Document Type

Article

Publication Date

2013

DOI

10.1177/0037549713497278

Publication Title

Simulation: Transactions of the Society for Modeling and Simulation International

Volume

89

Issue

12

Pages

1450-1458

Abstract

Auscultation, the act of listening to the heart and lung sounds, can reveal substantial information about patients’ health and other cardiac-related problems; therefore, competent training can be a key for accurate and reliable diagnosis. Standardized patients (SPs), who are healthy individuals trained to portray real patients, have been extensively used for such training and other medical teaching techniques; however, the range of symptoms and conditions they can simulate remains limited since they are only patient actors. In this work, we describe a novel tracking method for placing virtual symptoms in correct auscultation areas based on recorded ECG signals with various stethoscope diaphragm orientations; this augmented reality simulation would extend the capabilities of SPs and allow medical trainees to hear abnormal heart and lung sounds in a normal SP. ECG signals recorded from two different SPs over a wide range of stethoscope diaphragm orientations were processed and analyzed to accurately distinguish four different heart auscultation areas, aortic, mitral, pulmonic and tricuspid, for any stethoscope’s orientation. After processing the signals and extracting relevant features, different classifiers were applied for assessment of the proposed method; 95.1% and 87.1% accuracy were obtained for SP1 and SP2, respectively. The proposed system provides an efficient, non-invasive, and cost efficient method for training medical practitioners on heart auscultation.

Comments

Web of Science: "Free full-text from publisher."

Original Publication Citation

Kidane, N., Chemlal, S., Li, J., McKenzie, F. D., & Hubbard, T. (2013). Orientation invariant ecg-based stethoscope tracking for heart auscultation training on augmented standardized patients. Simulation: Transactions of the Society for Modeling and Simulation International, 89(12), 1450-1458. doi:10.1177/0037549713497278

ORCID

0000-0002-0160-5605 (McKenzie)

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