A compact and cost-effective laser-powered speckle visibility spectroscopy (SVS) device for measuring cerebral blood flow
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arXiv
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| Autores principales: | , , , , , , , , |
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| Formato: | Preprint |
| Publicado: |
2024
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| _version_ | 1866910323373506560 |
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| author | Huang, Yu Xi Mahler, Simon Dickson, Maya Abedi, Aidin Tyszka, Julian M. Tung, Jack Lo Yu Russin, Jonathan Liu, Charles Yang, Changhuei |
| author_facet | Huang, Yu Xi Mahler, Simon Dickson, Maya Abedi, Aidin Tyszka, Julian M. Tung, Jack Lo Yu Russin, Jonathan Liu, Charles Yang, Changhuei |
| contents | In the realm of cerebrovascular monitoring, primary metrics typically include blood pressure, which influences cerebral blood flow (CBF) and is contingent upon vessel radius. Measuring CBF non-invasively poses a persistent challenge, primarily attributed to the difficulty of accessing and obtaining signal from the brain. This study aims to introduce a compact speckle visibility spectroscopy (SVS) device designed for non-invasive CBF measurements, offering cost-effectiveness and scalability while tracking CBF with remarkable sensitivity and temporal resolution. The wearable hardware has a modular design approach consisting solely of a laser diode as the source and a meticulously selected board camera as the detector. They both can be easily placed on the head of a subject to measure CBF with no additional optical elements. The SVS device can achieve a sampling rate of 80 Hz with minimal susceptibility to external disturbances. The device also achieves better SNR compared with traditional fiber-based SVS devices, capturing about 70 times more signal and showing superior stability and reproducibility. It is designed to be paired and distributed in multiple configurations around the head, and measure signals that exceed the quality of prior optical CBF measurement techniques. Given its cost-effectiveness, scalability, and simplicity, this laser-centric tool offers significant potential in advancing non-invasive cerebral monitoring technologies. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2401_16592 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | A compact and cost-effective laser-powered speckle visibility spectroscopy (SVS) device for measuring cerebral blood flow Huang, Yu Xi Mahler, Simon Dickson, Maya Abedi, Aidin Tyszka, Julian M. Tung, Jack Lo Yu Russin, Jonathan Liu, Charles Yang, Changhuei Medical Physics Image and Video Processing In the realm of cerebrovascular monitoring, primary metrics typically include blood pressure, which influences cerebral blood flow (CBF) and is contingent upon vessel radius. Measuring CBF non-invasively poses a persistent challenge, primarily attributed to the difficulty of accessing and obtaining signal from the brain. This study aims to introduce a compact speckle visibility spectroscopy (SVS) device designed for non-invasive CBF measurements, offering cost-effectiveness and scalability while tracking CBF with remarkable sensitivity and temporal resolution. The wearable hardware has a modular design approach consisting solely of a laser diode as the source and a meticulously selected board camera as the detector. They both can be easily placed on the head of a subject to measure CBF with no additional optical elements. The SVS device can achieve a sampling rate of 80 Hz with minimal susceptibility to external disturbances. The device also achieves better SNR compared with traditional fiber-based SVS devices, capturing about 70 times more signal and showing superior stability and reproducibility. It is designed to be paired and distributed in multiple configurations around the head, and measure signals that exceed the quality of prior optical CBF measurement techniques. Given its cost-effectiveness, scalability, and simplicity, this laser-centric tool offers significant potential in advancing non-invasive cerebral monitoring technologies. |
| title | A compact and cost-effective laser-powered speckle visibility spectroscopy (SVS) device for measuring cerebral blood flow |
| topic | Medical Physics Image and Video Processing |
| url | https://arxiv.org/abs/2401.16592 |