Estimation of left ventricular function using a novel acoustic‐based device

Radzievsky, Naira; Papyan, Surik; Kushnir, Igal; Gat, Merav; Kushnir, Alon; Sagie, Alex; Agmon, Yoram

doi:10.1111/j.1365-2362.2011.02596.x

Cited by 5 publications

(3 citation statements)

References 22 publications

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“…Another group tested EF estimation with a novel acoustic-based device (vibration response imaging) that detects low-frequency acoustic signals (10 Hz-70 Hz). The device found sensitivity and specificity around 80%, but the protocol examined requires 36 microphones and a simultaneous ECG [ 14 ]. A study using acoustic cardiography in cohorts with and without atrial fibrillation found systolic dysfunction with moderate sensitivity and high specificity (Audicor; Inovise Medical, Inc) [ 37 ].…”

Section: Discussionmentioning

confidence: 99%

Accurate Modeling of Ejection Fraction and Stroke Volume With Mobile Phone Auscultation: Prospective Case-Control Study

Huecker,

Schutzman,

French

et al. 2024

JMIR Cardio

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Background Heart failure (HF) contributes greatly to morbidity, mortality, and health care costs worldwide. Hospital readmission rates are tracked closely and determine federal reimbursement dollars. No current modality or technology allows for accurate measurement of relevant HF parameters in ambulatory, rural, or underserved settings. This limits the use of telehealth to diagnose or monitor HF in ambulatory patients. Objective This study describes a novel HF diagnostic technology using audio recordings from a standard mobile phone. Methods This prospective study of acoustic microphone recordings enrolled convenience samples of patients from 2 different clinical sites in 2 separate areas of the United States. Recordings were obtained at the aortic (second intercostal) site with the patient sitting upright. The team used recordings to create predictive algorithms using physics-based (not neural networks) models. The analysis matched mobile phone acoustic data to ejection fraction (EF) and stroke volume (SV) as evaluated by echocardiograms. Using the physics-based approach to determine features eliminates the need for neural networks and overfitting strategies entirely, potentially offering advantages in data efficiency, model stability, regulatory visibility, and physical insightfulness. Results Recordings were obtained from 113 participants. No recordings were excluded due to background noise or for any other reason. Participants had diverse racial backgrounds and body surface areas. Reliable echocardiogram data were available for EF from 113 patients and for SV from 65 patients. The mean age of the EF cohort was 66.3 (SD 13.3) years, with female patients comprising 38.3% (43/113) of the group. Using an EF cutoff of ≤40% versus >40%, the model (using 4 features) had an area under the receiver operating curve (AUROC) of 0.955, sensitivity of 0.952, specificity of 0.958, and accuracy of 0.956. The mean age of the SV cohort was 65.5 (SD 12.7) years, with female patients comprising 34% (38/65) of the group. Using a clinically relevant SV cutoff of <50 mL versus >50 mL, the model (using 3 features) had an AUROC of 0.922, sensitivity of 1.000, specificity of 0.844, and accuracy of 0.923. Acoustics frequencies associated with SV were observed to be higher than those associated with EF and, therefore, were less likely to pass through the tissue without distortion. Conclusions This work describes the use of mobile phone auscultation recordings obtained with unaltered cellular microphones. The analysis reproduced the estimates of EF and SV with impressive accuracy. This technology will be further developed into a mobile app that could bring screening and monitoring of HF to several clinical settings, such as home or telehealth, rural, remote, and underserved areas across the globe. This would bring high-quality diagnostic methods to patients with HF using equipment they already own and in situations where no other diagnostic and monitoring options exist.

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Section: Discussionmentioning

confidence: 99%

Accurate Modeling of Ejection Fraction and Stroke Volume With Mobile Phone Auscultation: Prospective Case-Control Study

Huecker,

Schutzman,

French

et al. 2024

JMIR Cardio

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“…On the other side, it has demonstrated superior performances in clinical classification tasks compared to its single-channel counterpart. The multi-channel recording was successfully used to classify subjects with coronary artery disease from normal subjects [24][25][26], to identify and classify cardiac murmurs [27,28], and to estimate the Left Ventricular Ejection Fraction [29]. In the context of CTIs, Paiva et al employed a two-channel approach to improve the accuracy of their Pre-Ejection Period estimation by selecting the best channel based on a feature related to signal contrast [30].…”

