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Non-invasive Low-cost Cardiovascular Activity Monitoring

We harness the power of technology to revolutionize the way we monitor heart function and diagnose cardiovascular diseases. By measuring the vibrations generated by cardiac activities such as valve opening and closure, we are able to noninvasively gather critical diagnostic information. Our expertise in computational models, signal processing, and machine learning allows us to accurately characterize these signals, leading to the development of innovative cost-effective methods for monitoring and diagnosis of cardiovascular diseases. With a focus on precision and accuracy, our work has the potential to improve patient outcomes and change the future of healthcare, particularly within low-income populations and underserved areas.

AllSignal.png

---- Electrocardiography

to measure electrical

activity of heart

---- Stethoscope

to record heart sounds

---- Accelerometer

to measure cardiovascular-

induced vibrations

---- Respiration Belt

to record respiration rate

Objective

Develop cost-effective methods for monitoring and early diagnosis of cardiovascular diseases based on cardiovascular-induced vibrations measured noninvasively on the body surface

Amirtahà Taebi

Amirtahà Taebi

PI

Current members involved:

Sophia Ruckman
Jigar Bhatt
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Past members involved:

MicrosoftTeams-image (1)_edited_edited_edited.jpg
Jadyn Cook
Muneebah Umar

Skillsets

  • Human subject studies

  • Signal and image processing

  • Machine learning

  • Computational fluid dynamics and finite element modeling

  • Sensor array design

Sponsors

Selected Publications

Other Publications

Mann, A., Gamage, P.T., Kakavand, B., Taebi, A. (2024). Exploring the Impact of Sensor Location On Seismocardiography-Derived Cardiac Time Intervals. ASME J of Medical Diagnostics.
doi 10.1115/1.4063203

 

Ruckman, S., Bhatt, J., Cook, J., Gamage, P.T., Kakavand, B., Taebi, A. (2023). Design, Prototype, and Evaluation of a Low-Cost Multimodal Device for Cardiovascular Monitoring. ASME 2023 International Mechanical Engineering Conference and Exposition, V005T06A022. 
doi 10.1115/IMECE2023-112486

 

Mann, A., Kakavand, B., Gamage, P.T., Taebi, A. (2023). Effect of Measurement Location on Cardiac Time Intervals Estimated by Seismocardiography. ASME 2023 International Mechanical Engineering Conference and Exposition, V005T06A070. 
doi 10.1115/IMECE2023-112702

 

Mann, A., Cook, J., Umar, M., Khalili, F., Taebi, A. (2022). Heart Rate Monitoring Using Heart Acoustics. ASME 2022 International Mechanical Engineering Conference and Exposition, V004T05A069.
d
oi 10.1115/IMECE2022-96824

 

Khalili, F., Gamage, P.T., Taebi, A., Johnson, M.E., Roberts, R.B., Mitchell, J. (2021). Spectral decomposition of the flow and characterization of the sound signals generated through stenoses of different levels of severity. Bioengineering 8(3): 41.
doi 10.3390/bioengineering8030041

 

Khalili, F., Gamage, P.T., Taebi, A., Johnson, M.E., Roberts, R.B., Mitchell, J. (2021). Spectral decomposition and sound source localization of highly disturbed flow through a severe arterial stenosis, Bioengineering 8(3): 34.
doi 10.3390/bioengineering8030034

 

Taebi, A., Sandler, R.H., Kakavand, B., Mansy, H.A. (2019). Extraction of Peak Velocity Profiles from Doppler Echocardiography Using Image Processing. Bioengineering 6(3): 64.
doi 10.3390/bioengineering6030064
 GitHub 

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