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Anwar A, Khalifa Y, Lucatorto E, Coyle JL, Sejdic E. Towards a comprehensive bedside swallow screening protocol using cross-domain transformation and high-resolution cervical auscultation. Artif Intell Med 2024; 154:102921. [PMID: 38991399 DOI: 10.1016/j.artmed.2024.102921] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/24/2024] [Revised: 06/17/2024] [Accepted: 06/20/2024] [Indexed: 07/13/2024]
Abstract
High-resolution cervical auscultation (HRCA) is an emerging noninvasive and accessible option to assess swallowing by relying upon accelerometry and sound sensors. HRCA has shown tremendous promise and accuracy in identifying and predicting swallowing physiology and biomechanics with accuracies equivalent to trained human judges. These insights have historically been available only through instrumental swallowing evaluation methods, such as videofluoroscopy and endoscopy. HRCA uses supervised learning techniques to interpret swallowing physiology from the acquired signals, which are collected during radiographic assessment of swallowing using barium contrast. Conversely, bedside swallowing screening is typically conducted in non-radiographic settings using only water. This poses a challenge to translating and generalizing HRCA algorithms to bedside screening due to the rheological differences between barium and water. To address this gap, we proposed a cross-domain transformation framework that uses cycle generative adversarial networks to convert HRCA signals of water swallows into a domain compatible with the barium swallows-trained HRCA algorithms. The proposed framework achieved a cross-domain transformation accuracy that surpassed 90%. The authenticity of the generated signals was confirmed using a binary classifier to confirm the framework's capability to produce indistinguishable signals. This framework was also assessed for retaining swallow physiological and biomechanical properties in the signals by applying an existing model from the literature that identifies the opening and closure of the upper esophageal sphincter. The outcomes of this model showed nearly identical results between the generated and original signals. These findings suggest that the proposed transformation framework is a feasible avenue to advance HCRA towards clinical deployment for water-based swallowing screenings.
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Affiliation(s)
- Ayman Anwar
- Edward S. Rogers Department of Electrical and Computer Engineering, University of Toronto, Toronto, ON, Canada.
| | - Yassin Khalifa
- Center for Research Computing, University of Pittsburgh, Pittsburgh, PA, USA; Information Technology Analytics, University of Pittsburgh, Pittsburgh, PA, USA; Systems and Biomedical Engineering, Cairo University, Giza, Egypt.
| | - Erin Lucatorto
- 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.
| | - Ervin Sejdic
- Edward S. Rogers Department of Electrical and Computer Engineering, University of Toronto, Toronto, ON, Canada; North York General Hospital, Toronto, ON, Canada.
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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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Khalifa Y, Mahoney AS, Lucatorto E, Coyle JL, Sejdić E. Non-Invasive Sensor-Based Estimation of Anterior-Posterior Upper Esophageal Sphincter Opening Maximal Distension. IEEE JOURNAL OF TRANSLATIONAL ENGINEERING IN HEALTH AND MEDICINE 2023; 11:182-190. [PMID: 36873304 PMCID: PMC9976940 DOI: 10.1109/jtehm.2023.3246919] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 07/25/2022] [Revised: 01/25/2023] [Accepted: 02/15/2023] [Indexed: 02/22/2023]
Abstract
OBJECTIVE Dysphagia management relies on the evaluation of the temporospatial kinematic events of swallowing performed in videofluoroscopy (VF) by trained clinicians. The upper esophageal sphincter (UES) opening distension represents one of the important kinematic events that contribute to healthy swallowing. Insufficient distension of UES opening can lead to an accumulation of pharyngeal residue and subsequent aspiration which in turn can lead to adverse outcomes such as pneumonia. VF is usually used for the temporal and spatial evaluation of the UES opening; however, VF is not available in all clinical settings and may be inappropriate or undesirable for some patients. High resolution cervical auscultation (HRCA) is a noninvasive technology that uses neck-attached sensors and machine learning to characterize swallowing physiology by analyzing the swallow-induced vibrations/sounds in the anterior neck region. We investigated the ability of HRCA to noninvasively estimate the maximal distension of anterior-posterior (A-P) UES opening as accurately as the measurements performed by human judges from VF images. METHODS AND PROCEDURES Trained judges performed the kinematic measurement of UES opening duration and A-P UES opening maximal distension on 434 swallows collected from 133 patients. We used a hybrid convolutional recurrent neural network supported by attention mechanisms which takes HRCA raw signals as input and estimates the value of the A-P UES opening maximal distension as output. RESULTS The proposed network estimated the A-P UES opening maximal distension with an absolute percentage error of 30% or less for more than 64.14% of the swallows in the dataset. CONCLUSION This study provides substantial evidence for the feasibility of using HRCA to estimate one of the key spatial kinematic measurements used for dysphagia characterization and management. Clinical and Translational Impact Statement: The findings in this study have a direct impact on dysphagia diagnosis and management through providing a non-invasive and cheap way to estimate one of the most important swallowing kinematics, the UES opening distension, that contributes to safe swallowing. This study, along with other studies that utilize HRCA for swallowing kinematic analysis, paves the way for developing a widely available and easy-to-use tool for dysphagia diagnosis and management.
