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Suarez-Patiño LV, Roldan-Vasco S, Suarez-Escudero JC, Orozco-Duque A, Perez-Giraldo E. sEMG as complementary tool for VFSS: A synchronized study in patients with neurogenic oropharyngeal dysphagia. J Electromyogr Kinesiol 2024; 78:102913. [PMID: 39004010 DOI: 10.1016/j.jelekin.2024.102913] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/20/2024] [Revised: 05/24/2024] [Accepted: 06/17/2024] [Indexed: 07/16/2024] Open
Abstract
The neurogenic oropharyngeal dysphagia is a prevalent functional swallowing disorder resulting from neurological causes. The conventional diagnosis involves ionizing radiation in Videofluoroscopy Swallowing Studies (VFSS). Surface electromyography (sEMG) offers a non-invasive alternative by recording muscle activity. This research compares bolus passage timing through anatomical structures using VFSS and sEMG-related activation times. Fifty confirmed oropharyngeal dysphagia patients underwent synchronized VFSS and sEMG, evaluating muscle groups during cracker and fluid ingestion. sEMG revealed activation patterns in masseters, suprahyoid, and infrahyoid muscles, occurring before bolus passage through the mandibular line and concluding near the upper esophageal sphincter complex. sEMG identified differences in dysphagia severity (EAT-10 score), age, and diagnosis, contrasting VFSS results. Results indicate potential complementarity between sEMG and VFSS for dysphagia screening, diagnosis, and monitoring.
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Affiliation(s)
- Laura V Suarez-Patiño
- Facultad de Ciencias Exactas y Aplicadas, Instituto Tecnológico Metropolitano, Medellín, Colombia.
| | | | - Juan Camilo Suarez-Escudero
- Escuela de Ciencias de la Salud, facultad de Medicina, Universidad Pontificia Bolivariana, Medellín, Colombia
| | | | - Estefania Perez-Giraldo
- Facultad de Ciencias Exactas y Aplicadas, Instituto Tecnológico Metropolitano, Medellín, Colombia
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2
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Wu Y, Guo K, Chu Y, Wang Z, Yang H, Zhang J. Advancements and Challenges in Non-Invasive Sensor Technologies for Swallowing Assessment: A Review. Bioengineering (Basel) 2024; 11:430. [PMID: 38790297 PMCID: PMC11118896 DOI: 10.3390/bioengineering11050430] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/02/2024] [Revised: 04/20/2024] [Accepted: 04/25/2024] [Indexed: 05/26/2024] Open
Abstract
Dysphagia is a pervasive health issue that impacts diverse demographic groups worldwide, particularly the elderly, stroke survivors, and those suffering from neurological disorders. This condition poses substantial health risks, including malnutrition, respiratory complications, and increased mortality. Additionally, it exacerbates economic burdens by extending hospital stays and escalating healthcare costs. Given that this disorder is frequently underestimated in vulnerable populations, there is an urgent need for enhanced diagnostic and therapeutic strategies. Traditional diagnostic tools such as the videofluoroscopic swallowing study (VFSS) and flexible endoscopic evaluation of swallowing (FEES) require interpretation by clinical experts and may lead to complications. In contrast, non-invasive sensors offer a more comfortable and convenient approach for assessing swallowing function. This review systematically examines recent advancements in non-invasive swallowing function detection devices, focusing on the validation of the device designs and their implementation in clinical practice. Moreover, this review discusses the swallowing process and the associated biomechanics, providing a theoretical foundation for the technologies discussed. It is hoped that this comprehensive overview will facilitate a paradigm shift in swallowing assessments, steering the development of technologies towards more accessible and accurate diagnostic tools, thereby improving patient care and treatment outcomes.
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Affiliation(s)
- Yuwen Wu
- Suzhou Institute of Biomedical Engineering and Technology, Chinese Academy of Sciences, Suzhou 215163, China
| | - Kai Guo
- Suzhou Institute of Biomedical Engineering and Technology, Chinese Academy of Sciences, Suzhou 215163, China
- School of Biomedical Engineering (Suzhou), Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei 230026, China
| | - Yuyi Chu
- Suzhou Institute of Biomedical Engineering and Technology, Chinese Academy of Sciences, Suzhou 215163, China
| | - Zhisen Wang
- Suzhou Institute of Biomedical Engineering and Technology, Chinese Academy of Sciences, Suzhou 215163, China
- School of Biomedical Engineering (Suzhou), Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei 230026, China
| | - Hongbo Yang
- Suzhou Institute of Biomedical Engineering and Technology, Chinese Academy of Sciences, Suzhou 215163, China
- School of Biomedical Engineering (Suzhou), Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei 230026, China
| | - Juzhong Zhang
- Suzhou Institute of Biomedical Engineering and Technology, Chinese Academy of Sciences, Suzhou 215163, China
- School of Biomedical Engineering (Suzhou), Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei 230026, China
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3
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Shirobe M, Edahiro A, Motokawa K, Morishita S, Motohashi Y, Matsubara C, Iwasaki M, Watanabe Y, Hirano H. Feasibility of Oral Function Evaluation According to Dementia Severity in Older Adults with Alzheimer's Disease. Nutrients 2024; 16:992. [PMID: 38613025 PMCID: PMC11013786 DOI: 10.3390/nu16070992] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/28/2024] [Revised: 03/23/2024] [Accepted: 03/25/2024] [Indexed: 04/14/2024] Open
Abstract
Oral function evaluation in older adults with dementia is important for determining appropriate and practical dietary support plans; however, it can be challenging due to their difficulties in comprehending instructions and cooperating during assessments. The feasibility of oral function evaluation has not been well studied. This cross-sectional study aimed to determine the feasibility of oral function evaluation in older adults with Alzheimer's disease (AD) according to Functional Assessment Staging of Alzheimer's Disease (FAST) stages. In total, 428 older adults with AD (45 men and 383 women; mean age: 87.2 ± 6.2 years) were included. Multilevel logistic regression models were used to examine the prevalence of participants who were unable to perform oral function evaluations, including oral diadochokinesis (ODK), repeated saliva swallow test (RSST), and modified water swallow test (MWST). In comparison to the reference category (combined FAST stage 1-3), FAST stage 7 was associated with the infeasibility of ODK (adjusted odds ratio, 95% confidence interval = 26.7, 4.2-168.6), RSST (5.9, 2.2-16.1), and MWST (8.7, 1.6-48.5, respectively). Oral function evaluation is difficult in older adults with severe AD. Simpler and more practical swallowing function assessments and indicators that can be routinely observed are required.
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Affiliation(s)
- Maki Shirobe
- Research Team for Promoting Independence and Mental Health, Tokyo Metropolitan Institute for Geriatrics and Gerontology, Tokyo 173-0015, Japan; (M.S.); (A.E.); (S.M.); (M.I.); (Y.W.); (H.H.)
| | - Ayako Edahiro
- Research Team for Promoting Independence and Mental Health, Tokyo Metropolitan Institute for Geriatrics and Gerontology, Tokyo 173-0015, Japan; (M.S.); (A.E.); (S.M.); (M.I.); (Y.W.); (H.H.)
| | - Keiko Motokawa
- Research Team for Promoting Independence and Mental Health, Tokyo Metropolitan Institute for Geriatrics and Gerontology, Tokyo 173-0015, Japan; (M.S.); (A.E.); (S.M.); (M.I.); (Y.W.); (H.H.)
| | - Shiho Morishita
- Research Team for Promoting Independence and Mental Health, Tokyo Metropolitan Institute for Geriatrics and Gerontology, Tokyo 173-0015, Japan; (M.S.); (A.E.); (S.M.); (M.I.); (Y.W.); (H.H.)
- School of Health Sciences, Meikai University, Chiba 279-8550, Japan
| | - Yoshiko Motohashi
- Research Team for Promoting Independence and Mental Health, Tokyo Metropolitan Institute for Geriatrics and Gerontology, Tokyo 173-0015, Japan; (M.S.); (A.E.); (S.M.); (M.I.); (Y.W.); (H.H.)
| | - Chiaki Matsubara
- Research Team for Promoting Independence and Mental Health, Tokyo Metropolitan Institute for Geriatrics and Gerontology, Tokyo 173-0015, Japan; (M.S.); (A.E.); (S.M.); (M.I.); (Y.W.); (H.H.)
- Department of Dental Hygiene, University of Shizuoka, Shizuoka Junior College, Shizuoka 422-8021, Japan
| | - Masanori Iwasaki
- Research Team for Promoting Independence and Mental Health, Tokyo Metropolitan Institute for Geriatrics and Gerontology, Tokyo 173-0015, Japan; (M.S.); (A.E.); (S.M.); (M.I.); (Y.W.); (H.H.)
- Department of Preventive Dentistry, Faculty of Dental Medicine, Graduate School of Dental Medicine, Hokkaido University, Hokkaido 060-8586, Japan
| | - Yutaka Watanabe
- Research Team for Promoting Independence and Mental Health, Tokyo Metropolitan Institute for Geriatrics and Gerontology, Tokyo 173-0015, Japan; (M.S.); (A.E.); (S.M.); (M.I.); (Y.W.); (H.H.)
- Gerodontology, Department of Oral Health Science, Hokkaido University, Hokkaido 060-8586, Japan
| | - Hirohiko Hirano
- Research Team for Promoting Independence and Mental Health, Tokyo Metropolitan Institute for Geriatrics and Gerontology, Tokyo 173-0015, Japan; (M.S.); (A.E.); (S.M.); (M.I.); (Y.W.); (H.H.)
- Dentistry and Oral Surgery, Tokyo Metropolitan Geriatric Hospital, Tokyo 173-0015, Japan
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4
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Seah JJ, Zhao J, Wang DY, Lee HP. Review on the Advancements of Stethoscope Types in Chest Auscultation. Diagnostics (Basel) 2023; 13:diagnostics13091545. [PMID: 37174938 PMCID: PMC10177339 DOI: 10.3390/diagnostics13091545] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/11/2023] [Revised: 04/16/2023] [Accepted: 04/20/2023] [Indexed: 05/15/2023] Open
Abstract
Stethoscopes were originally designed for the auscultation of a patient's chest for the purpose of listening to lung and heart sounds. These aid medical professionals in their evaluation of the cardiovascular and respiratory systems, as well as in other applications, such as listening to bowel sounds in the gastrointestinal system or assessing for vascular bruits. Listening to internal sounds during chest auscultation aids healthcare professionals in their diagnosis of a patient's illness. We performed an extensive literature review on the currently available stethoscopes specifically for use in chest auscultation. By understanding the specificities of the different stethoscopes available, healthcare professionals can capitalize on their beneficial features, to serve both clinical and educational purposes. Additionally, the ongoing COVID-19 pandemic has also highlighted the unique application of digital stethoscopes for telemedicine. Thus, the advantages and limitations of digital stethoscopes are reviewed. Lastly, to determine the best available stethoscopes in the healthcare industry, this literature review explored various benchmarking methods that can be used to identify areas of improvement for existing stethoscopes, as well as to serve as a standard for the general comparison of stethoscope quality. The potential use of digital stethoscopes for telemedicine amidst ongoing technological advancements in wearable sensors and modern communication facilities such as 5G are also discussed. Based on the ongoing trend in advancements in wearable technology, telemedicine, and smart hospitals, understanding the benefits and limitations of the digital stethoscope is an essential consideration for potential equipment deployment, especially during the height of the current COVID-19 pandemic and, more importantly, for future healthcare crises when human and resource mobility is restricted.
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Affiliation(s)
- Jun Jie Seah
- Department of Otolaryngology, Yong Loo Lin School of Medicine, National University of Singapore, Singapore 119228, Singapore
| | - Jiale Zhao
- Department of Mechanical Engineering, National University of Singapore, Singapore 117575, Singapore
| | - De Yun Wang
- Department of Otolaryngology, Yong Loo Lin School of Medicine, National University of Singapore, Singapore 119228, Singapore
- Infectious Diseases Translational Research Programme, Yong Loo Lin School of Medicine, National University of Singapore, Singapore 117545, Singapore
| | - Heow Pueh Lee
- Department of Mechanical Engineering, National University of Singapore, Singapore 117575, Singapore
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5
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Analysis of electrophysiological and mechanical dimensions of swallowing by non-invasive biosignals. Biomed Signal Process Control 2023. [DOI: 10.1016/j.bspc.2022.104533] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/28/2022]
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Hoffmann J, Roldan-Vasco S, Krüger K, Niekiel F, Hansen C, Maetzler W, Orozco-Arroyave JR, Schmidt G. Pilot Study: Magnetic Motion Analysis for Swallowing Detection Using MEMS Cantilever Actuators. SENSORS (BASEL, SWITZERLAND) 2023; 23:3594. [PMID: 37050654 PMCID: PMC10099077 DOI: 10.3390/s23073594] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 02/24/2023] [Revised: 03/22/2023] [Accepted: 03/28/2023] [Indexed: 06/19/2023]
Abstract
The swallowing process involves complex muscle coordination mechanisms. When alterations in such mechanisms are produced by neurological conditions or diseases, a swallowing disorder known as dysphagia occurs. The instrumental evaluation of dysphagia is currently performed by invasive and experience-dependent techniques. Otherwise, non-invasive magnetic methods have proven to be suitable for various biomedical applications and might also be applicable for an objective swallowing assessment. In this pilot study, we performed a novel approach for deglutition evaluation based on active magnetic motion sensing with permanent magnet cantilever actuators. During the intake of liquids with different consistency, we recorded magnetic signals of relative movements between a stationary sensor and a body-worn actuator on the cricoid cartilage. Our results indicate the detection capability of swallowing-related movements in terms of a characteristic pattern. Consequently, the proposed technique offers the potential for dysphagia screening and biofeedback-based therapies.