Section: State Of the Artmentioning

confidence: 99%

A Wearable Multi-Sensor Array Enables the Recording of Heart Sounds in Homecare

Giordano

Rosati

Balestra

et al. 2023

Sensors

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The home monitoring of patients affected by chronic heart failure (CHF) is of key importance in preventing acute episodes. Nevertheless, no wearable technological solution exists to date. A possibility could be offered by Cardiac Time Intervals extracted from simultaneous recordings of electrocardiographic (ECG) and phonocardiographic (PCG) signals. Nevertheless, the recording of a good-quality PCG signal requires accurate positioning of the stethoscope over the chest, which is unfeasible for a naïve user as the patient. In this work, we propose a solution based on multi-source PCG. We designed a flexible multi-sensor array to enable the recording of heart sounds by inexperienced users. The multi-sensor array is based on a flexible Printed Circuit Board mounting 48 microphones with a high spatial resolution, three electrodes to record an ECG and a Magneto-Inertial Measurement Unit. We validated the usability over a sample population of 42 inexperienced volunteers and found that all subjects could record signals of good to excellent quality. Moreover, we found that the multi-sensor array is suitable for use on a wide population of at-risk patients regardless of their body characteristics. Based on the promising findings of this study, we believe that the described device could enable the home monitoring of CHF patients soon.

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“…These recordings are converted to digital signals, filtered between 150 and 200 Hz (to minimize artefact such as heart sounds) and finally represented by a series of greyscale images; each representing 0.17 seconds of recording [9,12]. Due to its ability to visually display lung sounds and provide quantitative data, VRI has sparked a great deal of interest in a wide range of clinical and research settings, relating to respiratory care and respiratory medicine [9,13-17]. …”

Section: Introductionmentioning

confidence: 99%

Vibration response imaging: protocol for a systematic review

2013

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BackgroundThe concept of lung sounds conveying information regarding lung physiology has been used extensively in clinical practice, particularly with physical auscultation using a stethoscope. Advances in computer technology have facilitated the construction of dynamic visual images derived from recorded lung sounds. Arguably, the most significant progress in this field was the development of the commercially available vibration response imaging (VRI) (Deep Breeze Ltd, Or-Akiva, Israel). This device provides a non-invasive, dynamic image of both lungs constructed from sounds detected from the lungs using surface sensors. In the literature, VRI has been utilized in a multitude of clinical and research settings. This systematic review aims to address three study questions relating to whether VRI can be used as an evaluative device, whether the images generated can be characterized, and which tools and measures have been used to assess these images.Methods/DesignThis systematic review will involve implementing search strategies in five online journal databases in order to extract articles relating to the application of VRI. Appropriate articles will be identified against a set of pre-determined eligibility criteria and assessed for methodological quality using a standardized scale. Included articles will have data extracted by the reviewers using a standardized evidence table. A narrative synthesis based on a standardized framework will be conducted, clustering evidence into three main groups; one for each of the study questions. A meta-analysis will be conducted if two or more research articles meet pre-determined criteria that allow quantitative synthesis to take place.DiscussionThis systematic review aims to provide a complete overview of the scope of VRI in the clinical and research settings, as well as to discuss methods to interpret the data obtained from VRI. The systematic review intends to help clinicians to make informed decisions on the clinical applicability of the device, to allow researchers to identify further potential avenues of investigation, and to provide methods for the evaluation and interpretation of dynamic and static images. The publication and registration of this review with PROSPERO provides transparency and accountability, and facilitates the appraisal of the proposed systematic review against the original design.Trial registrationPROSPERO registration number: CRD42013003751

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Estimation of left ventricular function using a novel acoustic‐based device

Abstract: LVEF can be estimated using a novel acoustic-based device. This device may assist in triage of patients according to LVEF prior to definitive assessment of LVEF by echocardiography.

Cited by 5 publications

References 22 publications

Accurate Modeling of Ejection Fraction and Stroke Volume With Mobile Phone Auscultation: Prospective Case-Control Study

Accurate Modeling of Ejection Fraction and Stroke Volume With Mobile Phone Auscultation: Prospective Case-Control Study

A Wearable Multi-Sensor Array Enables the Recording of Heart Sounds in Homecare

Vibration response imaging: protocol for a systematic review

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