Dataset Information

Measuring diaphragm movement and respiratory frequency using a novel ultrasound device in healthy volunteers.

ABSTRACT:

Purpose

To evaluate the ability of a novel ultrasound (US) device, DiaMon, to monitor diaphragm movement via its proxy liver movement, and compare it with the respired flow measured with a flowmeter, in awake and healthy volunteers. We wanted to (1) establish the optimal anatomical position for attaching the DiaMon device to the abdominal wall, and (2) evaluate the accuracy of continuous monitoring of respiratory frequency.

Methods

Thirty healthy subjects were recruited. The DiaMon probe was applied subcostally in four different positions with the subjects in five different postures. The subjects breathed tidal volumes into a spirometer for 30-60 s with the DiaMon recording simultaneously.

Results

The device detected a readable signal in 83-100% of the position/posture-combinations. The technical correlation between the two signals was highest in the anterior axillary-supine position (mean ± SD: 0.95 ± 0.03), followed by paramidline-supine (0.90 ± 0.09) and midclavicular-supine (0.89 ± 0.12). The frequency measurements yielded a mean difference of 0.03 (95% limits of agreement - 0.11, 0.16) breaths per minute in the anterior axillary-supine position.

Conclusion

The DiaMon device is able to detect liver movement in most subjects, and it measures breathing frequency accurately.

SUBMITTER: Sæverud HA

PROVIDER: S-EPMC7925735 | biostudies-literature | 2021 Mar

REPOSITORIES: biostudies-literature

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Publications

Measuring diaphragm movement and respiratory frequency using a novel ultrasound device in healthy volunteers.

Sæverud Håvard Andreassen HA Falk Ragnhild Sørum RS Dowrick Adam A Eriksen Morten M Aarrestad Sigurd S Skjønsberg Ole Henning OH

Journal of ultrasound 20191106 1

<h4>Purpose</h4>To evaluate the ability of a novel ultrasound (US) device, DiaMon, to monitor diaphragm movement via its proxy liver movement, and compare it with the respired flow measured with a flowmeter, in awake and healthy volunteers. We wanted to (1) establish the optimal anatomical position for attaching the DiaMon device to the abdominal wall, and (2) evaluate the accuracy of continuous monitoring of respiratory frequency.<h4>Methods</h4>Thirty healthy subjects were recruited. The DiaMo ...[more]

PMID: 31691921

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Project description:The Earable device is a behind-the-ear wearable originally developed to measure cognitive function. Since Earable measures electroencephalography (EEG), electromyography (EMG), and electrooculography (EOG), it may also have the potential to objectively quantify facial muscle and eye movement activities relevant in the assessment of neuromuscular disorders. As an initial step to developing a digital assessment in neuromuscular disorders, a pilot study was conducted to determine whether the Earable device could be utilized to objectively measure facial muscle and eye movements intended to be representative of Performance Outcome Assessments, (PerfOs) with tasks designed to model clinical PerfOs, referred to as mock-PerfO activities. The specific aims of this study were: To determine whether the Earable raw EMG, EOG, and EEG signals could be processed to extract features describing these waveforms; To determine Earable feature data quality, test re-test reliability, and statistical properties; To determine whether features derived from Earable could be used to determine the difference between various facial muscle and eye movement activities; and, To determine what features and feature types are important for mock-PerfO activity level classification. A total of N = 10 healthy volunteers participated in the study. Each study participant performed 16 mock-PerfOs activities, including talking, chewing, swallowing, eye closure, gazing in different directions, puffing cheeks, chewing an apple, and making various facial expressions. Each activity was repeated four times in the morning and four times at night. A total of 161 summary features were extracted from the EEG, EMG, and EOG bio-sensor data. Feature vectors were used as input to machine learning models to classify the mock-PerfO activities, and model performance was evaluated on a held-out test set. Additionally, a convolutional neural network (CNN) was used to classify low-level representations of the raw bio-sensor data for each task, and model performance was correspondingly evaluated and compared directly to feature classification performance. The model's prediction accuracy on the Earable device's classification ability was quantitatively assessed. Study results indicate that Earable can potentially quantify different aspects of facial and eye movements and may be used to differentiate mock-PerfO activities. Specially, Earable was found to differentiate talking, chewing, and swallowing tasks from other tasks with observed F1 scores >0.9. While EMG features contribute to classification accuracy for all tasks, EOG features are important for classifying gaze tasks. Finally, we found that analysis with summary features outperformed a CNN for activity classification. We believe Earable may be used to measure cranial muscle activity relevant for neuromuscular disorder assessment. Classification performance of mock-PerfO activities with summary features enables a strategy for detecting disease-specific signals relative to controls, as well as the monitoring of intra-subject treatment responses. Further testing is needed to evaluate the Earable device in clinical populations and clinical development settings.

Dataset Information

Measuring diaphragm movement and respiratory frequency using a novel ultrasound device in healthy volunteers.

Purpose

Methods

Results

Conclusion

Publications

Measuring diaphragm movement and respiratory frequency using a novel ultrasound device in healthy volunteers.

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