
Beamforming LDV-data for carotid-femoral pulse-wave velocity estimation
- Author
- Simeon Beeckman (UGent) , Yanlu Li, Soren Aasmul, Rosa-Maria Bruno, Pierre Boutouyrie, Nilesh Madhu (UGent) and Patrick Segers (UGent)
- Organization
- Project
- Abstract
- Background: Carotid-femoral pulse-wave velocity (cfPWV) has been recognized as a biomarker for arterial stiffness. It is therefore valuable to be able to estimate this value easily and quickly for a wide range of potential patients [1]. We are developing a novel device based on multi-beam laser-doppler vibrometry. It can measure pulse-induced vibrations of high spatial and temporal resolution on bare skin the neck and groin. Two methods of estimating carotid-femoral pulse transit time (cfPTT) were tested. Methods: We applied a dedicated beamforming algorithm to combine and improve the data from 6 parallel signals of simultaneous measurements at both carotid and femoral measurement sites. This was done on a subset of N=54 high-quality carotid-femoral LDV measurements [2]. We then calculated cfPTT (1) using all pair-wise combinations of the raw signals from all channels (brute-force method) and (2) using the beamformed signals. The final cfPTT estimate, in each case, was computed as the average of all estimated cfPTT’s per dataset. These cfPTT’s were then compared to reference cfPTT’s (Sphygmocor system). Results: As the number of generated cfPTT’s in a given measurement increased (>75), so did the correspondence of the final cfPTT estimate with the reference (see Figure 1). The same effect was observed with increasing number of timepoints (>5) at which a cfPTT was able to be calculated. This held true for cfPTT’s estimated using both beamforming and brute-force techniques. Conclusions: Accurate cfPTT estimates are obtained for good-quality LDV-measurements, where sufficient discernable heartbeats were recognized using the beamforming and brute-force methods.
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Citation
Please use this url to cite or link to this publication: http://hdl.handle.net/1854/LU-8771525
- MLA
- Beeckman, Simeon, et al. “Beamforming LDV-Data for Carotid-Femoral Pulse-Wave Velocity Estimation.” ARTERY 22, Abstracts, 2022.
- APA
- Beeckman, S., Li, Y., Aasmul, S., Bruno, R.-M., Boutouyrie, P., Madhu, N., & Segers, P. (2022). Beamforming LDV-data for carotid-femoral pulse-wave velocity estimation. ARTERY 22, Abstracts. Presented at the ARTERY 2022, Nancy, France.
- Chicago author-date
- Beeckman, Simeon, Yanlu Li, Soren Aasmul, Rosa-Maria Bruno, Pierre Boutouyrie, Nilesh Madhu, and Patrick Segers. 2022. “Beamforming LDV-Data for Carotid-Femoral Pulse-Wave Velocity Estimation.” In ARTERY 22, Abstracts.
- Chicago author-date (all authors)
- Beeckman, Simeon, Yanlu Li, Soren Aasmul, Rosa-Maria Bruno, Pierre Boutouyrie, Nilesh Madhu, and Patrick Segers. 2022. “Beamforming LDV-Data for Carotid-Femoral Pulse-Wave Velocity Estimation.” In ARTERY 22, Abstracts.
- Vancouver
- 1.Beeckman S, Li Y, Aasmul S, Bruno R-M, Boutouyrie P, Madhu N, et al. Beamforming LDV-data for carotid-femoral pulse-wave velocity estimation. In: ARTERY 22, Abstracts. 2022.
- IEEE
- [1]S. Beeckman et al., “Beamforming LDV-data for carotid-femoral pulse-wave velocity estimation,” in ARTERY 22, Abstracts, Nancy, France, 2022.
@inproceedings{8771525, abstract = {{Background: Carotid-femoral pulse-wave velocity (cfPWV) has been recognized as a biomarker for arterial stiffness. It is therefore valuable to be able to estimate this value easily and quickly for a wide range of potential patients [1]. We are developing a novel device based on multi-beam laser-doppler vibrometry. It can measure pulse-induced vibrations of high spatial and temporal resolution on bare skin the neck and groin. Two methods of estimating carotid-femoral pulse transit time (cfPTT) were tested. Methods: We applied a dedicated beamforming algorithm to combine and improve the data from 6 parallel signals of simultaneous measurements at both carotid and femoral measurement sites. This was done on a subset of N=54 high-quality carotid-femoral LDV measurements [2]. We then calculated cfPTT (1) using all pair-wise combinations of the raw signals from all channels (brute-force method) and (2) using the beamformed signals. The final cfPTT estimate, in each case, was computed as the average of all estimated cfPTT’s per dataset. These cfPTT’s were then compared to reference cfPTT’s (Sphygmocor system). Results: As the number of generated cfPTT’s in a given measurement increased (>75), so did the correspondence of the final cfPTT estimate with the reference (see Figure 1). The same effect was observed with increasing number of timepoints (>5) at which a cfPTT was able to be calculated. This held true for cfPTT’s estimated using both beamforming and brute-force techniques. Conclusions: Accurate cfPTT estimates are obtained for good-quality LDV-measurements, where sufficient discernable heartbeats were recognized using the beamforming and brute-force methods.}}, author = {{Beeckman, Simeon and Li, Yanlu and Aasmul, Soren and Bruno, Rosa-Maria and Boutouyrie, Pierre and Madhu, Nilesh and Segers, Patrick}}, booktitle = {{ARTERY 22, Abstracts}}, language = {{eng}}, location = {{Nancy, France}}, pages = {{1}}, title = {{Beamforming LDV-data for carotid-femoral pulse-wave velocity estimation}}, year = {{2022}}, }