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Affiliation(s)
- Yassin Khalifa
- Department of Biomedical EngineeringCairo UniversityGiza12613Egypt
- Department of Electrical and Computer EngineeringSwanson School of EngineeringUniversity of PittsburghPittsburghPA15260USA
- Case Western Reserve University School of MedicineClevelandOH44106USA
- University Hospitals Harrington Heart and Vascular InstituteClevelandOH44106USA
| | - Amanda S. Mahoney
- Department of Communication Science and DisordersUniversity of PittsburghPittsburghPA15260USA
| | - Erin Lucatorto
- Department of Communication Science and DisordersUniversity of PittsburghPittsburghPA15260USA
| | - James L. Coyle
- Department of Communication Science and DisordersUniversity of PittsburghPittsburghPA15260USA
- Department of OtolaryngologyUniversity of PittsburghPittsburghPA15260USA
| | - Ervin Sejdić
- The Edward S. Rogers Sr. Department of Electrical and Computer EngineeringFaculty of Applied Science and EngineeringUniversity of TorontoTorontoONM5S 1A1Canada
- North York General HospitalTorontoONM2K 1E1Canada
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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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Feng C, Volkman K, Wagoner C, Siu KC. Effects of different viscous liquids and solid foods on swallowing speeds and sounds among healthy adults. INTERNATIONAL JOURNAL OF LANGUAGE & COMMUNICATION DISORDERS 2022; 57:78-89. [PMID: 34637189 DOI: 10.1111/1460-6984.12675] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/21/2021] [Revised: 08/09/2021] [Accepted: 09/13/2021] [Indexed: 06/13/2023]
Abstract
BACKGROUND Digital cervical auscultation (CA) has been proposed since the 1950s for screening aspiration among patients with dysphagia. Researchers have investigated the 'external' effects such as bolus viscosity, volume, and head and neck positions. However, the influences of standardized liquid viscosity and food texture on swallowing sounds have not been fully understood due to lacking uniform standardization of bolus preparation. Furthermore, a paucity of the literature recommends proper viscous liquids and foods to start swallowing training or monitor the swallowing progress during the continuum of disease based on acoustic signals. AIMS To investigate the effects of eight-level liquids and foods on swallowing sound features based on the International Dysphagia Diet Standardisation Initiative (IDDSI). METHODS & PROCEDURES We collected swallowing sounds from 30 healthy participants ranging in age from 19 to 60 years and who were self-reporting no history of swallowing disorders. Each participant swallowed liquids and foods regarding different consistency or texture with their head-trunk in a neutral position. OUTCOMES & RESULTS Features of swallowing acoustic signals and the IDDSI flow test as well as food test confirmed the level 3 moderately thick (MO3) was more suitable to categorize into liquids and the level 4 extremely thick (EX4) was more corresponded to the properties of food bolus. We found significant differences in duration of acoustic signals across different liquids and foods except between swallowing level 0 thin liquid and level 1 slightly thick liquid, as well as EX4 and level 5 minced and moist. Our results also demonstrated liquid viscosity significantly impacted the peak intensity of swallowing sounds. CONCLUSIONS & IMPLICATIONS As an initial exploration of digital CA across eight levels of different liquids and foods according to the IDDSI, we established the baseline findings for future comparisons with other study populations or other various consistent liquids/foods. Although both MO3 and EX4 can be considered as liquid or food boluses with high thickness, MO3 might be suitable as the 'start liquid' for patients with dysphagia; however, the decision still needs to be confirmed by the healthcare provider based on patients' safety and the area of deficit. We also concluded there are influences of varied fluid consistency and food texture on swallowing sounds. Furthermore, future investigations should explore whether changing viscosity levels could either continuously or discretely disturb the swallowing acoustic signals. WHAT THIS PAPER ADDS What is already known on the subject Previous studies have found that the 'external' effects such as bolus viscosity, volume, and head and neck positions. Due to lacking uniform standardization of bolus preparation, there is limited information about the influences of standardized liquid viscosity and food texture on swallowing sounds. What this paper adds to the existing knowledge As an initial exploration, we utilized digital CA with a large sample of viscous liquids and different textures of foods based on the IDDSI to investigate the swallowing sounds. What are the potential or actual clinical implications of this work? This study confirms that the effects of various fluid consistency and food texture on swallowing acoustic signals. However, the findings of this study support the need for further research relating to changing viscosity could either continuously or discretely disturb the swallowing acoustic signals.