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Affiliation(s)
- Johannes Hoffmann
- Department of Electrical and Information Engineering, Faculty of Engineering, Kiel University, 24118 Kiel, Germany
| | - Sebastian Roldan-Vasco
- GITA Lab, Faculty of Engineering, Universidad de Antioquia, Medellín 050010, Colombia
- Faculty of Engineering, Instituto Tecnológico Metropolitano, Medellín 050536, Colombia
| | - Karolin Krüger
- Department of Electrical and Information Engineering, Faculty of Engineering, Kiel University, 24118 Kiel, Germany
| | - Florian Niekiel
- Fraunhofer Institute for Silicon Technology ISIT, 25524 Itzehoe, Germany
| | - Clint Hansen
- Department of Neurology, Kiel University, 24118 Kiel, Germany
| | - Walter Maetzler
- Department of Neurology, Kiel University, 24118 Kiel, Germany
| | - Juan Rafael Orozco-Arroyave
- GITA Lab, Faculty of Engineering, Universidad de Antioquia, Medellín 050010, Colombia
- Pattern Recognition Lab, Friedrich-Alexander-Universität, 91054 Erlangen, Germany
| | - Gerhard Schmidt
- Department of Electrical and Information Engineering, Faculty of Engineering, Kiel University, 24118 Kiel, Germany
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7
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Mialland A, Atallah I, Bonvilain A. Toward a robust swallowing detection for an implantable active artificial larynx: a survey. Med Biol Eng Comput 2023; 61:1299-1327. [PMID: 36792845 DOI: 10.1007/s11517-023-02772-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/17/2022] [Accepted: 01/04/2023] [Indexed: 02/17/2023]
Abstract
Total laryngectomy consists in the removal of the larynx and is intended as a curative treatment for laryngeal cancer, but it leaves the patient with no possibility to breathe, talk, and swallow normally anymore. A tracheostomy is created to restore breathing through the throat, but the aero-digestive tracts are permanently separated and the air no longer passes through the nasal tracts, which allowed filtration, warming, humidification, olfaction, and acceleration of the air for better tissue oxygenation. As for phonation restoration, various techniques allow the patient to talk again. The main one consists of a tracheo-esophageal valve prosthesis that makes the air passes from the esophagus to the pharynx, and makes the air vibrate to allow speech through articulation. Finally, swallowing is possible through the original tract as it is now isolated from the trachea. Yet, many methods exist to detect and assess a swallowing, but none is intended as a definitive restoration technique of the natural airway, which would permanently close the tracheostomy and avoid its adverse effects. In addition, these methods are non-invasive and lack detection accuracy. The feasibility of an effective early detection of swallowing would allow to further develop an implantable active artificial larynx and therefore restore the aero-digestive tracts. A previous attempt has been made on an artificial larynx implanted in 2012, but no active detection was included and the system was completely mechanic. This led to residues in the airway because of the imperfect sealing of the mechanism. An active swallowing detection coupled with indwelling measurements would thus likely add a significant reliability on such a system as it would allow to actively close an artificial larynx. So, after a brief explanation of the swallowing mechanism, this survey intends to first provide a detailed consideration of the anatomical region involved in swallowing, with a detection perspective. Second, the swallowing mechanism following total laryngectomy surgery is detailed. Third, the current non-invasive swallowing detection technique and their limitations are discussed. Finally, the previous points are explored with regard to the inherent requirements for the feasibility of an effective swallowing detection for an artificial larynx. Graphical Abstract.
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Affiliation(s)
- Adrien Mialland
- Institute of Engineering and Management Univ. Grenoble Alpes, Univ. Grenoble Alpes, CNRS, Grenoble INP, Gipsa-lab, 38000, Grenoble, France.
| | - Ihab Atallah
- Institute of Engineering and Management Univ. Grenoble Alpes, Otorhinolaryngology, CHU Grenoble Alpes, 38700, La Tronche, France
| | - Agnès Bonvilain
- Institute of Engineering and Management Univ. Grenoble Alpes, Univ. Grenoble Alpes, CNRS, Grenoble INP, Gipsa-lab, 38000, Grenoble, France
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Lim HJ, Lai DKH, So BPH, Yip CCK, Cheung DSK, Cheung JCW, Wong DWC. A Comprehensive Assessment Protocol for Swallowing (CAPS): Paving the Way towards Computer-Aided Dysphagia Screening. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2023; 20:2998. [PMID: 36833691 PMCID: PMC9963613 DOI: 10.3390/ijerph20042998] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 01/06/2023] [Revised: 02/04/2023] [Accepted: 02/06/2023] [Indexed: 06/18/2023]
Abstract
Dysphagia is one of the most common problems among older adults, which might lead to aspiration pneumonia and eventual death. It calls for a feasible, reliable, and standardized screening or assessment method to prompt rehabilitation measures and mitigate the risks of dysphagia complications. Computer-aided screening using wearable technology could be the solution to the problem but is not clinically applicable because of the heterogeneity of assessment protocols. The aim of this paper is to formulate and unify a swallowing assessment protocol, named the Comprehensive Assessment Protocol for Swallowing (CAPS), by integrating existing protocols and standards. The protocol consists of two phases: the pre-test phase and the assessment phase. The pre-testing phase involves applying different texture or thickness levels of food/liquid and determining the required bolus volume for the subsequent assessment. The assessment phase involves dry (saliva) swallowing, wet swallowing of different food/liquid consistencies, and non-swallowing (e.g., yawning, coughing, speaking, etc.). The protocol is designed to train the swallowing/non-swallowing event classification that facilitates future long-term continuous monitoring and paves the way towards continuous dysphagia screening.
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Affiliation(s)
- Hyo-Jung Lim
- Department of Biomedical Engineering, Faculty of Engineering, The Hong Kong Polytechnic University, Hong Kong, China
| | - Derek Ka-Hei Lai
- Department of Biomedical Engineering, Faculty of Engineering, The Hong Kong Polytechnic University, Hong Kong, China
| | - Bryan Pak-Hei So
- Department of Biomedical Engineering, Faculty of Engineering, The Hong Kong Polytechnic University, Hong Kong, China
| | | | - Daphne Sze Ki Cheung
- School of Nursing, The Hong Kong Polytechnic University, Hong Kong, China
- Research Institute of Smart Ageing, The Hong Kong Polytechnic University, Hong Kong, China
| | - James Chung-Wai Cheung
- Department of Biomedical Engineering, Faculty of Engineering, The Hong Kong Polytechnic University, Hong Kong, China
- Research Institute of Smart Ageing, The Hong Kong Polytechnic University, Hong Kong, China
| | - Duo Wai-Chi Wong
- Department of Biomedical Engineering, Faculty of Engineering, The Hong Kong Polytechnic University, Hong Kong, China
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Khalifa Y, Donohue C, Coyle JL, Sejdic E. Autonomous Swallow Segment Extraction Using Deep Learning in Neck-Sensor Vibratory Signals From Patients With Dysphagia. IEEE J Biomed Health Inform 2023; 27:956-967. [PMID: 36417738 PMCID: PMC10079637 DOI: 10.1109/jbhi.2022.3224323] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/27/2022]
Abstract
Dysphagia occurs secondary to a variety of underlying etiologies and can contribute to increased risk of adverse events such as aspiration pneumonia and premature mortality. Dysphagia is primarily diagnosed and characterized by instrumental swallowing exams such as videofluoroscopic swallowing studies. videofluoroscopic swallowing studies involve the inspection of a series of radiographic images for signs of swallowing dysfunction. Though effective, videofluoroscopic swallowing studies are only available in certain clinical settings and are not always desirable or feasible for certain patients. Because of the limitations of current instrumental swallow exams, research studies have explored the use of acceleration signals collected from neck sensors and demonstrated their potential in providing comparable radiation-free diagnostic value as videofluoroscopic swallowing studies. In this study, we used a hybrid deep convolutional recurrent neural network that can perform multi-level feature extraction (localized and across time) to annotate swallow segments automatically via multi-channel swallowing acceleration signals. In total, we used signals and videofluoroscopic swallowing study images of 3144 swallows from 248 patients with suspected dysphagia. Compared to other deep network variants, our network was superior at detecting swallow segments with an average area under the receiver operating characteristic curve value of 0.82 (95% confidence interval: 0.807-0.841), and was in agreement with up to 90% of the gold standard-labeled segments.
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So BPH, Chan TTC, Liu L, Yip CCK, Lim HJ, Lam WK, Wong DWC, Cheung DSK, Cheung JCW. Swallow Detection with Acoustics and Accelerometric-Based Wearable Technology: A Scoping Review. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2022; 20:170. [PMID: 36612490 PMCID: PMC9819201 DOI: 10.3390/ijerph20010170] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 11/01/2022] [Revised: 12/12/2022] [Accepted: 12/20/2022] [Indexed: 06/17/2023]
Abstract
Swallowing disorders, especially dysphagia, might lead to malnutrition and dehydration and could potentially lead to fatal aspiration. Benchmark swallowing assessments, such as videofluoroscopy or endoscopy, are expensive and invasive. Wearable technologies using acoustics and accelerometric sensors could offer opportunities for accessible and home-based long-term assessment. Identifying valid swallow events is the first step before enabling the technology for clinical applications. The objective of this review is to summarize the evidence of using acoustics-based and accelerometric-based wearable technology for swallow detection, in addition to their configurations, modeling, and assessment protocols. Two authors independently searched electronic databases, including PubMed, Web of Science, and CINAHL. Eleven (n = 11) articles were eligible for review. In addition to swallowing events, non-swallowing events were also recognized by dry (saliva) swallowing, reading, yawning, etc., while some attempted to classify the types of swallowed foods. Only about half of the studies reported that the device attained an accuracy level of >90%, while a few studies reported poor performance with an accuracy of <60%. The reviewed articles were at high risk of bias because of the small sample size and imbalanced class size problem. There was high heterogeneity in assessment protocol that calls for standardization for swallowing, dry-swallowing and non-swallowing tasks. There is a need to improve the current wearable technology and the credibility of relevant research for accurate swallowing detection before translating into clinical screening for dysphagia and other swallowing disorders.
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Affiliation(s)
- Bryan Pak-Hei So
- Department of Biomedical Engineering, Faculty of Engineering, The Hong Kong Polytechnic University, Hong Kong
| | - Tim Tin-Chun Chan
- Department of Biomedical Engineering, Faculty of Engineering, The Hong Kong Polytechnic University, Hong Kong
| | - Liangchao Liu
- Physical Education Department, University of International Business and Economics, Beijing 100029, China
| | | | - Hyo-Jung Lim
- Department of Biomedical Engineering, Faculty of Engineering, The Hong Kong Polytechnic University, Hong Kong
| | - Wing-Kai Lam
- Sports Information and External Affairs Centre, Hong Kong Sports Institute, Hong Kong
| | - Duo Wai-Chi Wong
- Department of Biomedical Engineering, Faculty of Engineering, The Hong Kong Polytechnic University, Hong Kong
| | - Daphne Sze Ki Cheung
- School of Nursing, The Hong Kong Polytechnic University, Hong Kong
- Research Institute of Smart Ageing, The Hong Kong Polytechnic University, Hong Kong
| | - James Chung-Wai Cheung
- Department of Biomedical Engineering, Faculty of Engineering, The Hong Kong Polytechnic University, Hong Kong
- Research Institute of Smart Ageing, The Hong Kong Polytechnic University, Hong Kong
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11
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Synchronization between videofluoroscopic swallowing study and surface electromyography in patients with neurological involvement presenting symptoms of dysphagia. BIOMEDICA : REVISTA DEL INSTITUTO NACIONAL DE SALUD 2022; 42:650-664. [PMID: 36511672 PMCID: PMC9814368 DOI: 10.7705/biomedica.6446] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 12/16/2021] [Indexed: 12/14/2022]
Abstract
Introduction: Dysphagia is defined as the difficulty in transporting food and liquids from the mouth to the stomach. The gold standard to diagnose this condition is the videofluoroscopic swallowing study. However, it exposes patients to ionizing radiation. Surface electromyography is a non-radioactive alternative for dysphagia evaluation that records muscle electrical activity during swallowing.
Objective: To evaluate the relationship between the relative activation times of the muscles involved in the oral and pharyngeal phases of swallowing and the kinematic events detected in the videofluoroscopy.
Materials and methods: Electromiographic signals from ten patients with neurological involvement who presented symptoms of dysphagia were analyzed simultaneously with
videofluoroscopy. Patients were given 5 ml of yogurt, 10 ml of water, and 3 g of crackers. Masseter, suprahyoid, and infrahyoid muscle groups were studied bilaterally. The bolus transit through the mandibular line, vallecula, and the cricopharyngeus muscle was analyzed in relation to the onset and offset times of each muscle group activation.
Results: The average time of the pharyngeal phase was 0.89 ± 0.12 s. Muscle activation was mostly observed prior to the bolus transit through the mandibular line and vallecula. The end of the muscle activity suggested that the passage of the bolus through the cricopharyngeus muscle was almost complete.
Conclusión: The muscle activity times, duration of the pharyngeal phase, and sequence of the muscle groups involved in swallowing were determined using sEMG validated with the videofluoroscopic swallowing study.
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Shu K, Mao S, Coyle JL, Sejdic E. Improving Non-Invasive Aspiration Detection With Auxiliary Classifier Wasserstein Generative Adversarial Networks. IEEE J Biomed Health Inform 2022; 26:1263-1272. [PMID: 34415842 PMCID: PMC8942096 DOI: 10.1109/jbhi.2021.3106565] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/06/2022]
Abstract
Aspiration is a serious complication of swallowing disorders. Adequate detection of aspiration is essential in dysphagia management and treatment. High-resolution cervical auscultation has been increasingly considered as a promising noninvasive swallowing screening tool and has inspired automatic diagnosis with advanced algorithms. The performance of such algorithms relies heavily on the amount of training data. However, the practical collection of cervical auscultation signal is an expensive and time-consuming process because of the clinical settings and trained experts needed for acquisition and interpretations. Furthermore, the relatively infrequent incidence of severe airway invasion during swallowing studies constrains the performance of machine learning models. Here, we produced supplementary training exemplars for desired class by capturing the underlying distribution of original cervical auscultation signal features using auxiliary classifier Wasserstein generative adversarial networks. A 10-fold subject cross-validation was conducted on 2079 sets of 36-dimensional signal features collected from 189 patients undergoing swallowing examinations. The proposed data augmentation outperforms basic data sampling, cost-sensitive learning and other generative models with significant enhancement. This demonstrates the remarkable potential of proposed network in improving classification performance using cervical auscultation signals and paves the way of developing accurate noninvasive swallowing evaluation in dysphagia care.
