Dr. Mostafa Haghi Profile

Dr. Mostafa Haghi

at Peter L. Reichertz Institut fuer Medizinische Informatik

SPIE Involvement:

Author

Publications (1)

This will count as one of your downloads.

You will have access to both the presentation and article (if available).

DOWNLOAD NOW

This content is available for download via your institution's subscription. To access this item, please sign in to your personal account.

Email or Username Forgot your username?

Password Forgot your password?

Show

Keep me signed in

No SPIE account? Create an account

Proceedings Article | 10 April 2023 Presentation + Paper

Reliability estimation of armchair-based capacitive ECG using video-based pose estimation

Satyam Srivastava, Arman Ershadi, Mostafa Haghi, Thomas Deserno

Proceedings Volume 12469, 124690E (2023) https://doi.org/10.1117/12.2654327

KEYWORDS: Windows, Electrocardiography, Pose estimation, Reliability, Neural networks, Chemical vapor deposition, Electrodes, Data modeling, Sensors, Heart

Read Abstract +

Background: Annually and globally, cardiovascular diseases yield the death of 17.9 million people. Continuous and unobtrusive monitoring of vital signs supports an early detection of abnormalities and diseases, such as atrial fibrillation. Here, we analyze capacitive electrocardiography (cECG) recorded in an armchair at home. However, processing such data is challenging, as body movements and other artifacts disturb the signal quality. Methods: In this paper, we suggest video-based pose estimation to assess the reliability of cEGC. In 20 subjects, we measured reference and capacitive ECG synchronized with a video recording for key-point-based movement analysis with the OpenPifPaf pose estimation algorithm. We considered all 17 human body joints to compute a movement index and label all data in windows of 5 s as reliable vs. unreliable, according to that index. Then, we compared the heart rates obtained from complete and reliable cEGC windows with the corresponding windows from the reference ground truth ECG. Result: The left and right hip joints are most significantly influencing the signal’s quality. In addition, the joints’ movement distance from the original position limited to the range 460.84 pixels and 382.22 pixels, respectively, deliver a reliable cECG signal. Conclusion: Video-based pose estimation delivers reliable and unreliable periods of cECG recordings and improves continuous health monitoring at home.

My Library

You currently do not have any folders to save your paper to! Create a new folder below.

Folder Name

Folder Description

View contact details

UPDATE YOUR PROFILE

Is this your profile? Update it now.

Sign into your SPIE.org account

Don’t have a profile and want one?

Create an account on SPIE.org

Access to the requested content is limited to institutions that have purchased or subscribe to SPIE eBooks. You are receiving this notice because your organization may not have SPIE eBooks access.*

*Shibboleth/Open Athens users─please sign in to access your institution's subscriptions.

To obtain this item, you may purchase the complete book in print or electronic format on SPIE.org.

ORGANIZATIONAL
Sign in with credentials provided by your organization.

Organizational Username

Organizational Password

Show/Hide Password

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available

Members:

Non-members: ADD TO CART

Keywords/Phrases

Search In:

Publication Years