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Affiliation(s)
- Chun Feng
- The Center of Rehabilitation Therapy, The First Rehabilitation Hospital of Shanghai, Rehabilitation Hospital Affiliated to Tongji University, Shanghai, China
| | - Kathleen Volkman
- Department of Health and Rehabilitation Sciences, 984420 Nebraska Medical Center, Omaha, NE, USA
| | - Cheryl Wagoner
- Madonna Rehabilitation Hospital Lincoln Campus, Lincoln, NE, USA
| | - Ka-Chun Siu
- Department of Health and Rehabilitation Sciences, 984420 Nebraska Medical Center, Omaha, NE, USA
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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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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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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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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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Sabry A, Mahoney AS, Mao S, Khalifa Y, Sejdić E, Coyle JL. Automatic Estimation of Laryngeal Vestibule Closure Duration Using High- Resolution Cervical Auscultation Signals. PERSPECTIVES OF THE ASHA SPECIAL INTEREST GROUPS 2020; 5:1647-1656. [PMID: 35937555 PMCID: PMC9355454 DOI: 10.1044/2020_persp-20-00073] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/13/2023]
Abstract
Purpose Safe swallowing requires adequate protection of the airway to prevent swallowed materials from entering the trachea or lungs (i.e., aspiration). Laryngeal vestibule closure (LVC) is the first line of defense against swallowed materials entering the airway. Absent LVC or mistimed/ shortened closure duration can lead to aspiration, adverse medical consequences, and even death. LVC mechanisms can be judged commonly through the videofluoroscopic swallowing study; however, this type of instrumentation exposes patients to radiation and is not available or acceptable to all patients. There is growing interest in noninvasive methods to assess/monitor swallow physiology. In this study, we hypothesized that our noninvasive sensor- based system, which has been shown to accurately track hyoid displacement and upper esophageal sphincter opening duration during swallowing, could predict laryngeal vestibule status, including the onset of LVC and the onset of laryngeal vestibule reopening, in real time and estimate the closure duration with a comparable degree of accuracy as trained human raters. Method The sensor-based system used in this study is high-resolution cervical auscultation (HRCA). Advanced machine learning techniques enable HRCA signal analysis through feature extraction and complex algorithms. A deep learning model was developed with a data set of 588 swallows from 120 patients with suspected dysphagia and further tested on 45 swallows from 16 healthy participants. Results The new technique achieved an overall mean accuracy of 74.90% and 75.48% for the two data sets, respectively, in distinguishing LVC status. Closure duration ratios between automated and gold-standard human judgment of LVC duration were 1.13 for the patient data set and 0.93 for the healthy participant data set. Conclusions This study found that HRCA signal analysis using advanced machine learning techniques can effectively predict laryngeal vestibule status (closure or opening) and further estimate LVC duration. HRCA is potentially a noninvasive tool to estimate LVC duration for diagnostic and biofeedback purposes without X-ray imaging.
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Affiliation(s)
- Aliaa Sabry
- Department of Communication Science and Disorders, School of Health and Rehabilitation Sciences, University of Pittsburgh, PA
- Krembil Research Institute, University Health Network, Toronto, Ontario, Canada
| | - Amanda S. Mahoney
- Department of Communication Science and Disorders, School of Health and Rehabilitation Sciences, University of Pittsburgh, PA
| | - Shitong Mao
- Department of Electrical and Computer Engineering, Swanson School of Engineering, University of Pittsburgh, PA
| | - Yassin Khalifa
- Department of Electrical and Computer Engineering, Swanson School of Engineering, 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, School of Medicine 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
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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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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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Chen CT, Wang LY, Wang YL, Lin BS. Quantitative Real-Time Assessment for Feeding Skill of Preterm Infants. J Med Syst 2017; 41:95. [DOI: 10.1007/s10916-017-0744-1] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/21/2017] [Accepted: 04/27/2017] [Indexed: 10/19/2022]
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14
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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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