Noninvasive Cerebral Blood Flow Monitoring Using Inductive Sensing Technology

Zhang, Maoting; Zhou, Cheng; Zeng, Lingxi; Hou, Xianhua; Xu, Jing; Xu, Lin; Wang, Feng; Zhuang, Wei; Chen, Yujie; Chen, Mingsheng; Yin, Shengyu; Li, Gen; Sun, Jian

doi:10.1109/tim.2023.3289539

Cited by 8 publications

(3 citation statements)

References 31 publications

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“…The experimental results indicate that RF changes of the order of 10–5 can still be detected at a vertical distance of 8 cm and a lateral displacement of 4 cm, with pronounced periodic pulsations identifiable between peaks and troughs. Compared to existing induction-based CBF assessment system, the effective detection range and depth of our proposed system are enhanced by a factor of three to four ( Zeng et al, 2022 ; Zhang et al, 2023 ).…”

Section: Discussionmentioning

confidence: 99%

“…And its primary frequency component is close to heart rate. In another experiment, inductive technology was used to observe pulsatile CBF in healthy volunteers during continuous inhalation of a certain concentration of CO 2 ( Zhang et al, 2023 ). Results indicated significant changes in time-domain and frequency-domain characteristics of the inductive signal correlated with the duration of CO 2 inhalation.…”

Section: Introductionmentioning

confidence: 99%

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Dynamic cerebral blood flow assessment based on electromagnetic coupling sensing and image feature analysis

Gong,

Zeng,

Jiang

et al. 2024

Front. Bioeng. Biotechnol.

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Dynamic assessment of cerebral blood flow (CBF) is crucial for guiding personalized management and treatment strategies, and improving the prognosis of stroke. However, a safe, reliable, and effective method for dynamic CBF evaluation is currently lacking in clinical practice. In this study, we developed a CBF monitoring system utilizing electromagnetic coupling sensing (ECS). This system detects variations in brain conductivity and dielectric constant by identifying the resonant frequency (RF) in an equivalent circuit containing both magnetic induction and electrical coupling. We evaluated the performance of the system using a self-made physical model of blood vessel pulsation to test pulsatile CBF. Additionally, we recruited 29 healthy volunteers to monitor cerebral oxygen (CO), cerebral blood flow velocity (CBFV) data and RF data before and after caffeine consumption. We analyzed RF and CBFV trends during immediate responses to abnormal intracranial blood supply, induced by changes in vascular stiffness, and compared them with CO data. Furthermore, we explored a method of dynamically assessing the overall level of CBF by leveraging image feature analysis. Experimental testing substantiates that this system provides a detection range and depth enhanced by three to four times compared to conventional electromagnetic detection techniques, thereby comprehensively covering the principal intracranial blood supply areas. And the system effectively captures CBF responses under different intravascular pressure stimulations. In healthy volunteers, as cerebral vascular stiffness increases and CO decreases due to caffeine intake, the RF pulsation amplitude diminishes progressively. Upon extraction and selection of image features, widely used machine learning algorithms exhibit commendable performance in classifying overall CBF levels. These results highlight that our proposed methodology, predicated on ECS and image feature analysis, enables the capture of immediate responses of abnormal intracranial blood supply triggered by alterations in vascular stiffness. Moreover, it provides an accurate diagnosis of the overall CBF level under varying physiological conditions.

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Dynamic cerebral blood flow assessment based on electromagnetic coupling sensing and image feature analysis

Gong,

Zeng,

Jiang

et al. 2024

Front. Bioeng. Biotechnol.

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“…An LDC provides a solution with low cost, low power consumption, and reliable performance for frequency signal measurement [ 25 ]. Its typical applications include metal testing in the automotive industry, buttons on household electronic products, and inductive equipment, such as noninvasive cerebral blood flow monitoring [ 26 ], heart activity monitoring, cardiac activity detection [ 27 ], and other inductor equipment. Brittany Rapp et al used an LDC to detect the nanofluids (NFs) system containing golden nanoparticles (NPs).…”

Section: Introductionmentioning

confidence: 99%

Non-Destructive Testing of Carbon Fiber-Reinforced Plastics (CFRPs) Using a Resonant Eddy Current Sensor

Ma,

Liu,

Zhang

et al. 2024

Sensors

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Eddy current testing (ECT) is commonly used for the detection of defects inside metallic materials. In order to achieve the effective testing of CFRP materials, increasing the operating frequency or improving the coil structure is a common method used by researchers. Higher or wider operating frequencies make the design of the ADC’s conditioning circuit complex and difficult to miniaturize. In this paper, an LC resonator based on inductance-to-digital converters (LDCs) is designed to easily detect the resonant frequency response to the state of the material under test. The reasonableness of the coil design is proven by simulation. The high signal-to-noise ratio (SNR) and detection sensitivity of the LC resonator are demonstrated through comparison experiments involving multiple probes. The anti-interference capability of the LC resonator in CFRP defect detection is demonstrated through various interference experiments.

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MOF-derived NiO/N-MWCNTs@PVDF film and MXene/Carbon/Ecoflex electrode for enhanced hybrid nanogenerator towards environmental monitoring

Wang

Tao

et al. 2023

Composites Part A: Applied Science and Manufacturing

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Noninvasive Cerebral Blood Flow Monitoring Using Inductive Sensing Technology

Cited by 8 publications

References 31 publications

Dynamic cerebral blood flow assessment based on electromagnetic coupling sensing and image feature analysis

Dynamic cerebral blood flow assessment based on electromagnetic coupling sensing and image feature analysis

Non-Destructive Testing of Carbon Fiber-Reinforced Plastics (CFRPs) Using a Resonant Eddy Current Sensor

MOF-derived NiO/N-MWCNTs@PVDF film and MXene/Carbon/Ecoflex electrode for enhanced hybrid nanogenerator towards environmental monitoring

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