Trial reportSensors (Basel, Switzerland)2019
Using Wearable and Non-Invasive Sensors to Measure Swallowing Function: Detection, Verification, and Clinical Application.
Trial report in Sensors (Basel, Switzerland), 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.
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The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
14 citing papers in PubMed, 28 citations in OpenAlex.
- Artificial intelligence tools for the assessment and management of dysphagia: a scoping review.BMJ open · 2026Article
- Patient Perceptions on a Wearable Sensor Technology for Swallowing: A Qualitative Study with Patients with Parkinson's Disease.Dysphagia · 2026Article
- Analysis of preoperative swallowing function in head and neck cancer patients based on fiberoptic endoscopic evaluation of swallowing (FEES): a cross-sectional study.BMC oral health · 2025Article
- Developing a Swallow-State Monitoring System Using Nasal Airflow, Surface Electromyography, and Thyroid Cartilage Movement Detection.Bioengineering (Basel, Switzerland) · 2024Article
- Identification of Respiratory Pauses during Swallowing by Unconstrained Measuring Using Millimeter Wave Radar.Sensors (Basel, Switzerland) · 2024Article
- Advancements and Challenges in Non-Invasive Sensor Technologies for Swallowing Assessment: A Review.Bioengineering (Basel, Switzerland) · 2024Review
- A fully integrated, standalone stretchable device platform with in-sensor adaptive machine learning for rehabilitation.Nature communications · 2023Article
- Multi-Sensor Respiratory-Swallow Telecare System for Safe Feeding in Different Trunk Inclinations: System Development and Clinical Application.Sensors (Basel, Switzerland) · 2023Article
- Swallow Detection with Acoustics and Accelerometric-Based Wearable Technology: A Scoping Review.International journal of environmental research and public health · 2022Article
- Synchronization between videofluoroscopic swallowing study and surface electromyography in patients with neurological involvement presenting symptoms of dysphagiaBiomedica : revista del Instituto Nacional de Salud · 2022Article
- Development of Piezoelectric Silk Sensors Doped with Graphene for Biosensing by Near-Field Electrospinning.Sensors (Basel, Switzerland) · 2022Article
- Wearable technology use for the analysis and monitoring of functions related to feeding and communication.CoDAS · 2022Article
- Noninvasive Measurement of Tongue Pressure and Its Correlation with Swallowing and Respiration.Sensors (Basel, Switzerland) · 2021Article
- Automatic Detection of the Pharyngeal Phase in Raw Videos for the Videofluoroscopic Swallowing Study Using Efficient Data Collection and 3D Convolutional NetworksSensors (Basel, Switzerland) · 2019Article
Corrections and comments
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Authors and funding
4 authors at 1 institution in 1 country.
Funding
Abstract
backgroundA widely used method for assessing swallowing dysfunction is the videofluoroscopic swallow study (VFSS) examination. However, this method has a risk of radiation exposure. Therefore, using wearable, non-invasive and radiation-free sensors to assess swallowing function has become a research trend. This study addresses the use of a surface electromyography sensor, a nasal airflow sensor, and a force sensing resistor sensor to monitor the coordination of respiration and larynx movement which are considered the major indicators of the swallowing function. The demand for an autodetection program that identifies the swallowing patterns from multiple sensors is raised. The main goal of this study is to show that the sensor-based measurement using the proposed detection program is able to detect early-stage swallowing disorders, which specifically, are useful for the assessment of the coordination between swallowing and respiration.
methodsThree sensors were used to collect the signals from submental muscle, nasal cavity, and thyroid cartilage, respectively, during swallowing. An analytic swallowing model was proposed based on these sensors. A set of temporal parameters related to the swallowing events in this model were defined and measured by an autodetection algorithm. The verification of this algorithm was accomplished by comparing the results from the sensors with the results from the VFSS. A clinical application of the long-term smoking effect on the swallowing function was detected by the proposed sensors and the program.
resultsThe verification results showed that the swallowing patterns obtained from the sensors strongly correlated with the laryngeal movement monitored from the VFSS. The temporal parameters measured from these two methods had insignificant delays which were all smaller than 0.03 s. In the smoking effect application, this study showed that the differences between the swallowing function of smoking and nonsmoking participants, as well as their disorders, is revealed by the sensor-based method without the VFSS examination.
conclusionsThis study showed that the sensor-based non-invasive measurement with the proposed detection algorithm is a viable method for temporal parameter measurement of the swallowing function.
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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.