The task of the present study was to investigate the relationship between parameters and factors predictive of voice quality and to suggest treatment guidelines for patients suffering from vocal polyps. In total, 158 patients diagnosed with vocal polyps and who received voice therapy were enrolled. Clinicomorphological factors such as size, location, color, and type of the polyp were evaluated. Perceptive and acoustic voice evaluation was conducted and the relationship of these voice parameters with clinicomorphological factors was analyzed. Additionally, factors favorable for voice therapy were investigated. GRBAS scale grade was closely related to acoustic parameters, such as jitter and shimmer. Univariate analysis showed the size of the polyp, the color of the vocal fold, a history of voice abuse, associated muscle tension dysphonia (MTD), and opposing reactive scar affected voice quality. In multivariate analysis, only the size of the polyp was associated with voice quality. The patients in whom the voice quality improved with voice therapy initially had smaller polyps and whitish-colored vocal folds. Results of the present study indicate that although the most influential factor on voice quality in vocal polyp patients was the size, several other factors should be considered in evaluating and treating vocal polyps. The size of the polyp and the color of the vocal fold are indicative of success or failure in voice therapy.
Download full-text PDF |
Source |
---|---|
http://dx.doi.org/10.1007/s00405-011-1618-7 | DOI Listing |
Clin Linguist Phon
January 2025
École d'orthophonie et d'audiologie, Faculté de médecine, Université de Montréal, Québec, Canada.
This article presents the Quebec French adaptation of the Consensus Auditory-Perceptual Evaluation of Voice (CAPE-V), a standardised protocol for evaluating voice quality. Developed through collaboration within the Quebec Voice Speech-Language Pathologist (SLP) Community of Practice, the adapted tool addresses linguistic and cultural nuances specific to Quebec French. This adaptation ensures standardised assessments and harmonises clinical and research practices across the province.
View Article and Find Full Text PDFInt J Chron Obstruct Pulmon Dis
January 2025
Department of Cardiology, Respiratory Medicine and Intensive Care, University Hospital Augsburg, Augsburg, Germany.
Background: Chronic obstructive pulmonary disease (COPD) affects breathing, speech production, and coughing. We evaluated a machine learning analysis of speech for classifying the disease severity of COPD.
Methods: In this single centre study, non-consecutive COPD patients were prospectively recruited for comparing their speech characteristics during and after an acute COPD exacerbation.
Digit Health
January 2025
Independent Researcher, Calgary, Alberta, Canada.
Digital health (DH) and artificial intelligence (AI) in healthcare are rapidly evolving but were addressed synonymously by many healthcare authorities and practitioners. A deep understanding and clarification of these concepts are fundamental and a prerequisite for developing robust frameworks and practical guidelines to ensure the safety, efficacy, and effectiveness of DH solutions and AI-embedded technologies. Categorizing DH into technologies (DHTs) and services (DHSs) enables regulatory, HTA, and reimbursement bodies to develop category-specific frameworks and guidelines for evaluating these solutions effectively.
View Article and Find Full Text PDFJ Voice
January 2025
Department of Speech and Language Therapy, School of Health Rehabilitation Sciences, University of Patras, Patras, Greece; A' ENT University Clinic, Medical School, National Kapodistreian University of Athens, Athens, Greece. Electronic address:
Objectives: The Singing Voice Handicap Index (SVHI) was culturally adapted and validated in Greek to examine the impacts of voice problems on a singer's everyday life.
Methods: The translated version was administered to 120 singers in total, along with the translated version of the Voice Handicap Index (VHI), a sort voice history questionnaire, two Self-Rating Dysphonia Severity Scales (SRDSSs), and two visual analog scales. A week after the original completion of the Greek version of SVHI, a second copy of the SVHI was administered to 50% of the participants.
Sensors (Basel)
January 2025
Instituto de Ciencias Aplicadas y Tecnología (ICAT), Universidad Nacional Autónoma de México, Ciudad de México C.P. 04510, Mexico.
Mobility is essential for individuals with physical disabilities, and wheelchairs significantly enhance their quality of life. Recent advancements focus on developing sophisticated control systems for effective and efficient interaction. This study evaluates the usability and performance of three wheelchair control modes manual, automatic, and voice controlled using a virtual reality (VR) simulation tool.
View Article and Find Full Text PDFEnter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!