Detection of Swallow Kinematic Events From Acoustic High-Resolution Cervical Auscultation Signals in Patients With Stroke.

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.

Dysphagia and its effects on swallowing sounds and vibrations in adults.

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.

Deep Learning for Classification of Normal Swallows in Adults.

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.

A statistical analysis of cervical auscultation signals from adults with unsafe airway protection.

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.

A comparative analysis of swallowing accelerometry and sounds during saliva swallows.

BACKGROUND: Accelerometry (the measurement of vibrations) and auscultation (the measurement of sounds) are both non-invasive techniques that have been explored for their potential to detect abnormalities in swallowing. The differences between these techniques and the information they capture about swallowing have not previously been explored in a direct comparison. METHODS: In this study, we investigated the differences between dual-axis swallowing accelerometry and swallowing sounds by recording data from adult participants and calculating a number of time and frequency domain features. During the experiment, 55 participants (ages 18-65) were asked to complete five saliva swallows in a neutral head position. The resulting data was processed using previously designed techniques including wavelet denoising, spline filtering, and fuzzy means segmentation. The pre-processed signals were then used to calculate 9 time, frequency, and time-frequency domain features for each independent signal. Wilcoxon signed-rank and Wilcoxon rank-sum tests were utilized to compare feature values across transducers and patient demographics, respectively. RESULTS: In addition to finding a number of features that varied between male and female participants, our statistical analysis determined that the majority of our chosen features were statistically significantly different across the two sensor methods and that the dependence on within-subject factors varied with the transducer type. However, a regression analysis showed that age accounted for an insignificant amount of variation in our signals. CONCLUSIONS: We conclude that swallowing accelerometry and swallowing sounds provide different information about deglutition despite utilizing similar transduction methods. This contradicts past assumptions in the field and necessitates the development of separate analysis and processing techniques for swallowing sounds and vibrations.

The effects of increased fluid viscosity on swallowing sounds in healthy adults.

BACKGROUND: Cervical auscultation (CA) is an affordable, non-invasive technique used to observe sounds occurring during swallowing. CA involves swallowing characterization via stethoscopes or microphones, while accelerometers can detect other vibratory signals. While the effects of fluid viscosity on swallowing accelerometry signals is well understood, there are still open questions about these effects on swallowing sounds. Therefore, this study investigated the influence of fluids with increasing thickness on swallowing sound characteristics. METHOD: We collected swallowing sounds and swallowing accelerometry signals from 56 healthy participants. Each participant completed five water swallows, five swallows of nectar-thick apple juice, and five swallows of honey-thick apple juice. These swallows were completed in neutral head and chin-tuck head positions. After pre-processing of collected signals, a number of features in time, frequency and time-frequency domains were extracted. RESULTS: Our numerical analysis demonstrated that significant influence of viscosity was found in most of the features. In general, features extracted from swallows in the neutral head position were affected more than swallows from the chin-tuck position. Furthermore, most of the differences were found between water and fluids with higher viscosity. Almost no significant differences were found between swallows involving nectar-thick and honey-thick apple juices. Our results also showed that thicker fluids had higher acoustic regularity and predictability as demonstrated by the information-theoretic features, and a lower frequency content as demonstrated by features in the frequency domain. CONCLUSIONS: According to these results, we can conclude that viscosity of fluids should be considered in future investigations involving swallowing sounds.

A Matched Dual-Tree Wavelet Denoising for Tri-Axial Swallowing Vibrations.

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.

Dysphagia Screening: Contributions of Cervical Auscultation Signals and Modern Signal-Processing Techniques.

Cervical auscultation is the recording of sounds and vibrations caused by the human body from the throat during swallowing. While traditionally done by a trained clinician with a stethoscope, much work has been put towards developing more sensitive and clinically useful methods to characterize the data obtained with this technique. The eventual goal of the field is to improve the effectiveness of screening algorithms designed to predict the risk that swallowing disorders pose to individual patients' health and safety. This paper provides an overview of these signal processing techniques and summarizes recent advances made with digital transducers in hopes of organizing the highly varied research on cervical auscultation. It investigates where on the body these transducers are placed in order to record a signal as well as the collection of analog and digital filtering techniques used to further improve the signal quality. It also presents the wide array of methods and features used to characterize these signals, ranging from simply counting the number of swallows that occur over a period of time to calculating various descriptive features in the time, frequency, and phase space domains. Finally, this paper presents the algorithms that have been used to classify this data into 'normal' and 'abnormal' categories. Both linear as well as non-linear techniques are presented in this regard.