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Suzuki K, Shimizu Y, Ohshimo S, Oue K, Saeki N, Sadamori T, Tsutsumi Y, Irifune M, Shime N. Real-time assessment of swallowing sound using an electronic stethoscope and an artificial intelligence system. Clin Exp Dent Res 2022; 8:225-230. [PMID: 35018714 PMCID: PMC8874105 DOI: 10.1002/cre2.531] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/16/2020] [Revised: 11/02/2021] [Accepted: 12/14/2021] [Indexed: 12/01/2022] Open
Abstract
Objectives Daily assessments of swallowing function and interventions such as rehabilitation and dietary adjustments are necessary to improve dysphagia. Cervical auscultation is convenient for health care providers for assessing swallowing ability. Although this method allows for swallowing sound evaluations, sensory evaluations with this method are difficult. Thus, we aimed to assess swallowing sound by the combined use of an electronic stethoscope and an artificial intelligence (AI) system that incorporates sound recognition. Material and Methods Herein, 20 fifth‐year dentistry student volunteers were included; each participant was drank 10 ml and then 20 ml of water in different positions (sitting and supine). We developed an algorithm for indexing bolus inflow sounds using AI, which compared the swallowing sounds and created a new index. Results The new index value used for swallowing sound was significantly higher in men than in women and in the sitting position than in the supine position. A software for acoustic analysis confirmed that the swallowing index was significantly higher in men than in women as well as in the sitting position than in the supine position. These results were similar to those obtained using the new index. However, the new index substantially differed between sexes in terms of posture compared with effective sound pressure. Conclusions We developed a new algorithm for indexing swallowing sounds using a stethoscope and an AI system, which could identify swallowing sounds. For future research and development, evaluations of patients with dysphagia are necessary to determine the efficacy of the new index for bedside screening of swallowing conditions.
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Affiliation(s)
- Kazuma Suzuki
- Department of General Dentistry, Hiroshima University Hospital, Hiroshima, Japan
| | - Yoshitaka Shimizu
- Department of Dental Anesthesiology, Graduate School of Biomedical and Health Sciences, Hiroshima University, Hiroshima, Japan
| | - Shinichiro Ohshimo
- Department of Emergency and Critical Care Medicine, Graduate School of Biomedical and Health Sciences, Hiroshima University, Hiroshima, Japan
| | - Kana Oue
- Section of Dental Anesthesiology, Department of Oral & Maxillofacial Surgery and Oral Medicine, Hiroshima University Hospital, Hiroshima, Japan
| | - Noboru Saeki
- Department of Anesthesiology and Critical Care, Graduate School of Biomedical and Health Sciences, Hiroshima University, Hiroshima, Japan
| | - Takuma Sadamori
- Department of Emergency and Critical Care Medicine, Graduate School of Biomedical and Health Sciences, Hiroshima University, Hiroshima, Japan
| | - Yasuo Tsutsumi
- Department of Anesthesiology and Critical Care, Graduate School of Biomedical and Health Sciences, Hiroshima University, Hiroshima, Japan
| | - Masahiro Irifune
- Department of Dental Anesthesiology, Graduate School of Biomedical and Health Sciences, Hiroshima University, Hiroshima, Japan
| | - Nobuaki Shime
- Department of Emergency and Critical Care Medicine, Graduate School of Biomedical and Health Sciences, Hiroshima University, Hiroshima, Japan
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14
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O'Brien MK, Botonis OK, Larkin E, Carpenter J, Martin-Harris B, Maronati R, Lee K, Cherney LR, Hutchison B, Xu S, Rogers JA, Jayaraman A. Advanced Machine Learning Tools to Monitor Biomarkers of Dysphagia: A Wearable Sensor Proof-of-Concept Study. Digit Biomark 2021; 5:167-175. [PMID: 34723069 DOI: 10.1159/000517144] [Citation(s) in RCA: 15] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/16/2021] [Accepted: 05/10/2021] [Indexed: 11/19/2022] Open
Abstract
Introduction Difficulty swallowing (dysphagia) occurs frequently in patients with neurological disorders and can lead to aspiration, choking, and malnutrition. Dysphagia is typically diagnosed using costly, invasive imaging procedures or subjective, qualitative bedside examinations. Wearable sensors are a promising alternative to noninvasively and objectively measure physiological signals relevant to swallowing. An ongoing challenge with this approach is consolidating these complex signals into sensitive, clinically meaningful metrics of swallowing performance. To address this gap, we propose 2 novel, digital monitoring tools to evaluate swallows using wearable sensor data and machine learning. Methods Biometric swallowing and respiration signals from wearable, mechano-acoustic sensors were compared between patients with poststroke dysphagia and nondysphagic controls while swallowing foods and liquids of different consistencies, in accordance with the Mann Assessment of Swallowing Ability (MASA). Two machine learning approaches were developed to (1) classify the severity of impairment for each swallow, with model confidence ratings for transparent clinical decision support, and (2) compute a similarity measure of each swallow to nondysphagic performance. Task-specific models were trained using swallow kinematics and respiratory features from 505 swallows (321 from patients and 184 from controls). Results These models provide sensitive metrics to gauge impairment on a per-swallow basis. Both approaches demonstrate intrasubject swallow variability and patient-specific changes which were not captured by the MASA alone. Sensor measures encoding respiratory-swallow coordination were important features relating to dysphagia presence and severity. Puree swallows exhibited greater differences from controls than saliva swallows or liquid sips (p < 0.037). Discussion Developing interpretable tools is critical to optimize the clinical utility of novel, sensor-based measurement techniques. The proof-of-concept models proposed here provide concrete, communicable evidence to track dysphagia recovery over time. With refined training schemes and real-world validation, these tools can be deployed to automatically measure and monitor swallowing in the clinic and community for patients across the impairment spectrum.
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Affiliation(s)
- Megan K O'Brien
- Max Nader Lab for Rehabilitation Technologies and Outcomes Research, Shirley Ryan AbilityLab, Chicago, Illinois, USA.,Department of Physical Medicine and Rehabilitation, Northwestern University, Chicago, Illinois, USA
| | - Olivia K Botonis
- Max Nader Lab for Rehabilitation Technologies and Outcomes Research, Shirley Ryan AbilityLab, Chicago, Illinois, USA
| | - Elissa Larkin
- Think and Speak Lab, Shirley Ryan AbilityLab, Chicago, Illinois, USA
| | - Julia Carpenter
- Think and Speak Lab, Shirley Ryan AbilityLab, Chicago, Illinois, USA
| | - Bonnie Martin-Harris
- Department of Communication Sciences and Disorders, Northwestern University, Evanston, Illinois, USA
| | - Rachel Maronati
- Max Nader Lab for Rehabilitation Technologies and Outcomes Research, Shirley Ryan AbilityLab, Chicago, Illinois, USA
| | | | - Leora R Cherney
- Department of Physical Medicine and Rehabilitation, Northwestern University, Chicago, Illinois, USA.,Think and Speak Lab, Shirley Ryan AbilityLab, Chicago, Illinois, USA.,Department of Communication Sciences and Disorders, Northwestern University, Evanston, Illinois, USA
| | - Brianna Hutchison
- Department of Biomedical Engineering, Case Western Reserve University, Cleveland, Ohio, USA
| | - Shuai Xu
- Departments of Materials Science and Engineering, Center for Bio-Integrated Electronics, Biomedical Engineering, Electrical Engineering and Computer Science, Northwestern University, Evanston, Illinois, USA
| | - John A Rogers
- Departments of Materials Science and Engineering, Center for Bio-Integrated Electronics, Biomedical Engineering, Electrical Engineering and Computer Science, Northwestern University, Evanston, Illinois, USA
| | - Arun Jayaraman
- Max Nader Lab for Rehabilitation Technologies and Outcomes Research, Shirley Ryan AbilityLab, Chicago, Illinois, USA.,Department of Physical Medicine and Rehabilitation, Northwestern University, Chicago, Illinois, USA
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15
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McNulty J, de Jager K, Lancashire HT, Graveston J, Birchall M, Vanhoestenberghe A. Prediction of larynx function using multichannel surface EMG classification. IEEE TRANSACTIONS ON MEDICAL ROBOTICS AND BIONICS 2021; 3:1032-1039. [PMID: 34901764 PMCID: PMC7612081 DOI: 10.1109/tmrb.2021.3122966] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/14/2023]
Abstract
Total laryngectomy (TL) affects critical functions such as swallowing, coughing and speaking. An artificial, bio-engineered larynx (ABL), operated via myoelectric signals, may improve quality of life for TL patients. To evaluate the efficacy of using surface electromyography (sEMG) as a control signal to predict instances of swallowing, coughing and speaking, sEMG was recorded from submental, intercostal and diaphragm muscles. The cohort included TL and control participants. Swallowing, coughing, speaking and movement actions were recorded, and a range of classifiers were investigated for prediction of these actions. Our algorithm achieved F1-scores of 76.0 ± 4.4 % (swallows), 93.8 ± 2.8 % (coughs) and 70.5 ± 5.4 % (speech) for controls, and 67.7 ± 4.4 % (swallows), 71.0 ± 9.1 % (coughs) and 78.0 ± 3.8 % (speech) for TLs, using a random forest (RF) classifier. 75.1 ± 6.9 % of swallows were detected within 500 ms of onset in the controls, and 63.1 ± 6.1 % in TLs. sEMG can be used to predict critical larynx movements, although a viable ABL requires improvements. Results are particularly encouraging as they encompass a TL cohort. An ABL could alleviate many challenges faced by laryngectomees. This study represents a promising step toward realising such a device.
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Affiliation(s)
- Johnny McNulty
- corresponding author: . H.T. Lancashire is with the Department of Medical Physics and Biomedical Engineering, UCL. J. Graveston was with the UCL Ear Institute, UCL, M. Birchall is with the UCL Ear Institute, Division of Brain Sciences and Royal National Nose and Throat and Eastman Dental Hospitals, UCL
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16
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Mootassim‐Billah S, Van Nuffelen G, Schoentgen J, De Bodt M, Dragan T, Digonnet A, Roper N, Van Gestel D. Assessment of cough in head and neck cancer patients at risk for dysphagia-An overview. Cancer Rep (Hoboken) 2021; 4:e1395. [PMID: 33932152 PMCID: PMC8551981 DOI: 10.1002/cnr2.1395] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/09/2020] [Revised: 02/22/2021] [Accepted: 03/26/2021] [Indexed: 11/06/2022] Open
Abstract
BACKGROUND This literature review explores the terminology, the neurophysiology, and the assessment of cough in general, in the framework of dysphagia and regarding head and neck cancer patients at risk for dysphagia. In the dysphagic population, cough is currently assessed perceptually during a clinical swallowing evaluation or aerodynamically. RECENT FINDINGS Recent findings have shown intra and inter-rater disagreements regarding perceptual scoring of cough. Also, aerodynamic measurements are impractical in a routine bedside assessment. Coughing, however, is considered to be a clinically relevant sign of aspiration and dysphagia in head and cancer patients treated with concurrent chemoradiotherapy. CONCLUSION This article surveys the literature regarding the established cough assessment and stresses the need to implement innovative methods for assessing cough in head and neck cancer patients treated with concurrent chemoradiotherapy at risk for dysphagia.
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Affiliation(s)
- Sofiana Mootassim‐Billah
- Department of Radiation Oncology, Speech Therapy, Institut Jules BordetUniversité Libre de BruxellesBrusselsBelgium
| | - Gwen Van Nuffelen
- Department of Otolaryngology and Head and Neck Surgery, University Rehabilitation Center for Communication DisordersAntwerp University HospitalAntwerpBelgium
- Department of Translational Neurosciences, Faculty of Medicine and Health SciencesUniversity of AntwerpAntwerpBelgium
- Department of Logopaedics and Audiological Sciences, Faculty of Medicine and Health SciencesUniversity of GhentGhentBelgium
| | - Jean Schoentgen
- BEAMS (Bio‐, Electro‐ And Mechanical Systems)Université Libre de BruxellesBrusselsBelgium
| | - Marc De Bodt
- Department of Otolaryngology and Head and Neck Surgery, University Rehabilitation Center for Communication DisordersAntwerp University HospitalAntwerpBelgium
- Department of Translational Neurosciences, Faculty of Medicine and Health SciencesUniversity of AntwerpAntwerpBelgium
- Department of Logopaedics and Audiological Sciences, Faculty of Medicine and Health SciencesUniversity of GhentGhentBelgium
| | - Tatiana Dragan
- Department of Radiation Oncology, Head and Neck Unit, Institut Jules BordetUniversité Libre de BruxellesBrusselsBelgium
| | - Antoine Digonnet
- Department of Surgical Oncology, Head and Neck Surgery Unit, Institut Jules BordetUniversité Libre de BruxellesBrusselsBelgium
| | - Nicolas Roper
- Department of Oto‐Rhino‐Laryngology and Head & Neck Surgery, Erasme HospitalUniversité Libre de BruxellesBrusselsBelgium
| | - Dirk Van Gestel
- Department of Radiation Oncology, Head and Neck Unit, Institut Jules BordetUniversité Libre de BruxellesBrusselsBelgium
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17
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Accuracy of Acoustic Evaluation of Swallowing as a Diagnostic Method of Dysphagia in Individuals Affected by Stroke: Preliminary Analysis. Dysphagia 2021; 37:724-735. [PMID: 34586494 DOI: 10.1007/s00455-021-10358-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/18/2020] [Accepted: 08/16/2021] [Indexed: 10/20/2022]
Abstract
After a stroke, more than half of the patients have some kind of disability, and dysphagia is frequently found. Cervical auscultation by Doppler sonar is an innovative technique with gain of credibility in the clinical evaluation of swallowing. To verify the diagnostic accuracy of Doppler sonar along with the DeglutiSom® software as an auxiliary method in the evaluation of oropharyngeal dysphagia in patients after stroke. The research is a cross-sectional, uncontrolled, blind, quantitative study with systematic random sampling. Patients from inpatient and outpatient units of a reference hospital with a stroke care unit were concomitantly submitted to both Doppler sonar and Fiberoptic Endoscopic Evaluation of Swallowing (FEES®). Seventy-three audio files collected from 26 patients through Doppler sonar were analyzed using DeglutiSom® software and confronted with the FEES® report, regarding three food consistencies offered to them during the exam. The study showed that the Doppler sonar correctly identified, among all the analyzed files, those that actually presented tracheal aspiration as well as it effectively identified patients who did not aspirate. The Youden index of 0.91 corroborates this information, showing a promising accuracy in detecting tracheal aspiration in the studied sample. The study evaluates the diagnostic accuracy of Doppler sonar, showing that it can be used as a valuable tool in the diagnosis of tracheal aspiration in patients after stroke. It is important to emphasize that the identification of residue by this method requires further studies. Also, larger sample size and more than one blind evaluator should be considered in future researches to increase the reliability of the proposed method.
