Identification of Location Specific Feature Points in a Cardiac Cycle Using a Novel Seismocardiogram Spectrum System
Abstract
Seismocardiogram (SCG) or mechanocardiography is a noninvasive cardiac diagnostic method; however, previous studies used only a single sensor to detect cardiac mechanical activities that will not be able to identify location-specific feature points in a cardiac cycle corresponding to the four valvular auscultation locations. In this study, a multichannel SCG spectrum measurement system was proposed and examined for cardiac activity monitoring to overcome problems like, position dependency, time delay, and signal attenuation, occurring in traditional single-channel SCG systems. ECG and multichannel SCG signals were simultaneously recorded in 25 healthy subjects. Cardiac echocardiography was conducted at the same time. SCG traces were analyzed and compared with echocardiographic images for feature point identification. Fifteen feature points were identified in the corresponding SCG traces. Among them, six feature points, including left ventricular lateral wall contraction peak velocity, septal wall contraction peak velocity, transaortic peak flow, transpulmonary peak flow, transmitral ventricular relaxation flow, and transmitral atrial contraction flow were identified. These new feature points were not observed in previous studies because the single-channel SCG could not detect the location-specific signals from other locations due to time delay and signal attenuation. As the results, the multichannel SCG spectrum measurement system can record the corresponding cardiac mechanical activities with location-specific SCG signals and six new feature points were identified with the system. This new modality may help clinical diagnoses of valvular heart diseases and heart failure in the future.
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Effect of Sternal Sensor Location on Seismocardiography for Severe Aortic Stenosis Detection
Elnaggar, I., Pykäri, J., Vasankari, T., Anzanpour, A., Kaisti, M., Airola, A., Savontaus, M., & Koivisto, T. (2026) · IEEE Sensors Letters · doi:10.1109/lsens.2026.3726755
- Authors
- Lin, W.-Y., Tsai, T.-H., Lee, M.-Y., Chou, W.-C., Chang, P.-C., Chou, C.-C., Wen, M.-S., Ho, M.-Y., Lee, W.-C., Hsieh, M.-J., & Lin, C.-C.
- Affiliations
- Chang Gung University (TW)
- Chang Gung Memorial Hospital (TW)
- ORCID
- Venue
- IEEE Journal of Biomedical and Health Informatics
- Published
- 2018-03
- Volume
- 22
- Issue
- 2
- Pages
- 442-449
- ISSN
- 2168-2194 (ISSN-L)
- 2168-2208
- OpenAlex
- W2533378859
- Cited by
- 62
- References
- 22
- Citations by year
- 2026: 5 · 2025: 4 · 2024: 6 · 2023: 5 · 2022: 10 · 2021: 4 · 2020: 8 · 2019: 8 · 2018: 7 · 2017: 4 · 2016: 1
- FWCI
- 5.98
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- IEEE Journal of Biomedical and Health Informatics (publishedVersion)
- PubMed (publishedVersion)
- Funders
- Ministry of Science and Technology, Taiwan (MOST 104-2627-E-182-001, MOST104-2754-8-182-001, MOST 103-2221-E-182-003, MOST 104-2221-E-182-013)
- CGU (BMRPC50, BMRP138)
- Topics
- Health Sciences › Medicine › Pulmonary and Respiratory Medicine › Phonocardiography and Auscultation Techniques
- Physical Sciences › Engineering › Biomedical Engineering › Non-Invasive Vital Sign Monitoring
- Health Sciences › Medicine › Cardiology and Cardiovascular Medicine › ECG Monitoring and Analysis
- Keywords
- seismocardiogram, mechanocardiography, cardiac mechanics, transmitral flow, heart failure diagnosis, valvular heart disease
- MeSH terms
- Adult, Female, Heart, Heart Failure, Heart Function Tests, Humans, Male, Signal Processing, Computer-Assisted, Young Adult, Accelerometry
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