A comparative analysis of DBSCAN, K-means, and quadratic variation algorithms for automatic identification of swallows from swallowing accelerometry signals.

BACKGROUND: Cervical auscultation with high resolution sensors is currently under consideration as a method of automatically screening for specific swallowing abnormalities. To be clinically useful without human involvement, any devices based on cervical auscultation should be able to detect specified swallowing events in an automatic manner. METHODS: In this paper, we comparatively analyze the density-based spatial clustering of applications with noise algorithm (DBSCAN), a k-means based algorithm, and an algorithm based on quadratic variation as methods of differentiating periods of swallowing activity from periods of time without swallows. These algorithms utilized swallowing vibration data exclusively and compared the results to a gold standard measure of swallowing duration. Data was collected from 23 subjects that were actively suffering from swallowing difficulties. RESULTS: Comparing the performance of the DBSCAN algorithm with a proven segmentation algorithm that utilizes k-means clustering demonstrated that the DBSCAN algorithm had a higher sensitivity and correctly segmented more swallows. Comparing its performance with a threshold-based algorithm that utilized the quadratic variation of the signal showed that the DBSCAN algorithm offered no direct increase in performance. However, it offered several other benefits including a faster run time and more consistent performance between patients. All algorithms showed noticeable differentiation from the endpoints provided by a videofluoroscopy examination as well as reduced sensitivity. CONCLUSIONS: In summary, we showed that the DBSCAN algorithm is a viable method for detecting the occurrence of a swallowing event using cervical auscultation signals, but significant work must be done to improve its performance before it can be implemented in an unsupervised manner.

Characteristics of Dry Chin-Tuck Swallowing Vibrations and Sounds.

OBJECTIVE: The effects of the chin-tuck maneuver, a technique commonly employed to compensate for dysphagia, on cervical auscultation are not fully understood. Characterizing a technique that is known to affect swallowing function is an important step on the way to developing a new instrumentation-based swallowing screening tool. METHODS: In this study, we recorded data from 55 adult participants who each completed five saliva swallows in a chin-tuck position. The resulting data were processed using previously designed filtering and segmentation algorithms. We then calculated nine time-, frequency-, and time-frequency-domain features for each independent signal. RESULTS: We found that multiple frequency- and time-domain features varied significantly between male and female subjects as well as between swallowing sounds and vibrations. However, our analysis showed that participant age did not play a significant role on the values of the extracted features. Finally, we found that various frequency features corresponding to swallowing vibrations did demonstrate statistically significant variation between the neutral and chin-tuck positions but sounds showed no changes between these two positions. CONCLUSION: The chin-tuck maneuver affects many facets of swallowing vibrations and sounds and its effects can be monitored via cervical auscultation. SIGNIFICANCE: These results suggest that a subject's swallowing technique does need to be accounted for when monitoring their performance with cervical auscultation-based instrumentation.

Understanding differences between healthy swallows and penetration-aspiration swallows via compressive sensing of tri-axial swallowing accelerometry signals.

Swallowing accelerometry is a promising tool for non-invasive assessment of swallowing difficulties. A recent contribution showed that swallowing accelerometry signals for healthy swallows and swallows indicating laryngeal penetration or tracheal aspiration have different time-frequency structures, which may be problematic for compressive sensing schemes based on time-frequency dictionaries. In this paper, we examined the effects of different swallows on the accuracy of a compressive sensing scheme based on modulated discrete prolate spheroidal sequences. We utilized tri-axial swallowing accelerometry signals recorded from four patients during routinely schedule videofluoroscopy exams. In particular, we considered 77 swallows approximately equally distributed between healthy swallows and swallows presenting with some penetration/aspiration. Our results indicated that the swallow type does not affect the accuracy of a considered compressive sensing scheme. Also, the results confirmed previous findings that each individual axis contributes different information. Our findings are important for further developments of a device which is to be used for long-term monitoring of swallowing difficulties.