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18
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Characterizing Effortful Swallows from Healthy Community Dwelling Adults Across the Lifespan Using High-Resolution Cervical Auscultation Signals and MBSImP Scores: A Preliminary Study. Dysphagia 2021; 37:1103-1111. [PMID: 34537905 PMCID: PMC8449695 DOI: 10.1007/s00455-021-10368-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/10/2020] [Accepted: 09/10/2021] [Indexed: 11/16/2022]
Abstract
There is growing enthusiasm to develop inexpensive, non-invasive, and portable methods that accurately assess swallowing and provide biofeedback during dysphagia treatment. High-resolution cervical auscultation (HRCA), which uses acoustic and vibratory signals from non-invasive sensors attached to the anterior laryngeal framework during swallowing, is a novel method for quantifying swallowing physiology via advanced signal processing and machine learning techniques. HRCA has demonstrated potential as a dysphagia screening method and diagnostic adjunct to VFSSs by determining swallowing safety, annotating swallow kinematic events, and classifying swallows between healthy participants and patients with a high degree of accuracy. However, its feasibility as a non-invasive biofeedback system has not been explored. This study investigated 1. Whether HRCA can accurately differentiate between non-effortful and effortful swallows; 2. Whether differences exist in Modified Barium Swallow Impairment Profile (MBSImP) scores (#9, #11, #14) between non-effortful and effortful swallows. We hypothesized that HRCA would accurately classify non-effortful and effortful swallows and that differences in MBSImP scores would exist between the types of swallows. We analyzed 247 thin liquid 3 mL command swallows (71 effortful) to minimize variation from 36 healthy adults who underwent standardized VFSSs with concurrent HRCA. Results revealed differences (p < 0.05) in 9 HRCA signal features between non-effortful and effortful swallows. Using HRCA signal features as input, decision trees classified swallows with 76% accuracy, 76% sensitivity, and 77% specificity. There were no differences in MBSImP component scores between non-effortful and effortful swallows. While preliminary in nature, this study demonstrates the feasibility/promise of HRCA as a biofeedback method for dysphagia treatment.
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19
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Donohue C, Khalifa Y, Mao S, Perera S, Sejdić E, Coyle JL. Characterizing Swallows From People With Neurodegenerative Diseases Using High-Resolution Cervical Auscultation Signals and Temporal and Spatial Swallow Kinematic Measurements. JOURNAL OF SPEECH, LANGUAGE, AND HEARING RESEARCH : JSLHR 2021; 64:3416-3431. [PMID: 34428093 PMCID: PMC8642099 DOI: 10.1044/2021_jslhr-21-00134] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/09/2021] [Revised: 04/21/2021] [Accepted: 05/21/2021] [Indexed: 06/13/2023]
Abstract
Purpose The prevalence of dysphagia in patients with neurodegenerative diseases (ND) is alarmingly high and frequently results in morbidity and accelerated mortality due to subsequent adverse events (e.g., aspiration pneumonia). Swallowing in patients with ND should be continuously monitored due to the progressive disease nature. Access to instrumental swallow evaluations can be challenging, and limited studies have quantified changes in temporal/spatial swallow kinematic measures in patients with ND. High-resolution cervical auscultation (HRCA), a dysphagia screening method, has accurately differentiated between safe and unsafe swallows, identified swallow kinematic events (e.g., laryngeal vestibule closure [LVC]), and classified swallows between healthy adults and patients with ND. This study aimed to (a) compare temporal/spatial swallow kinematic measures between patients with ND and healthy adults and (b) investigate HRCA's ability to annotate swallow kinematic events in patients with ND. We hypothesized there would be significant differences in temporal/spatial swallow measurements between groups and that HRCA would accurately annotate swallow kinematic events in patients with ND. Method Participants underwent videofluoroscopic swallowing studies with concurrent HRCA. We used linear mixed models to compare temporal/spatial swallow measurements (n = 170 ND patient swallows, n = 171 healthy adult swallows) and deep learning machine-learning algorithms to annotate specific temporal and spatial kinematic events in swallows from patients with ND. Results Differences (p < .05) were found between groups for several temporal and spatial swallow kinematic measures. HRCA signal features were used as input to machine-learning algorithms and annotated upper esophageal sphincter (UES) opening, UES closure, LVC, laryngeal vestibule reopening, and hyoid bone displacement with 66.25%, 85%, 68.18%, 70.45%, and 44.6% accuracy, respectively, compared to human judges' measurements. Conclusion This study demonstrates HRCA's potential in characterizing swallow function in patients with ND and other patient populations.
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Affiliation(s)
- Cara Donohue
- Department of Communication Science and Disorders, School of Health and Rehabilitation Sciences, University of Pittsburgh, PA
| | - Yassin Khalifa
- Department of Electrical and Computer Engineering, Swanson School of Engineering, University of Pittsburgh, PA
| | - Shitong Mao
- Department of Electrical and Computer Engineering, Swanson School of Engineering, University of Pittsburgh, PA
| | - Subashan Perera
- Division of Geriatric Medicine, Department of Medicine, University of Pittsburgh, PA
| | - Ervin Sejdić
- Department of Electrical and Computer Engineering, Swanson School of Engineering, University of Pittsburgh, PA
- Department of Bioengineering, Swanson School of Engineering, University of Pittsburgh, PA
- Department of Biomedical Informatics, University of Pittsburgh School of Medicine, PA
- Intelligent Systems Program, School of Computing and Information, University of Pittsburgh, PA
| | - James L. Coyle
- Department of Communication Science and Disorders, School of Health and Rehabilitation Sciences, University of Pittsburgh, PA
- Department of Otolaryngology, School of Medicine, University of Pittsburgh Medical Center, PA
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20
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Donohue C, Khalifa Y, Mao S, Perera S, Sejdić E, Coyle JL. Establishing Reference Values for Temporal Kinematic Swallow Events Across the Lifespan in Healthy Community Dwelling Adults Using High-Resolution Cervical Auscultation. Dysphagia 2021; 37:664-675. [PMID: 34018024 DOI: 10.1007/s00455-021-10317-0] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/18/2020] [Accepted: 05/13/2021] [Indexed: 11/29/2022]
Abstract
Few research studies have investigated temporal kinematic swallow events in healthy adults to establish normative reference values. Determining cutoffs for normal and disordered swallowing is vital for differentially diagnosing presbyphagia, variants of normal swallowing, and dysphagia; and for ensuring that different swallowing research laboratories produce consistent results in common measurements from different samples within the same population. High-resolution cervical auscultation (HRCA), a sensor-based dysphagia screening method, has accurately annotated temporal kinematic swallow events in patients with dysphagia, but hasn't been used to annotate temporal kinematic swallow events in healthy adults to establish dysphagia screening cutoffs. This study aimed to determine: (1) Reference values for temporal kinematic swallow events, (2) Whether HRCA can annotate temporal kinematic swallow events in healthy adults. We hypothesized (1) Our reference values would align with a prior study; (2) HRCA would detect temporal kinematic swallow events as accurately as human judges. Trained judges completed temporal kinematic measurements on 659 swallows (N = 70 adults). Swallow reaction time and LVC duration weren't different (p > 0.05) from a previously published historical cohort (114 swallows, N = 38 adults), while other temporal kinematic measurements were different (p < 0.05), suggesting a need for further standardization to feasibly pool data analyses across laboratories. HRCA signal features were used as input to machine learning algorithms and annotated UES opening (69.96% accuracy), UES closure (64.52% accuracy), LVC (52.56% accuracy), and LV re-opening (69.97% accuracy); providing preliminary evidence that HRCA can noninvasively and accurately annotate temporal kinematic measurements in healthy adults to determine dysphagia screening cutoffs.
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Affiliation(s)
- Cara Donohue
- Department of Communication Science and Disorders, School of Health and Rehabilitation Sciences, University of Pittsburgh, 6035 Forbes Tower, Pittsburgh, PA, 15260, USA
| | - Yassin Khalifa
- Department of Electrical and Computer Engineering, Swanson School of Engineering, University of Pittsburgh, Pittsburgh, PA, 15260, USA
| | - Shitong Mao
- Department of Electrical and Computer Engineering, Swanson School of Engineering, University of Pittsburgh, Pittsburgh, PA, 15260, USA
| | - Subashan Perera
- Division of Geriatrics, Department of Medicine, University of Pittsburgh, Pittsburgh, PA, 15261, USA
| | - Ervin Sejdić
- Department of Electrical and Computer Engineering, Swanson School of Engineering, University of Pittsburgh, Pittsburgh, PA, 15260, USA.,Department of Bioengineering, Swanson School of Engineering, University of Pittsburgh, Pittsburgh, PA, 15260, USA.,Department of Biomedical Informatics, School of Medicine Intelligent Systems Program, School of Computing and Information, University of Pittsburgh, Pittsburgh, PA, 15260, USA
| | - James L Coyle
- Department of Communication Science and Disorders, School of Health and Rehabilitation Sciences, University of Pittsburgh, 6035 Forbes Tower, Pittsburgh, PA, 15260, USA. .,Department of Otolaryngology, School of Medicine, University of Pittsburgh Medical Center, Pittsburgh, PA, 15260, USA.
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21
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Shu K, Coyle JL, Perera S, Khalifa Y, Sabry A, Sejdić E. Anterior-posterior distension of maximal upper esophageal sphincter opening is correlated with high-resolution cervical auscultation signal features. Physiol Meas 2021; 42. [PMID: 33601360 DOI: 10.1088/1361-6579/abe7cb] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/02/2020] [Accepted: 02/18/2021] [Indexed: 12/22/2022]
Abstract
Objective. Adequate upper esophageal sphincter (UES) opening is essential during swallowing to enable clearance of material into the digestive system, and videofluoroscopy (VF) is the most commonly deployed instrumental examination for assessment of UES opening. High-resolution cervical auscultation (HRCA) has been shown to be an effective, portable and cost-efficient screening tool for dysphagia with strong capabilities in non-invasively and accurately approximating manual measurements of VF images. In this study, we aimed to examine whether the HRCA signals are correlated to the manually measured anterior-posterior (AP) distension of maximal UES opening from VF recordings, under the hypothesis that they would be strongly associated.Approach. We developed a standardized method to spatially measure the AP distension of maximal UES opening in 203 swallows VF recording from 27 patients referred for VF due to suspected dysphagia. Statistical analysis was conducted to compare the manually measured AP distension of maximal UES opening from lateral plane VF images and features extracted from two sets of HRCA signal segments: whole swallow segments and segments excluding all events other than the duration of UES is opening.Main results. HRCA signal features were significantly associated with the normalized AP distension of the maximal UES opening in the longer whole swallowing segments and the association became much stronger when analysis was performed solely during the duration of UES opening.Significance. This preliminary feasibility study demonstrated the potential value of HRCA signals features in approximating the objective measurements of maximal UES AP distension and paves the way of developing HRCA to non-invasively and accurately predict human spatial measurement of VF kinematic events.
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Affiliation(s)
- Kechen Shu
- Department of Electrical and Computer Engineering, Swanson School of Engineering, University of Pittsburgh, Pittsburgh, PA, 15261, United States of America
| | - James L Coyle
- Department of Communication Science and Disorders, School of Health and Rehabilitation Sciences, Department of Otolaryngology, School of Medicine, University of Pittsburgh, PA, 15260, United States of America
| | - Subashan Perera
- Division of Geriatrics, Department of Medecine, University of Pittsburgh, Pittsburgh, PA, 15261, United States of America
| | - Yassin Khalifa
- Department of Electrical and Computer Engineering, Swanson School of Engineering, University of Pittsburgh, Pittsburgh, PA, 15261, United States of America
| | - Aliaa Sabry
- Department of Communication Science and Disorders, School of Health and Rehabilitation Sciences, University of Pittsburgh, PA, 15260, United States of America
| | - Ervin Sejdić
- Department of Electrical and Computer Engineering, Swanson School of Engineering, Department of Bioengineering, Swanson School of Engineering, Department of Biomedical informatics, School of Medecine, Intelligent Systems Program, School of Computing and Information, University of Pittsburgh, PA, 15260, United States of America
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22
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Khalifa Y, Donohue C, Coyle JL, Sejdic E. Upper Esophageal Sphincter Opening Segmentation With Convolutional Recurrent Neural Networks in High Resolution Cervical Auscultation. IEEE J Biomed Health Inform 2021; 25:493-503. [PMID: 32750928 DOI: 10.1109/jbhi.2020.3000057] [Citation(s) in RCA: 22] [Impact Index Per Article: 7.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/10/2022]
Abstract
Upper esophageal sphincter is an important anatomical landmark of the swallowing process commonly observed through the kinematic analysis of radiographic examinations that are vulnerable to subjectivity and clinical feasibility issues. Acting as the doorway of esophagus, upper esophageal sphincter allows the transition of ingested materials from pharyngeal into esophageal stages of swallowing and a reduced duration of opening can lead to penetration/aspiration and/or pharyngeal residue. Therefore, in this study we consider a non-invasive high resolution cervical auscultation-based screening tool to approximate the human ratings of upper esophageal sphincter opening and closure. Swallows were collected from 116 patients and a deep neural network was trained to produce a mask that demarcates the duration of upper esophageal sphincter opening. The proposed method achieved more than 90% accuracy and similar values of sensitivity and specificity when compared to human ratings even when tested over swallows from an independent clinical experiment. Moreover, the predicted opening and closure moments surprisingly fell within an inter-human comparable error of their human rated counterparts which demonstrates the clinical significance of high resolution cervical auscultation in replacing ionizing radiation-based evaluation of swallowing kinematics.
