Diagnosis of Coexisting Valvular Heart Diseases Using Image-to-Sequence Translation of Contact Microphone Recordings

Arash Shokouhmand, Haoran Wen, Samiha Khan, Joseph A. Puma, Amisha Patel, Philip Green, Farrokh Ayazi, Negar Ebadi

Research output: Contribution to journalArticlepeer-review

1 Scopus citations

Abstract

Objective: Development of a contact microphone-driven screening framework for the diagnosis of coexisting valvular heart diseases (VHDs). Methods: A sensitive accelerometer contact microphone (ACM) is employed to capture heart-induced acoustic components on the chest wall. Inspired by the human auditory system, ACM recordings are initially transformed into Mel-frequency cepstral coefficients (MFCCs) and their first and second derivatives, resulting in 3-channel images. An image-to-sequence translation network based on the convolution-meets-transformer (CMT) architecture is then applied to each image to find local and global dependencies in images, and predict a 5-digit binary sequence, where each digit corresponds to the presence of a specific type of VHD. The performance of the proposed framework is evaluated on 58 VHD patients and 52 healthy individuals using a 10-fold leave-subject-out cross-validation (10-LSOCV) approach. Results: Statistical analyses suggest an average sensitivity, specificity, accuracy, positive predictive value, and F1 score of 93.28%, 98.07%, 96.87%, 92.97%, and 92.4% respectively, for the detection of coexisting VHDs. Furthermore, areas under the curve (AUC) of 0.99 and 0.98 are respectively reported for the validation and test sets. Conclusion: The high performances achieved prove that local and global features of ACM recordings effectively characterize heart murmurs associated with valvular abnormalities. Significance: Limited access of primary care physicians to echocardiography machines has resulted in a low sensitivity of 44% when using a stethoscope for the identification of heart murmurs. The proposed framework provides accurate decision-making on the presence of VHDs, thus reducing the number of undetected VHD patients in primary care settings.

Original languageEnglish
Pages (from-to)2540-2551
Number of pages12
JournalIEEE Transactions on Biomedical Engineering
Volume70
Issue number9
DOIs
StatePublished - 1 Sep 2023

Keywords

  • Accelerometer Contact Microphone (ACM)
  • Coexisting VHDs
  • Convolution-Meets-Transformer (CMT)
  • Valvular Heart Disease (VHD)

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