognosis depends on the establishment of appropriate preventive and diagnostic measures, especially in high-risk populations. We present a retrospective two-year study (January 2021 to December 2022) with 152 patients diagnosed with laryngeal cancer from a tertiary hospital in Romania. The average age of the patients was 62 years old for both sexes, with a range from 44 to 83 years. The most frequent symptom was dysphonia with or without dyspnea in 142 cases (93.42%), followed by dyspnea alone in nine patients (5.92%) and dysphagia in one case (0.66%). Surgical treatment in this study consisted of partial laryngectomy (CO₂ laser transoral tumor ablation, supraglottic horizontal laryngectomy or hemilaryngectomy), or total laryngectomy. The main treatment was total laryngectomy (63%). For the eight patients with initial organ preservation treatment, the average time of recurrence was about two-and-a-half years. For the four patients who underwent a total circular pharyngo-laryngectomy, the upper digestive tract needed to be rebuilt with a salivary bypass tube or with a tubed myocutaneous flap from the major pectoralis muscle. One strong point is characteristic of the study group in gathering patients with advanced stages of laryngeal carcinoma candidates for salvage surgery and extended reconstruction methods. The development of new prevention protocols is mandatory in Eastern European countries. Full article

Adductor spasmodic dysphonia (AdSD) disrupts laryngeal muscle control during speech and, therefore, affects the onset and offset of phonation. In this study, the goal is to use laryngeal high-speed videoendoscopy (HSV) to measure the glottal attack time (GAT) and glottal offset time (GOT) during connected speech for normophonic (vocally normal) and AdSD voices. A monochrome HSV system was used to record readings of six CAPE-V sentences and part of the “Rainbow Passage” from the participants. Three raters visually analyzed the HSV data using a playback software to measure the GAT and GOT. The results show that the GAT was greater in the AdSD group than in the normophonic group; however, the clinical significance of the amount of this difference needs to be studied further. More variability was observed in both GATs and GOTs of the disorder group. Additionally, the GAT and GOT time series were found to be nonstationary for the AdSD group while they were stationary for the normophonic voices. This study shows that the GAT and GOT measures can be potentially used as objective markers to characterize AdSD. The findings will potentially help in the development of standardized measures for voice evaluation and the accurate diagnosis of AdSD. Full article

The aerodynamic voice assessment of subglottal air pressure can discriminate between speakers with typical voices from patients with voice disorders, with further evidence validating subglottal pressure as a clinical outcome measure. Although estimating subglottal pressure during phonation is an important component of a standard voice assessment, current methods for estimating subglottal pressure rely on non-natural speech tasks in a clinical or laboratory setting. This study reports on the validation of a method for subglottal pressure estimation in individuals with and without voice disorders that can be translated to connected speech to enable the monitoring of vocal function and behavior in real-world settings. During a laboratory calibration session, a participant-specific multiple regression model was derived to estimate subglottal pressure from a neck-surface vibration signal that can be recorded during natural speech production. The model was derived for vocally typical individuals and patients diagnosed with phonotraumatic vocal fold lesions, primary muscle tension dysphonia, and unilateral vocal fold paralysis. Estimates of subglottal pressure using the developed method exhibited significantly lower error than alternative methods in the literature, with average errors ranging from 1.13 to 2.08 cm H₂O for the participant groups. The model was then applied during activities of daily living, thus yielding ambulatory estimates of subglottal pressure for the first time in these populations. Results point to the feasibility and potential of real-time monitoring of subglottal pressure during an individual’s daily life for the prevention, assessment, and treatment of voice disorders. Full article

High cervical spinal cord stimulation (HCSCS) was found to have therapeutic effects on Parkinsonian gait disturbance. However, the results were inconsistent and confounded with symptoms of pain. This study aimed to reveal the gait and dysarthric effects of HCSCS in PD (Parkinson’s disease) and MSA-P (Parkinson variant of multiple system atrophy) patients without pain. Three PD and five MSA-P patients without painful comorbidities were assessed for gait performance and speech before SCS surgery and at 3- and 6-month follow-up. Stride length and the time spent in the Timed Up-and-Go task showed little change after HCSCS surgery. Overall voice quality (measured by dysphonia severity index) and perceptual speech intelligence improved significantly at 3 months, but improvements slightly diminished at 6 months postoperatively. Change in quality of life (measured by 8-item Parkinson’s disease questionnaire) was also notable at 3 months but narrowed over time following HCSCS. In conclusion, HCSCS showed therapeutic effects in improving the dysarthria but not gait disturbance in pain-free PD and MSA-P patients. Full article