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23
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Mao S, Sabry A, Khalifa Y, Coyle JL, Sejdic E. Estimation of laryngeal closure duration during swallowing without invasive X-rays. FUTURE GENERATIONS COMPUTER SYSTEMS : FGCS 2021; 115:610-618. [PMID: 33100445 PMCID: PMC7584133 DOI: 10.1016/j.future.2020.09.040] [Citation(s) in RCA: 14] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/11/2023]
Abstract
Laryngeal vestibule (LV) closure is a critical physiologic event during swallowing, since it is the first line of defense against food bolus entering the airway. Identifying the laryngeal vestibule status, including closure, reopening and closure duration, provides indispensable references for assessing the risk of dysphagia and neuromuscular function. However, commonly used radiographic examinations, known as videofluoroscopy swallowing studies, are highly constrained by their radiation exposure and cost. Here, we introduce a non-invasive sensor-based system, that acquires high-resolution cervical auscultation signals from neck and accommodates advanced deep learning techniques for the detection of LV behaviors. The deep learning algorithm, which combined convolutional and recurrent neural networks, was developed with a dataset of 588 swallows from 120 patients with suspected dysphagia and further clinically tested on 45 samples from 16 healthy participants. For classifying the LV closure and opening statuses, our method achieved 78.94% and 74.89% accuracies for these two datasets, suggesting the feasibility of implementing sensor signals for LV prediction without traditional videofluoroscopy screening methods. The sensor supported system offers a broadly applicable computational approach for clinical diagnosis and biofeedback purposes in patients with swallowing disorders without the use of radiographic examination.
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Affiliation(s)
- Shitong Mao
- Department of Electrical and Computer Engineering, Swanson School of Engineering, University of Pittsburgh, Pittsburgh, PA 15260 USA
| | - Aliaa Sabry
- Department of Communication Science and Disorders, School of Health and Rehabilitation Sciences, University of Pittsburgh, Pittsburgh, PA 15260 USA
| | - Yassin Khalifa
- Department of Electrical and Computer Engineering, Swanson School of Engineering, University of Pittsburgh, Pittsburgh, PA 15260 USA
| | - James L Coyle
- Department of Communication Science and Disorders, School of Health and Rehabilitation Sciences, University of Pittsburgh, Pittsburgh, PA 15260 USA
| | - Ervin Sejdic
- Department of Electrical and Computer Engineering, Swanson School of Engineering, University of Pittsburgh, Pittsburgh, PA 15260 USA
- Department of Bioengineering, Swanson School of Engineering Department of Biomedical Informatics, School of Medicine Intelligent Systems Program, School of Computing and Information, University of Pittsburgh, Pittsburgh, PA 15260 USA
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24
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Rayneau P, Bouteloup R, Rouf C, Makris P, Moriniere S. Automatic Detection and Analysis of Swallowing Sounds in Healthy Subjects and in Patients with Pharyngolaryngeal Cancer. Dysphagia 2021; 36:984-992. [PMID: 33389178 DOI: 10.1007/s00455-020-10225-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/22/2019] [Accepted: 11/24/2020] [Indexed: 10/22/2022]
Abstract
Assessment of swallowing function is often invasive or involves irradiation. Analysis of swallowing sounds is a noninvasive method for assessment of swallowing but is not used in daily medical practice. Dysphagia could be the first symptom that occurs in head and neck cancer. This study evaluated a method for the automatic detection and analysis of swallowing sounds in healthy subjects and in patients with pharyngolaryngeal cancer. A smartphone application, developed for automatic detection and analysis of swallowing sounds was developed and tested in 12 healthy volunteers and in 26 patients with pharyngolaryngeal cancer. Swallowing sounds were recorded with a laryngophone during a standardized meal (100 mL mashed potatoes, 100 mL water, and 100 mL yogurt). Swallowing number and duration were noted; the results were compared to a standard swallowing sound analysis using the software AUDACITY®. There were no statistically significant differences in swallowing number or duration between the two analysis methods for the three types of foods in healthy volunteers and only for water in patients. In healthy volunteers, the results of our automatic analysis were comparable with those obtained with the standard analysis. However, a better discrimination of swallowing sounds is necessary for the algorithm to obtain reliable results with thicker food in patients with head and neck cancer.
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Affiliation(s)
- P Rayneau
- ENT and Head and Neck Surgery, University Hospital of Tours, 2 Boulevard Tonnelé, 37044, Tours, France. .,Service ORL Et Chirurgie Cervico-Faciale, CHU de Tours, 2 Boulevard Tonnelé, 37044, Tours, France.
| | - R Bouteloup
- Polytech School, University of Tours, 64 Avenue Jean Portalis, 37200, Tours, France
| | - C Rouf
- ENT and Head and Neck Surgery, University Hospital of Tours, 2 Boulevard Tonnelé, 37044, Tours, France
| | - P Makris
- Tours Fundamental and Applied Computer Laboratory, University of Tours, CNRS 7002, 64 Avenue Jean Portalis, 37200, Tours, France
| | - S Moriniere
- ENT and Head and Neck Surgery, University Hospital of Tours, 2 Boulevard Tonnelé, 37044, Tours, France.,Francois-Rabelais University of Tours, University Hospital of Tours, 10 Boulevard Tonnelé, 37032, Tours, France
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25
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Donohue C, Khalifa Y, Perera S, Sejdić E, Coyle JL. How Closely do Machine Ratings of Duration of UES Opening During Videofluoroscopy Approximate Clinician Ratings Using Temporal Kinematic Analyses and the MBSImP? Dysphagia 2020; 36:707-718. [PMID: 32955619 DOI: 10.1007/s00455-020-10191-2] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/01/2020] [Accepted: 09/14/2020] [Indexed: 10/23/2022]
Abstract
Clinicians evaluate swallow kinematic events by analyzing videofluoroscopy (VF) images for dysphagia management. The duration of upper esophageal sphincter opening (DUESO) is one important temporal swallow event, because reduced DUESO can result in pharyngeal residue and penetration/aspiration. VF is frequently used for evaluating swallowing but exposes patients to radiation and is not always feasible/readily available. High resolution cervical auscultation (HRCA) is a non-invasive, sensor-based dysphagia screening method that uses signal processing and machine learning to characterize swallowing. We investigated HRCA's ability to annotate DUESO and predict Modified Barium Swallow Impairment Profile (MBSImP) scores (component #14). We hypothesized that HRCA and machine learning techniques would detect DUESO with similar accuracy as human judges. Trained judges completed temporal kinematic measurements of DUESO on 719 swallows (116 patients) and 50 swallows (15 age-matched healthy adults). An MBSImP certified clinician completed MBSImP ratings on 100 swallows. A multi-layer convolutional recurrent neural network (CRNN) using HRCA signal features for input was used to detect DUESO. Generalized estimating equations models were used to determine statistically significant HRCA signal features for predicting DUESO MBSImP scores. A support vector machine (SVM) classifier and a leave-one-out procedure was used to predict DUESO MBSImP scores. The CRNN detected UES opening within a 3-frame tolerance for 82.6% of patient and 86% of healthy swallows and UES closure for 72.3% of patient and 64% of healthy swallows. The SVM classifier predicted DUESO MBSImP scores with 85.7% accuracy. This study provides evidence of HRCA's feasibility in detecting DUESO without VF images.
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Affiliation(s)
- Cara Donohue
- Department of Communication Science and Disorders, School of Health and Rehabilitation Sciences, University of Pittsburgh, 6035 Forbes Tower, Pittsburgh, PA, 15260, USA
| | - Yassin Khalifa
- Department of Electrical and Computer Engineering, Swanson School of Engineering, University of Pittsburgh, Pittsburgh, PA, 15260, USA
| | - Subashan Perera
- Division of Geriatrics, Department of Medicine, University of Pittsburgh, Pittsburgh, PA, 15261, USA
| | - Ervin Sejdić
- Department of Electrical and Computer Engineering, Swanson School of Engineering, University of Pittsburgh, Pittsburgh, PA, 15260, USA.,Department of Bioengineering, Swanson School of Engineering, University of Pittsburgh, Pittsburgh, PA, 15260, USA.,Department of Biomedical Informatics, School of Medicine, University of Pittsburgh, Pittsburgh, PA, 15260, USA.,Intelligent Systems Program, School of Computing and Information, University of Pittsburgh, Pittsburgh, PA, 15260, USA
| | - James L Coyle
- Department of Communication Science and Disorders, School of Health and Rehabilitation Sciences, University of Pittsburgh, 6035 Forbes Tower, Pittsburgh, PA, 15260, USA.
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26
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Donohue C, Khalifa Y, Perera S, Sejdić E, Coyle JL. A Preliminary Investigation of Whether HRCA Signals Can Differentiate Between Swallows from Healthy People and Swallows from People with Neurodegenerative Diseases. Dysphagia 2020; 36:635-643. [PMID: 32889627 DOI: 10.1007/s00455-020-10177-0] [Citation(s) in RCA: 14] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/19/2019] [Accepted: 08/24/2020] [Indexed: 12/13/2022]
Abstract
High-resolution cervical auscultation (HRCA) is an emerging method for non-invasively assessing swallowing by using acoustic signals from a contact microphone, vibratory signals from an accelerometer, and advanced signal processing and machine learning techniques. HRCA has differentiated between safe and unsafe swallows, predicted components of the Modified Barium Swallow Impairment Profile, and predicted kinematic events of swallowing such as hyoid bone displacement, laryngeal vestibular closure, and upper esophageal sphincter opening with a high degree of accuracy. However, HRCA has not been used to characterize swallow function in specific patient populations. This study investigated the ability of HRCA to differentiate between swallows from healthy people and people with neurodegenerative diseases. We hypothesized that HRCA would differentiate between swallows from healthy people and people with neurodegenerative diseases with a high degree of accuracy. We analyzed 170 swallows from 20 patients with neurodegenerative diseases and 170 swallows from 51 healthy age-matched adults who underwent concurrent video fluoroscopy with non-invasive neck sensors. We used a linear mixed model and several supervised machine learning classifiers that use HRCA signal features and a leave-one-out procedure to differentiate between swallows. Twenty-two HRCA signal features were statistically significant (p < 0.05) for predicting whether swallows were from healthy people or from patients with neurodegenerative diseases. Using the HRCA signal features alone, logistic regression and decision trees classified swallows between the two groups with 99% accuracy, 100% sensitivity, and 99% specificity. This provides preliminary research evidence that HRCA can differentiate swallow function between healthy and patient populations.
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Affiliation(s)
- Cara Donohue
- Department of Communication Science and Disorders, School of Health and Rehabilitation Sciences, University of Pittsburgh, 6035 Forbes Tower, Pittsburgh, PA, 15260, USA.
| | - Yassin Khalifa
- Department of Electrical and Computer Engineering, Swanson School of Engineering, University of Pittsburgh, Pittsburgh, PA, 15260, USA
| | - Subashan Perera
- Division of Geriatrics, Department of Medicine, University of Pittsburgh, Pittsburgh, PA, 15261, USA
| | - Ervin Sejdić
- Department of Electrical and Computer Engineering, Swanson School of Engineering, University of Pittsburgh, Pittsburgh, PA, 15260, USA.,Department of Bioengineering, Swanson School of Engineering, Department of Biomedical Informatics, School of Medicine Intelligent Systems Program, School of Computing and Information, University of Pittsburgh, Pittsburgh, PA, 15260, USA
| | - James L Coyle
- Department of Communication Science and Disorders, School of Health and Rehabilitation Sciences, University of Pittsburgh, 6035 Forbes Tower, Pittsburgh, PA, 15260, USA
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27
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Coyle JL, Sejdić E. High-Resolution Cervical Auscultation and Data Science: New Tools to Address an Old Problem. AMERICAN JOURNAL OF SPEECH-LANGUAGE PATHOLOGY 2020; 29:992-1000. [PMID: 32650655 PMCID: PMC7844341 DOI: 10.1044/2020_ajslp-19-00155] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/17/2019] [Revised: 01/15/2020] [Accepted: 02/16/2020] [Indexed: 06/11/2023]
Abstract
High-resolution cervical auscultation (HRCA) is an evolving clinical method for noninvasive screening of dysphagia that relies on data science, machine learning, and wearable sensors to investigate the characteristics of disordered swallowing function in people with dysphagia. HRCA has shown promising results in categorizing normal and disordered swallowing (i.e., screening) independent of human input, identifying a variety of swallowing physiological events as accurately as trained human judges. The system has been developed through a collaboration of data scientists, computer-electrical engineers, and speech-language pathologists. Its potential to automate dysphagia screening and contribute to evaluation lies in its noninvasive nature (wearable electronic sensors) and its growing ability to accurately replicate human judgments of swallowing data typically formed on the basis of videofluoroscopic imaging data. Potential contributions of HRCA when videofluoroscopic swallowing study may be unavailable, undesired, or not feasible for many patients in various settings are discussed, along with the development and capabilities of HRCA. The use of technological advances and wearable devices can extend the dysphagia clinician's reach and reinforce top-of-license practice for patients with swallowing disorders.
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Affiliation(s)
- James L. Coyle
- Department of Communication Science and Disorders, School of Health and Rehabilitation Sciences, University of Pittsburgh, PA
- Department of Otolaryngology, School of Medicine, University of Pittsburgh, PA
| | - Ervin Sejdić
- Department of Electrical and Computer Engineering, Swanson School of Engineering, University of Pittsburgh, PA
- Department of Bioengineering, Swanson School of Engineering, University of Pittsburgh, PA
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28
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Khalifa Y, Coyle JL, Sejdić E. Non-invasive identification of swallows via deep learning in high resolution cervical auscultation recordings. Sci Rep 2020; 10:8704. [PMID: 32457331 PMCID: PMC7251089 DOI: 10.1038/s41598-020-65492-1] [Citation(s) in RCA: 29] [Impact Index Per Article: 7.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/17/2019] [Accepted: 05/05/2020] [Indexed: 11/22/2022] Open
Abstract
High resolution cervical auscultation is a very promising noninvasive method for dysphagia screening and aspiration detection, as it does not involve the use of harmful ionizing radiation approaches. Automatic extraction of swallowing events in cervical auscultation is a key step for swallowing analysis to be clinically effective. Using time-varying spectral estimation of swallowing signals and deep feed forward neural networks, we propose an automatic segmentation algorithm for swallowing accelerometry and sounds that works directly on the raw swallowing signals in an online fashion. The algorithm was validated qualitatively and quantitatively using the swallowing data collected from 248 patients, yielding over 3000 swallows manually labeled by experienced speech language pathologists. With a detection accuracy that exceeded 95%, the algorithm has shown superior performance in comparison to the existing algorithms and demonstrated its generalizability when tested over 76 completely unseen swallows from a different population. The proposed method is not only of great importance to any subsequent swallowing signal analysis steps, but also provides an evidence that such signals can capture the physiological signature of the swallowing process.
