ArticleScientific reports2021
OpenHSV: an open platform for laryngeal high-speed videoendoscopy.
Article in Scientific reports, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 papers.
What it found
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The trial behind it
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Who cites it
23 citing papers in PubMed, 45 citations in OpenAlex.
- Clinical Applications of Deep Learning for Glottal Area Segmentation and Glottal Area Waveform Feature Computation.IEEE open journal of engineering in medicine and biology · 2026Article
- Vocal Fold Kinematics in Phonotrauma From High Speed Videoendoscopy.The Laryngoscope · 2025Article
- Instrumental Voice Evaluation in Children: What Are We Getting?American journal of speech-language pathology · 2025Observational
- Approach to the Dynamics of the Vocal Cords During the Exploration With Flexible Laryngeal Stroboscopy.Laryngoscope investigative otolaryngology · 2025Article
- The Laryngovibrogram as a normalized spatiotemporal representation of vocal fold dynamics.Scientific reports · 2025Article
- GIRAFE: Glottal imaging dataset for advanced segmentation, analysis, and facilitative playbacks evaluation.Data in brief · 2025Review
- Comparative Evaluation of High-Speed Videoendoscopy and Laryngovideostroboscopy for Functional Laryngeal Assessment in Clinical Practice.Journal of clinical medicine · 2025Article
- Empirical Distribution of Glottal Edges (EDGE): A Statistical Assessment of Vocal Fold Kinematics Using High-Speed Videoendoscopy.IEEE journal of biomedical and health informatics · 2025Article
- Machine learning based assessment of hoarseness severity: a multi-sensor approach centered on high-speed videoendoscopy.Frontiers in artificial intelligence · 2025Article
- Scale for the assessment of mucosal wave dynamics of the free edges during stroboscopic examination: clinical validation study and analysis of results.European archives of oto-rhino-laryngology : official journal of the European Federation of Oto-Rhino-Laryngological Societies (EUFOS) : affiliated with the German Society for Oto-Rhino-Laryngology - Head and Neck Surgery · 2024Article
- Three-Dimensional Analysis of Vocal Fold Oscillations: Correlating Superior and Medial Surface Dynamics Using Ex Vivo Human Hemilarynges.Bioengineering (Basel, Switzerland) · 2024Article
- Value of high-speed videoendoscopy as an auxiliary tool in differentiation of benign and malignant unilateral vocal lesions.Journal of cancer research and clinical oncology · 2024Article
- Development and Application of Automated Vocal Fold Tracking Software in a Rat Surgical Model.The Laryngoscope · 2024Article
- Article
- Predicting 3D soft tissue dynamics from 2D imaging using physics informed neural networks.Communications biology · 2023Article
- Videostroboscopy Versus High-Speed Videoendoscopy: Factors Influencing Ratings of Laryngeal Oscillation.Journal of speech, language, and hearing research : JSLHR · 2023Article
- Laryngeal Imaging Study of Glottal Attack/Offset Time in Adductor Spasmodic Dysphonia during Connected Speech.Applied sciences (Basel, Switzerland) · 2023Article
- Localization and quantification of glottal gaps on deep learning segmentation of vocal folds.Scientific reports · 2023Article
- GlottisNetV2: Temporal Glottal Midline Detection Using Deep Convolutional Neural Networks.IEEE journal of translational engineering in health and medicine · 2023Article
- Re-Training of Convolutional Neural Networks for Glottis Segmentation in Endoscopic High-Speed Videos.Applied sciences (Basel, Switzerland) · 2022Article
Corrections and comments
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Authors and funding
4 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
High-speed videoendoscopy is an important tool to study laryngeal dynamics, to quantify vocal fold oscillations, to diagnose voice impairments at laryngeal level and to monitor treatment progress. However, there is a significant lack of an open source, expandable research tool that features latest hardware and data analysis. In this work, we propose an open research platform termed OpenHSV that is based on state-of-the-art, commercially available equipment and features a fully automatic data analysis pipeline. A publicly available, user-friendly graphical user interface implemented in Python is used to interface the hardware. Video and audio data are recorded in synchrony and are subsequently fully automatically analyzed. Video segmentation of the glottal area is performed using efficient deep neural networks to derive glottal area waveform and glottal midline. Established quantitative, clinically relevant video and audio parameters were implemented and computed. In a preliminary clinical study, we recorded video and audio data from 28 healthy subjects. Analyzing these data in terms of image quality and derived quantitative parameters, we show the applicability, performance and usefulness of OpenHSV. Therefore, OpenHSV provides a valid, standardized access to high-speed videoendoscopy data acquisition and analysis for voice scientists, highlighting its use as a valuable research tool in understanding voice physiology. We envision that OpenHSV serves as basis for the next generation of clinical HSV systems.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.