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Affiliation(s)
- Yassin Khalifa
- Department of Electrical and Computer Engineering, Swanson School of Engineering, University of Pittsburgh, Pittsburgh, PA, USA
| | - James L Coyle
- Department of Communication Science and Disorders, School of Health and Rehabilitation Sciences, University of Pittsburgh, Pittsburgh, PA, USA
| | - Ervin Sejdić
- Department of Electrical and Computer Engineering, Swanson School of Engineering, University of Pittsburgh, Pittsburgh, PA, USA.
- Department of Bioengineering, Swanson School of Engineering, University of Pittsburgh, Pittsburgh, PA, USA.
- Department of Biomedical Informatics, School of Medicine, University of Pittsburgh, Pittsburgh, PA, USA.
- Intelligent Systems Program, School of Computing and Information, University of Pittsburgh, Pittsburgh, PA, USA.
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29
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Donohue C, Mao S, Sejdić E, Coyle JL. Tracking Hyoid Bone Displacement During Swallowing Without Videofluoroscopy Using Machine Learning of Vibratory Signals. Dysphagia 2020; 36:259-269. [PMID: 32419103 DOI: 10.1007/s00455-020-10124-z] [Citation(s) in RCA: 20] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/29/2019] [Accepted: 04/29/2020] [Indexed: 10/24/2022]
Abstract
Identifying physiological impairments of swallowing is essential for determining accurate diagnosis and appropriate treatment for patients with dysphagia. The hyoid bone is an anatomical landmark commonly monitored during analysis of videofluoroscopic swallow studies (VFSSs). Its displacement is predictive of penetration/aspiration and is associated with other swallow kinematic events. However, VFSSs are not always readily available/feasible and expose patients to radiation. High-resolution cervical auscultation (HRCA), which uses acoustic and vibratory signals from a microphone and tri-axial accelerometer, is under investigation as a non-invasive dysphagia screening method and potential adjunct to VFSS when it is unavailable or not feasible. We investigated the ability of HRCA to independently track hyoid bone displacement during swallowing with similar accuracy to VFSS, by analyzing vibratory signals from a tri-axial accelerometer using machine learning techniques. We hypothesized HRCA would track hyoid bone displacement with a high degree of accuracy compared to humans. Trained judges completed frame-by-frame analysis of hyoid bone displacement on 400 swallows from 114 patients and 48 swallows from 16 age-matched healthy adults. Extracted features from vibratory signals were used to train the predictive algorithm to generate a bounding box surrounding the hyoid body on each frame. A metric of relative overlapped percentage (ROP) compared human and machine ratings. The mean ROP for all swallows analyzed was 50.75%, indicating > 50% of the bounding box containing the hyoid bone was accurately predicted in every frame. This provides evidence of the feasibility of accurate, automated hyoid bone displacement tracking using HRCA signals without use of VFSS images.
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Affiliation(s)
- Cara Donohue
- Department of Communication Science and Disorders, School of Health and Rehabilitation Sciences, University of Pittsburgh, 6035 Forbes Tower, Pittsburgh, PA, 15260, USA
| | - Shitong Mao
- Department of Electrical and Computer Engineering, Swanson School of Engineering, Department of Bioengineering, Swanson School of Engineering, Department of Biomedical Informatics, School of Medicine Intelligent Systems Program, School of Computing and Information, University of Pittsburgh, Pittsburgh, PA, 15260, USA
| | - Ervin Sejdić
- Department of Electrical and Computer Engineering, Swanson School of Engineering, Department of Bioengineering, Swanson School of Engineering, Department of Biomedical Informatics, School of Medicine Intelligent Systems Program, School of Computing and Information, University of Pittsburgh, Pittsburgh, PA, 15260, USA
| | - James L Coyle
- Department of Communication Science and Disorders, School of Health and Rehabilitation Sciences, University of Pittsburgh, 6035 Forbes Tower, Pittsburgh, PA, 15260, USA.
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30
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Miyagi S, Sugiyama S, Kozawa K, Moritani S, Sakamoto SI, Sakai O. Classifying Dysphagic Swallowing Sounds with Support Vector Machines. Healthcare (Basel) 2020; 8:healthcare8020103. [PMID: 32326267 PMCID: PMC7349358 DOI: 10.3390/healthcare8020103] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/03/2020] [Revised: 04/09/2020] [Accepted: 04/16/2020] [Indexed: 11/16/2022] Open
Abstract
Swallowing sounds from cervical auscultation include information related to the swallowing function. Several studies have been conducted on the screening tests of dysphagia. The literature shows a significant difference between the characteristics of swallowing sounds obtained from different subjects (e.g., healthy and dysphagic subjects; young and old adults). These studies demonstrate the usefulness of swallowing sounds during dysphagic screening. However, the degree of classification for dysphagia based on swallowing sounds has not been thoroughly studied. In this study, we investigate the use of machine learning for classifying swallowing sounds into various types, such as normal swallowing or mild, moderate, and severe dysphagia. In particular, swallowing sounds were recorded from patients with dysphagia. Support vector machines (SVMs) were trained using some features extracted from the obtained swallowing sounds. Moreover, the accuracy of the classification of swallowing sounds using the trained SVMs was evaluated via cross-validation techniques. In the two-class scenario, wherein the swallowing sounds were divided into two categories (viz. normal and dysphagic subjects), the maximum F-measure was 78.9%. In the four-class scenario, where the swallowing sounds were divided into four categories (viz. normal subject, and mild, moderate, and severe dysphagic subjects), the F-measure values for the classes were 65.6%, 53.1%, 51.1%, and 37.1%, respectively.
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Affiliation(s)
- Shigeyuki Miyagi
- Department of Electronic Systems Engineering, Graduate School of Engineering, The University of Shiga Prefecture, Hikone, Shiga 522-8533, Japan; (S.S.); (S.-i.S.); (O.S.)
- Correspondence: ; Tel.: +81-749-28-9559
| | - Syo Sugiyama
- Department of Electronic Systems Engineering, Graduate School of Engineering, The University of Shiga Prefecture, Hikone, Shiga 522-8533, Japan; (S.S.); (S.-i.S.); (O.S.)
| | - Keiko Kozawa
- Department of Nutrition, School of Human Cultures, The University of Shiga Prefecture, Hikone, Shiga 522-8533, Japan;
| | - Sueyoshi Moritani
- Head, Neck, and Thyroid Surgery, Kusatsu General Hospital, 1660, Yabase, Kusatsu, Shiga 525-8585, Japan;
| | - Shin-ichi Sakamoto
- Department of Electronic Systems Engineering, Graduate School of Engineering, The University of Shiga Prefecture, Hikone, Shiga 522-8533, Japan; (S.S.); (S.-i.S.); (O.S.)
| | - Osamu Sakai
- Department of Electronic Systems Engineering, Graduate School of Engineering, The University of Shiga Prefecture, Hikone, Shiga 522-8533, Japan; (S.S.); (S.-i.S.); (O.S.)
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31
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Lee K, Ni X, Lee JY, Arafa H, Pe DJ, Xu S, Avila R, Irie M, Lee JH, Easterlin RL, Kim DH, Chung HU, Olabisi OO, Getaneh S, Chung E, Hill M, Bell J, Jang H, Liu C, Park JB, Kim J, Kim SB, Mehta S, Pharr M, Tzavelis A, Reeder JT, Huang I, Deng Y, Xie Z, Davies CR, Huang Y, Rogers JA. Mechano-acoustic sensing of physiological processes and body motions via a soft wireless device placed at the suprasternal notch. Nat Biomed Eng 2019; 4:148-158. [PMID: 31768002 PMCID: PMC7035153 DOI: 10.1038/s41551-019-0480-6] [Citation(s) in RCA: 138] [Impact Index Per Article: 27.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/03/2019] [Accepted: 10/11/2019] [Indexed: 01/23/2023]
Abstract
Skin-mounted soft electronics incorporating high-bandwidth triaxial accelerometers can provide broad classes of physiologically relevant information, such as mechanoacoustic signatures of underlying body processes (such as those captured by a stethoscope) and precision kinematics of core body motions. Here, we describe a wireless device designed to be conformally placed on the suprasternal notch for the continuous measurement of mechanoacoustic signals, from subtle vibrations of the skin at accelerations of ~10−3 m·s−2 to large motions of the entire body at ~10 m·s−2, and at frequencies up to ~800 Hz. Because th measurements are a complex superposition of signals that arise from locomotion, body orientation, swallowing, respiration, cardiac activity, vocal-fold vibrations and other sources, we used frequency-domain analysis and machine learning to obtain, from human subjects during natural daily activities and exercise, real-time recordings of heart rate, respiration rate, energy intensity and other essential vital signs, as well as talking time and cadence, swallow counts and patterns, and other unconventional biomarkers. We also used the device in sleep laboratories, and validated the measurements via polysomnography.
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Affiliation(s)
- KunHyuck Lee
- Simpson Querry Institute, Northwestern University, Chicago, IL, USA.,Department of Materials Science and Engineering, Northwestern University, Evanston, IL, USA
| | - Xiaoyue Ni
- Center for Bio-Integrated Electronics, Northwestern University, Evanston, IL, USA
| | - Jong Yoon Lee
- Center for Bio-Integrated Electronics, Northwestern University, Evanston, IL, USA
| | - Hany Arafa
- Simpson Querry Institute, Northwestern University, Chicago, IL, USA.,Department of Biomedical Engineering, Northwestern University, Evanston, IL, USA
| | - David J Pe
- Department of Chemistry, Northwestern University, Evanston, IL, USA
| | - Shuai Xu
- Simpson Querry Institute, Northwestern University, Chicago, IL, USA.,Center for Bio-Integrated Electronics, Northwestern University, Evanston, IL, USA.,Department of Dermatology, Feinberg School of Medicine, Northwestern University, Chicago, IL, USA
| | - Raudel Avila
- Department of Materials Science and Engineering, Northwestern University, Evanston, IL, USA.,Center for Bio-Integrated Electronics, Northwestern University, Evanston, IL, USA.,Department of Civil and Environmental Engineering, Northwestern University, Evanston, IL, USA.,Department of Mechanical Engineering, Northwestern University, Evanston, IL, USA
| | - Masahiro Irie
- Simpson Querry Institute, Northwestern University, Chicago, IL, USA.,Department of Electrical and Computer Engineering, Northwestern University, Evanston, IL, USA
| | - Joo Hee Lee
- Center for Bio-Integrated Electronics, Northwestern University, Evanston, IL, USA
| | - Ryder L Easterlin
- Department of Molecular Biosciences, Northwestern University, Evanston, IL, USA
| | - Dong Hyun Kim
- Department of Electrical and Computer Engineering, University of Illinois at Urbana-Champaign, Urbana, IL, USA
| | - Ha Uk Chung
- Simpson Querry Institute, Northwestern University, Chicago, IL, USA.,Department of Electrical and Computer Engineering, Northwestern University, Evanston, IL, USA
| | - Omolara O Olabisi
- Department of Biomedical Engineering, Northwestern University, Evanston, IL, USA
| | - Selam Getaneh
- Department of Mechanical Engineering, Northwestern University, Evanston, IL, USA
| | - Esther Chung
- Department of Biomedical Engineering, Northwestern University, Evanston, IL, USA
| | - Marc Hill
- Department of Biomedical Engineering, Northwestern University, Evanston, IL, USA
| | - Jeremy Bell
- Department of Economics, Northwestern University, Evanston, IL, USA
| | - Hokyung Jang
- Center for Bio-Integrated Electronics, Northwestern University, Evanston, IL, USA
| | - Claire Liu
- Simpson Querry Institute, Northwestern University, Chicago, IL, USA.,Department of Biomedical Engineering, Northwestern University, Evanston, IL, USA
| | - Jun Bin Park
- Department of Statistics, University of Illinois at Urbana-Champaign, Urbana, IL, USA
| | - Jungwoo Kim
- Center for Bio-Integrated Electronics, Northwestern University, Evanston, IL, USA
| | - Sung Bong Kim
- Department of Materials Science and Engineering, University of Illinois at Urbana-Champaign, Urbana, IL, USA
| | - Sunita Mehta
- Center for Bio-Integrated Electronics, Northwestern University, Evanston, IL, USA
| | - Matt Pharr
- Department of Mechanical Engineering, Texas A&M University, College Station, TX, USA
| | - Andreas Tzavelis
- Medical Scientist Training Program, Feinberg School of Medicine, Northwestern University, Chicago, IL, USA
| | - Jonathan T Reeder
- Department of Materials Science and Engineering, Northwestern University, Evanston, IL, USA.,Center for Bio-Integrated Electronics, Northwestern University, Evanston, IL, USA
| | - Ivy Huang
- Simpson Querry Institute, Northwestern University, Chicago, IL, USA.,Department of Materials Science and Engineering, Northwestern University, Evanston, IL, USA
| | - Yujun Deng
- Department of Materials Science and Engineering, Northwestern University, Evanston, IL, USA.,Center for Bio-Integrated Electronics, Northwestern University, Evanston, IL, USA.,Department of Civil and Environmental Engineering, Northwestern University, Evanston, IL, USA.,Department of Mechanical Engineering, Northwestern University, Evanston, IL, USA.,State Key Laboratory of Mechanical System and Vibration, Shanghai Jiao Tong University, Shanghai, China
| | - Zhaoqian Xie
- Department of Materials Science and Engineering, Northwestern University, Evanston, IL, USA. .,Center for Bio-Integrated Electronics, Northwestern University, Evanston, IL, USA. .,Department of Civil and Environmental Engineering, Northwestern University, Evanston, IL, USA. .,Department of Mechanical Engineering, Northwestern University, Evanston, IL, USA. .,State Key Laboratory of Structural Analysis for Industrial Equipment, Department of Engineering Mechanics, Dalian University of Technology, Dalian, China.
| | - Charles R Davies
- Carle Neuroscience Institute, Carle Physician Group, Urbana, IL, USA.
| | - Yonggang Huang
- Department of Materials Science and Engineering, Northwestern University, Evanston, IL, USA. .,Center for Bio-Integrated Electronics, Northwestern University, Evanston, IL, USA. .,Department of Civil and Environmental Engineering, Northwestern University, Evanston, IL, USA. .,Department of Mechanical Engineering, Northwestern University, Evanston, IL, USA.
| | - John A Rogers
- Simpson Querry Institute, Northwestern University, Chicago, IL, USA. .,Department of Materials Science and Engineering, Northwestern University, Evanston, IL, USA. .,Center for Bio-Integrated Electronics, Northwestern University, Evanston, IL, USA. .,Department of Biomedical Engineering, Northwestern University, Evanston, IL, USA. .,Department of Chemistry, Northwestern University, Evanston, IL, USA. .,Department of Mechanical Engineering, Northwestern University, Evanston, IL, USA. .,Department of Electrical and Computer Engineering, Northwestern University, Evanston, IL, USA. .,Department of Neurological Surgery, Northwestern University, Evanston, IL, USA.
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32
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He Q, Perera S, Khalifa Y, Zhang Z, Mahoney AS, Sabry A, Donohue C, Coyle JL, Sejdic E. The Association of High Resolution Cervical Auscultation Signal Features With Hyoid Bone Displacement During Swallowing. IEEE Trans Neural Syst Rehabil Eng 2019; 27:1810-1816. [PMID: 31443032 PMCID: PMC6746228 DOI: 10.1109/tnsre.2019.2935302] [Citation(s) in RCA: 17] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/07/2022]
Abstract
Recent publications have suggested that high-resolution cervical auscultation (HRCA) signals may provide an alternative non-invasive option for swallowing assessment. However, the relationship between hyoid bone displacement, a key component to safe swallowing, and HRCA signals is not thoroughly understood. Therefore, in this work we investigated the hypothesis that a strong relationship exists between hyoid displacement and HRCA signals. Videofuoroscopy data was collected for 129 swallows, simultaneously with vibratory/acoustic signals. Horizontal, vertical and hypotenuse displacements of the hyoid bone were measured through manual expert analysis of videofluoroscopy images. Our results showed that the vertical displacement of both the anterior and posterior landmarks of the hyoid bone was strongly associated with the Lempel-Ziv complexity of superior-inferior and anterior-posterior vibrations from HRCA signals. Horizontal and hypotenuse displacements of the posterior aspect of the hyoid bone were strongly associated with the standard deviation of swallowing sounds. Medial-Lateral vibrations and patient characteristics such as age, sex, and history of stroke were not significantly associated with the hyoid bone displacement. The results imply that some vibratory/acoustic features extracted from HRCA recordings can provide information about the magnitude and direction of hyoid bone displacement. These results provide additional support for using HRCA as a non-invasive tool to assess physiological aspects of swallowing such as the hyoid bone displacement.
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33
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Mao S, Zhang Z, Khalifa Y, Donohue C, Coyle JL, Sejdic E. Neck sensor-supported hyoid bone movement tracking during swallowing. ROYAL SOCIETY OPEN SCIENCE 2019; 6:181982. [PMID: 31417694 PMCID: PMC6689594 DOI: 10.1098/rsos.181982] [Citation(s) in RCA: 18] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 11/30/2018] [Accepted: 05/10/2019] [Indexed: 06/10/2023]
Abstract
Hyoid bone movement is an important physiological event during swallowing that contributes to normal swallowing function. In order to determine the adequate hyoid bone movement, clinicians conduct an X-ray videofluoroscopic swallowing study, which even though it is the gold-standard technique, has limitations such as radiation exposure and cost. Here, we demonstrated the ability to track the hyoid bone movement using a non-invasive accelerometry sensor attached to the surface of the human neck. Specifically, deep neural networks were used to mathematically describe the relationship between hyoid bone movement and sensor signals. Training and validation of the system were conducted on a dataset of 400 swallows from 114 patients. Our experiments indicated the computer-aided hyoid bone movement prediction has a promising performance when compared with human experts' judgements, revealing that the universal pattern of the hyoid bone movement is acquirable by the highly nonlinear algorithm. Such a sensor-supported strategy offers an alternative and widely available method for online hyoid bone movement tracking without any radiation side-effects and provides a pronounced and flexible approach for identifying dysphagia and other swallowing disorders.
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Affiliation(s)
- Shitong Mao
- Department of Electrical and Computer Engineering, Swanson School of Engineering, University of Pittsburgh, Pittsburgh, PA 15260, USA
| | - Zhenwei Zhang
- Department of Electrical and Computer Engineering, Swanson School of Engineering, University of Pittsburgh, Pittsburgh, PA 15260, USA
| | - Yassin Khalifa
- Department of Electrical and Computer Engineering, Swanson School of Engineering, University of Pittsburgh, Pittsburgh, PA 15260, USA
| | - Cara Donohue
- Department of Communication Science and Disorders, School of Health and Rehabilitation Sciences, University of Pittsburgh, Pittsburgh, PA 15260, USA
| | - James L Coyle
- Department of Communication Science and Disorders, School of Health and Rehabilitation Sciences, University of Pittsburgh, Pittsburgh, PA 15260, USA
| | - Ervin Sejdic
- Department of Electrical and Computer Engineering, Swanson School of Engineering, University of Pittsburgh, Pittsburgh, PA 15260, USA
- Department of Bioengineering, Swanson School of Engineering, University of Pittsburgh, Pittsburgh, PA 15260, USA
- Department of Biomedical Informatics, School of Medicine, University of Pittsburgh, Pittsburgh, PA 15260, USA
- Intelligent Systems Program, School of Computing and Information, University of Pittsburgh, Pittsburgh, PA 15260, USA
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Sejdić E, Malandraki GA, Coyle JL. Computational deglutition: Signal and image processing methods to understand swallowing and associated disorders. IEEE SIGNAL PROCESSING MAGAZINE 2019; 36:138-146. [PMID: 31631954 PMCID: PMC6800740 DOI: 10.1109/msp.2018.2875863] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/10/2023]
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Rebrion C, Zhang Z, Khalifa Y, Ramadan M, Kurosu A, Coyle JL, Perera S, Sejdic E. High-Resolution Cervical Auscultation Signal Features Reflect Vertical and Horizontal Displacements of the Hyoid Bone During Swallowing. IEEE JOURNAL OF TRANSLATIONAL ENGINEERING IN HEALTH AND MEDICINE-JTEHM 2018; 7:1800109. [PMID: 30701145 PMCID: PMC6345415 DOI: 10.1109/jtehm.2018.2881468] [Citation(s) in RCA: 17] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 03/01/2018] [Revised: 10/19/2018] [Accepted: 10/29/2018] [Indexed: 12/19/2022]
Abstract
Millions of people across the globe suffer from swallowing difficulties, known as dysphagia, which can lead to malnutrition, pneumonia, and even death. Swallowing cervical auscultation, which has been suggested as a noninvasive screening method for dysphagia, has not been associated yet with any physical events. In this paper, we have compared the hyoid bone displacement extracted from the videofluoroscopy images of 31 swallows to the signal features extracted from the cervical auscultation recordings captured with a tri-axial accelerometer and a microphone. First, the vertical displacement of the anterior part of the hyoid bone is related to the entropy rate of the superior–inferior swallowing vibrations and to the kurtosis of the swallowing sounds. Second, the vertical displacement of the posterior part of the hyoid bone is related to the bandwidth of the medial–lateral swallowing vibrations. Third, the horizontal displacements of the posterior and anterior parts of the hyoid bone are related to the spectral centroid of the superior–inferior swallowing vibrations and to the peak frequency of the medial–lateral swallowing vibrations, respectively. At last, the airway protection scores and the command characteristics were associated with the vertical and horizontal displacements, respectively, of the posterior part of the hyoid bone. Additional associations between the patients’ characteristics and auscultations’ signals were also observed. The hyoid bone maximal displacement is a cause of swallowing vibrations and sounds. High-resolution cervical auscultation may offer a noninvasive alternative for dysphagia screening and additional diagnostic information.
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Affiliation(s)
- Cedrine Rebrion
- Department of Electrical and Computer EngineeringSwanson School of EngineeringUniversity of PittsburghPittsburghPA15261USA
| | - Zhenwei Zhang
- Department of Electrical and Computer EngineeringSwanson School of EngineeringUniversity of PittsburghPittsburghPA15261USA
| | - Yassin Khalifa
- Department of Electrical and Computer EngineeringSwanson School of EngineeringUniversity of PittsburghPittsburghPA15261USA
| | - Mona Ramadan
- Department of Electrical and Computer EngineeringSwanson School of EngineeringUniversity of PittsburghPittsburghPA15261USA
| | - Atsuko Kurosu
- Department of the Communication Science and DisordersSchool of Health and Rehabilitation SciencesUniversity of PittsburghPittsburghPA15260USA
| | - James L Coyle
- Department of the Communication Science and DisordersSchool of Health and Rehabilitation SciencesUniversity of PittsburghPittsburghPA15260USA
| | - Subashan Perera
- Division of Geriatric MedicineDepartment of MedicineUniversity of PittsburghPittsburghPA15261USA
| | - Ervin Sejdic
- Department of Electrical and Computer EngineeringSwanson School of EngineeringUniversity of PittsburghPittsburghPA15261USA
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Kurosu A, Coyle JL, Dudik JM, Sejdic E. Detection of Swallow Kinematic Events From Acoustic High-Resolution Cervical Auscultation Signals in Patients With Stroke. Arch Phys Med Rehabil 2018; 100:501-508. [PMID: 30071198 DOI: 10.1016/j.apmr.2018.05.038] [Citation(s) in RCA: 18] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/08/2018] [Accepted: 05/12/2018] [Indexed: 11/26/2022]
Abstract
OBJECTIVE To examine whether there were any associations between high-resolution cervical auscultation (HRCA) acoustic signals recorded by a contact microphone and swallowing kinematic events during pharyngeal swallow as assessed by a videofluoroscopic (VF) examination. DESIGN Prospective pilot study. SETTING University teaching hospital, university research laboratories. PARTICIPANTS Patients (N=35) with stroke who have suspected dysphagia (26 men + 9 women; age = 65.8±11.2). METHODS VF recordings of 100 liquid swallows from 35 stroke patients were analyzed, and a variety of HRCA signal features to characterize each swallow were calculated. MAIN OUTCOME MEASURES Percent of signal feature maxima (peak) occurring within 0.1 seconds of swallow kinematic event identified from VF recording. RESULTS Maxima of HRCA signal features, such as standard deviation, skewness, kurtosis, centroid frequency, bandwidth, and wave entropy, were associated with hyoid elevation, laryngeal vestibule closure, and upper esophageal sphincter opening, and the contact of the base of the tongue and posterior pharyngeal wall. CONCLUSIONS Although the kinematic source of HRCA acoustic signals has yet to be fully elucidated, these results indicate a strong relationship between these HRCA signals and several swallow kinematic events. There is a potential for HRCA to be developed for diagnostic and rehabilitative clinical management of dysphagia.
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Affiliation(s)
- Atsuko Kurosu
- Department of Communication Science and Disorders, School of Health and Rehabilitation and Sciences, University of Pittsburgh, Pittsburgh, PA
| | - James L Coyle
- Department of Communication Science and Disorders, School of Health and Rehabilitation and Sciences, University of Pittsburgh, Pittsburgh, PA; Department of Otolaryngology, School of Medicine, University of Pittsburgh, Pittsburgh, PA
| | - Joshua M Dudik
- Department of Electrical and Computer Engineering, Swanson School of Engineering, University of Pittsburgh, Pittsburgh, PA
| | - Ervin Sejdic
- Department of Electrical and Computer Engineering, Swanson School of Engineering, University of Pittsburgh, Pittsburgh, PA.
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Dudik JM, Kurosu A, Coyle JL, Sejdić E. Dysphagia and its effects on swallowing sounds and vibrations in adults. Biomed Eng Online 2018; 17:69. [PMID: 29855309 PMCID: PMC5984479 DOI: 10.1186/s12938-018-0501-9] [Citation(s) in RCA: 19] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/22/2018] [Accepted: 05/17/2018] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND To utilize cervical auscultation as a means of screening for risk of dysphagia, we must first determine how the signal differs between healthy subjects and subjects with swallowing disorders. METHODS In this experiment we gathered swallowing sound and vibration data from 53 (13 with stroke, 40 without) patients referred for imaging evaluation of swallowing function with videofluoroscopy. The analysis was limited to non-aspirating swallows of liquid with either thin (< 5 cps) or viscous ([Formula: see text]) consistency. After calculating a selection of generalized time, frequency, and time frequency features for each swallow, we compared our data against our findings in a previous experiment that investigated identical features for a different group of 56 healthy subjects. RESULTS We found that nearly all of our chosen features for both vibrations and sounds showed significant differences between the healthy and disordered swallows despite the absence of aspiration. We also found only negligible differences between dysphagia as a symptom of stroke and dysphagia as a symptom of another condition. CONCLUSION Non-aspirating swallows from healthy controls and patients with dysphagia have distinct feature patterns. These findings should greatly help the development of the cervical auscultation field and serve as a reference for future investigations into more specialized characterization methods.
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Affiliation(s)
- Joshua M Dudik
- Department of Electrical and Computer Engineering, University of Pittsburgh, Pittsburgh, PA, USA
| | - Atsuko Kurosu
- Department of Communication Sciences and Disorders, University of Pittsburgh, Pittsburgh, PA, USA
| | - James L Coyle
- Department of Communication Sciences and Disorders, University of Pittsburgh, Pittsburgh, PA, USA
| | - Ervin Sejdić
- Department of Electrical and Computer Engineering, University of Pittsburgh, Pittsburgh, PA, USA.
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Dudik JM, Coyle JL, El-Jaroudi A, Mao ZH, Sun M, Sejdić E. Deep Learning for Classification of Normal Swallows in Adults. Neurocomputing 2018; 285:1-9. [PMID: 29755210 PMCID: PMC5944858 DOI: 10.1016/j.neucom.2017.12.059] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/18/2022]
Abstract
Cervical auscultation is a method for assessing swallowing performance. However, its ability to serve as a classification tool for a practical clinical assessment method is not fully understood. In this study, we utilized neural network classification methods in the form of Deep Belief networks in order to classify swallows. We specifically utilized swallows that did not result in clinically significant aspiration and classified them on whether they originated from healthy subjects or unhealthy patients. Dual-axis swallowing vibrations from 1946 discrete swallows were recorded from 55 healthy and 53 unhealthy subjects. The Fourier transforms of both signals were used as inputs to the networks of various sizes. We found that single and multi-layer Deep Belief networks perform nearly identically when analyzing only a single vibration signal. However, multi-layered Deep Belief networks demonstrated approximately a 5% to 10% greater accuracy and sensitivity when both signals were analyzed concurrently, indicating that higher-order relationships between these vibrations are important for classification and assessment.
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Affiliation(s)
- Joshua M Dudik
- Department of Electrical and Computer Engineering, Swanson School of Enginering, University of Pittsburgh, Pittsburgh, PA, USA
| | - James L Coyle
- Department of Communication Science and Disorders, School of Health and Rehabilitation Sciences, University of Pittsburgh, Pittsburgh, PA, USA
| | - Amro El-Jaroudi
- Department of Electrical and Computer Engineering, Swanson School of Enginering, University of Pittsburgh, Pittsburgh, PA, USA
| | - Zhi-Hong Mao
- Department of Electrical and Computer Engineering, Swanson School of Enginering, University of Pittsburgh, Pittsburgh, PA, USA
| | - Mingui Sun
- Department of Neurological Surgery, School of Medicine, University of Pittsburgh, Pittsburgh, PA, USA
| | - Ervin Sejdić
- Department of Electrical and Computer Engineering, Swanson School of Enginering, University of Pittsburgh, Pittsburgh, PA, USA
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Wang CM, Shieh WY, Weng YH, Hsu YH, Wu YR. Non-invasive assessment determine the swallowing and respiration dysfunction in early Parkinson's disease. Parkinsonism Relat Disord 2017; 42:22-27. [DOI: 10.1016/j.parkreldis.2017.05.024] [Citation(s) in RCA: 22] [Impact Index Per Article: 3.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/03/2017] [Revised: 05/06/2017] [Accepted: 05/25/2017] [Indexed: 11/30/2022]
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Movahedi F, Kurosu A, Coyle JL, Perera S, Sejdić E. A comparison between swallowing sounds and vibrations in patients with dysphagia. COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE 2017; 144:179-187. [PMID: 28495001 PMCID: PMC5455149 DOI: 10.1016/j.cmpb.2017.03.009] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/09/2016] [Revised: 01/27/2017] [Accepted: 03/09/2017] [Indexed: 06/07/2023]
Abstract
The cervical auscultation refers to the observation and analysis of sounds or vibrations captured during swallowing using either a stethoscope or acoustic/vibratory detectors. Microphones and accelerometers have recently become two common sensors used in modern cervical auscultation methods. There are open questions about whether swallowing signals recorded by these two sensors provide unique or complementary information about swallowing function; or whether they present interchangeable information. This study aims to compare of swallowing signals recorded by a microphone and a tri-axial accelerometer from 72 patients (mean age 63.94 ± 12.58 years, 42 male, 30 female), who had videofluoroscopic examination. The participants swallowed one or more boluses of thickened liquids of different consistencies, including thin liquids, nectar-thick liquids, and pudding. A comfortable self-selected volume from a cup or a controlled volume by the examiner from a 5 ml spoon was given to the participants. A broad feature set was extracted in time, information-theoretic, and frequency domains from each of 881 swallows presented in this study. The swallowing sounds exhibited significantly higher frequency content and kurtosis values than the swallowing vibrations. In addition, the Lempel-Ziv complexity was lower for swallowing sounds than those for swallowing vibrations. To conclude, information provided by microphones and accelerometers about swallowing function are unique and these two transducers are not interchangeable. Consequently, the selection of transducer would be a vital step in future studies.
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Affiliation(s)
- Faezeh Movahedi
- Department of Electrical and Computer Engineering, Swanson School of Enginering, University of Pittsburgh, Pittsburgh, PA, USA
| | - Atsuko Kurosu
- Department of Communication Science and Disorders, School of Health and Rehabilitation Sciences, University of Pittsburgh, Pittsburgh, PA, USA
| | - James L Coyle
- Department of Communication Science and Disorders, School of Health and Rehabilitation Sciences, University of Pittsburgh, Pittsburgh, PA, USA
| | - Subashan Perera
- Department of Medicine, Division of Geriatric Medicine, University of Pittsburgh, Pittsburgh, PA, USA
| | - Ervin Sejdić
- Department of Electrical and Computer Engineering, Swanson School of Enginering, University of Pittsburgh, Pittsburgh, PA, USA.
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Hennessey NW, Fisher G, Ciccone N. Developmental changes in pharyngeal swallowing acoustics: a comparison of adults and children. LOGOP PHONIATR VOCO 2017; 43:63-72. [DOI: 10.1080/14015439.2017.1326526] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/19/2022]
Affiliation(s)
| | - Gemma Fisher
- School of Psychology and Speech Pathology, Curtin University, Perth, Australia
- Department of Health, Government of Western Australia, Perth, Australia
| | - Natalie Ciccone
- School of Psychology and Speech Pathology, Curtin University, Perth, Australia
- School of Psychology and Social Science, Edith Cowan University, Joondalup, Australia
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Movahedi F, Kurosu A, Coyle JL, Perera S, Sejdic E. Anatomical Directional Dissimilarities in Tri-axial Swallowing Accelerometry Signals. IEEE Trans Neural Syst Rehabil Eng 2016; 25:447-458. [PMID: 27295677 DOI: 10.1109/tnsre.2016.2577882] [Citation(s) in RCA: 18] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/25/2023]
Abstract
Swallowing accelerometry is a noninvasive approach currently under consideration as an instrumental screening test for swallowing difficulties, with most current studies focusing on the swallowing vibrations in the anterior-posterior (A-P) and superior-inferior (S-I) directions. However, the displacement of the hyolaryngeal structure during the act of swallowing in patients with dysphagia involves declination of the medial-lateral (M-L), which suggests that the swallowing vibrations in the M-L direction have the ability to reveal additional details about the swallowing function. With this motivation, we performed a broad comparison of the swallowing vibrations in all three anatomical directions. Tri-axial swallowing accelerometry signals were concurrently collected from 72 dysphagic patients undergoing videofluoroscopic evaluation of swallowing (mean age: 63.94 ± 12.58 years period). Participants swallowed one or more thickened liquids with different consistencies including thin-thick liquids, nectar-thick liquids, and pudding-thick liquids with either a comfortable self-selected volume from a cup or a controlled volume by the examiner from a 5-ml spoon. Swallows were grouped based on the viscosity of swallows and the participant's stroke history. Then, a comprehensive set of features was extracted in multiple signal domains from 881 swallows. The results highlighted inter-axis dissimilarities among tri-axial swallowing vibrations including the extent of variability in the amplitude of signals, the degree of predictability of signals, and the extent of disordered behavior of signals in time-frequency domain. First, the upward movement of the hyolaryngeal structure, representing the S-I signals, were actually more variable in amplitude and showed less predictable behavior than the sideways and forward movements, representing the A-P and M-L signals, during swallowing. Second, the S-I signals, which represent the upward movement of the hyolaryngeal structure, behaved more disordered in the time-frequency domain than the sideways movement, M-L signals, in all groups of study except for the pudding swallows in the stroke group. Third, considering the viscosity and the participant's pathology, thin liquid swallows in the nonstroke group presented the most directional differences among all groups of study. In summary, despite some directional dissimilarities, M-L axis accelerometry characteristics are similar to those of the two other axes. This indicates that M-L axis characteristics, which cannot be observed in videofluoroscopic images, can be adequately derived from the A-P and S-I axes.
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Sejdić E, Movahedi F, Zhang Z, Kurosu A, Coyle JL. The effects of compressive sensing on extracted features from tri-axial swallowing accelerometry signals. PROCEEDINGS OF SPIE--THE INTERNATIONAL SOCIETY FOR OPTICAL ENGINEERING 2016; 9857. [PMID: 27695157 DOI: 10.1117/12.2225466] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/14/2022]
Abstract
Acquiring swallowing accelerometry signals using a comprehensive sensing scheme may be a desirable approach for monitoring swallowing safety for longer periods of time. However, it needs to be insured that signal characteristics can be recovered accurately from compressed samples. In this paper, we considered this issue by examining the effects of the number of acquired compressed samples on the calculated swallowing accelerometry signal features. We used tri-axial swallowing accelerometry signals acquired from seventeen stroke patients (106 swallows in total). From acquired signals, we extracted typically considered signal features from time, frequency and time-frequency domains. Next, we compared these features from the original signals (sampled using traditional sampling schemes) and compressively sampled signals. Our results have shown we can obtain accurate estimates of signal features even by using only a third of original samples.
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Affiliation(s)
- Ervin Sejdić
- Department of Electrical and Computer Engineering, Swanson School of Engineering, University of Pittsburgh, Pittsburgh, PA, 15261, USA
| | - Faezeh Movahedi
- Department of Electrical and Computer Engineering, Swanson School of Engineering, University of Pittsburgh, Pittsburgh, PA, 15261, USA
| | - Zhenwei Zhang
- Department of Electrical and Computer Engineering, Swanson School of Engineering, University of Pittsburgh, Pittsburgh, PA, 15261, USA
| | - Atsuko Kurosu
- Department of Communication Science and Disorders, School of Health and Rehabilitation Sciences, University of Pittsburgh, PA, 15260, USA
| | - James L Coyle
- Department of Communication Science and Disorders, School of Health and Rehabilitation Sciences, University of Pittsburgh, PA, 15260, USA
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Dudik JM, Coyle JL, El-Jaroudi A, Sun M, Sejdić E. A Matched Dual-Tree Wavelet Denoising for Tri-Axial Swallowing Vibrations. Biomed Signal Process Control 2016; 27:112-121. [PMID: 27152118 DOI: 10.1016/j.bspc.2016.01.012] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/22/2022]
Abstract
Swallowing disorders affect thousands of patients every year. Currently utilized techniques to screen for this condition are questionably reliable and are often deployed in non-standard manners, so efforts have been put forth to generate an instrumental alternative based on cervical auscultation. These physiological signals with low signal-to-noise ratios are traditionally denoised by well-known wavelets in a discrete, single tree wavelet decomposition. We attempt to improve this widely accepted method by designing a matched wavelet for cervical auscultation signals to provide better denoising capabilities and by implementing a dual-tree complex wavelet transform to maintain time invariant properties of this filtering. We found that our matched wavelet did offer better denoising capabilities for cervical auscultation signals compared to several popular wavelets and that the dual tree complex wavelet transform did offer better time invariance when compared to the single tree structure. We conclude that this new method of denoising cervical auscultation signals could benefit applications that can spare the required computation time and complexity.
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Affiliation(s)
- Joshua M Dudik
- Department of Electrical and Computer Engineering, Swanson School of Enginering, University of Pittsburgh, Pittsburgh, PA, USA.
| | - James L Coyle
- Department of Communication Science and Disorders, School of Health and Rehabilitation Sciences, University of Pittsburgh, Pittsburgh, PA, USA.
| | - Amro El-Jaroudi
- Department of Electrical and Computer Engineering, Swanson School of Enginering, University of Pittsburgh, Pittsburgh, PA, USA,
| | - Mingui Sun
- Department of Neurological Surgery, School of Medicine, University of Pittsburgh, Pittsburgh, PA, USA.
| | - Ervin Sejdić
- Department of Electrical and Computer Engineering, Swanson School of Enginering, University of Pittsburgh, Pittsburgh, PA, USA,
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Kappelle WFW, Siersema PD, Bogte A, Vleggaar FP. Challenges in oral drug delivery in patients with esophageal dysphagia. Expert Opin Drug Deliv 2016; 13:645-58. [DOI: 10.1517/17425247.2016.1142971] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/06/2023]
Affiliation(s)
- Wouter F. W. Kappelle
- University Medical Center Utrecht, Department of Gastroenterology and Hepatology, Utrecht, The Netherlands
| | - Peter D. Siersema
- University Medical Center Utrecht, Department of Gastroenterology and Hepatology, Utrecht, The Netherlands
| | - Auke Bogte
- University Medical Center Utrecht, Department of Gastroenterology and Hepatology, Utrecht, The Netherlands
| | - Frank P. Vleggaar
- University Medical Center Utrecht, Department of Gastroenterology and Hepatology, Utrecht, The Netherlands
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Dudik JM, Kurosu A, Coyle JL, Sejdić E. A statistical analysis of cervical auscultation signals from adults with unsafe airway protection. J Neuroeng Rehabil 2016; 13:7. [PMID: 26801236 PMCID: PMC4722771 DOI: 10.1186/s12984-015-0110-9] [Citation(s) in RCA: 21] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/22/2015] [Accepted: 12/19/2015] [Indexed: 01/16/2023] Open
Abstract
Background Aspiration, where food or liquid is allowed to enter the larynx during a swallow, is recognized as the most clinically salient feature of oropharyngeal dysphagia. This event can lead to short-term harm via airway obstruction or more long-term effects such as pneumonia. In order to non-invasively identify this event using high resolution cervical auscultation there is a need to characterize cervical auscultation signals from subjects with dysphagia who aspirate. Methods In this study, we collected swallowing sound and vibration data from 76 adults (50 men, 26 women, mean age 62) who underwent a routine videofluoroscopy swallowing examination. The analysis was limited to swallows of liquid with either thin (<5 cps) or viscous (≈300 cps) consistency and was divided into those with deep laryngeal penetration or aspiration (unsafe airway protection), and those with either shallow or no laryngeal penetration (safe airway protection), using a standardized scale. After calculating a selection of time, frequency, and time-frequency features for each swallow, the safe and unsafe categories were compared using Wilcoxon rank-sum statistical tests. Results Our analysis found that few of our chosen features varied in magnitude between safe and unsafe swallows with thin swallows demonstrating no statistical variation. We also supported our past findings with regard to the effects of sex and the presence or absence of stroke on cervical ausculation signals, but noticed certain discrepancies with regards to bolus viscosity. Conclusions Overall, our results support the necessity of using multiple statistical features concurrently to identify laryngeal penetration of swallowed boluses in future work with high resolution cervical auscultation.
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Affiliation(s)
- Joshua M Dudik
- Department of Electrical and Computer Engineering, Swanson School of Engineering, University of Pittsburgh, 3700 O'Hara Street, Pittsburgh, PA, 15261, USA.
| | - Atsuko Kurosu
- Department of Communication Science and Disorders, School of Health and Rehabilitation Sciences, University of Pittsburgh, 4028 Forbes Tower, Pittsburgh, PA, 15260, USA.
| | - James L Coyle
- Department of Communication Science and Disorders, School of Health and Rehabilitation Sciences, University of Pittsburgh, 4028 Forbes Tower, Pittsburgh, PA, 15260, USA.
| | - Ervin Sejdić
- Department of Electrical and Computer Engineering, Swanson School of Engineering, University of Pittsburgh, 3700 O'Hara Street, Pittsburgh, PA, 15261, USA.
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