Noninvasive Blood and Tissue Analysis: Raman Spectroscopy, One Perspective for Monitoring of Glucose and Beyond

Chaiken, J.

doi:10.1177/1932296820964803

Cited by 10 publications

(4 citation statements)

References 40 publications

(69 reference statements)

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The potential for employing spectroscopic analysis noninvasively, in vivo, to provide quantitative measures of physiology has never been greater 1 . Enabled by new photonic technologies, improved measurement of long-standing vital signs e.g.…”

Section: Introductionmentioning

confidence: 99%

Noninvasive in-vivo monitoring of plasma volume and hematocrit using the FRD-PVOH device: from cozy to cold

Porreca,

Dent,

Peterson

et al. 2024

Data Science for Photonics and Biophotonics

View full text Add to dashboard Cite

The FRD-PVOH algorithm/medical device enables continuous noninvasive spectroscopic analysis and monitoring of physiology induced changes in the peripheral vasculature in vivo in humans, specifically red blood cell and plasma volume fractions. Previously, FRD-PVOH demonstrated a correlation between mean arterial pressure (MAP) and vascular plasma volume with tilt-table experiments, indicating physiological relevance. Continuous monitoring of plasma volume and hematocrit (Hct) with a total bandwidth of 0-0.3 Hz in volar side fingertip capillary beds, reveals MAP fluctuations superimposed on slower background. These MAP fluctuations isolated from slower vascular volume shifts and the cardiac pulse create a time series associated with vasodilation/vasoconstriction i.e., thermoregulation, an autonomic path to homeostasis. We consistently observe random walk dynamics i.e., the amplitudes of the fluctuations in the time domain are distributed as a Gaussian while Fourier analysis simultaneously confirms the presence of circulatory physiology in the results i.e., breathing effects and the Baroflex response. Lorenz plots indicate linear dynamics control short and long timescale fluctuations across both test subjects. ANOVA analysis of data from a small, on-going, study using a mild external thermoregulation protocol (2 supine subjects, 16 total hours of monitoring for each subject, in 8 sessions of 2 hours each) demonstrates that the number of fluctuations per unit time varies across the two subjects with 95% significance with or without the thermoregulation challenge. Also, the mean number of fluctuations per monitoring session was significantly greater for sessions that included an external thermoregulation challenge compared to those that did not, for both subjects at 95% confidence.

show abstract

Section: Introductionmentioning

confidence: 99%

Noninvasive in-vivo monitoring of plasma volume and hematocrit using the FRD-PVOH device: from cozy to cold

Porreca,

Dent,

Peterson

et al. 2024

Data Science for Photonics and Biophotonics

View full text Add to dashboard Cite

show abstract

“…Different molecules have different characteristics of Raman spectroscopy, so it can be used as a "fingerprint" spectrum for molecular recognition [3] . In recent years, Raman spectroscopy has attracted attention in the field of blood glucose concentration measurement due to its rapidness, high-efficiency and high-sensitivity [4] . However, blood glucose concentration is low and the composition of blood is complex, spectral signal of glucose is easy to be influenced by noise or other components, so the estimation of blood glucose concentration by Raman spectroscopy is a challenging task.…”

Section: Introductionmentioning

confidence: 99%

Blood glucose concentration estimation by Raman spectroscopy based on particle swarm optimized SVR

Jing

Fan

Gao

et al. 2023

AOPC 2022: Optical Information and Networks

View full text Add to dashboard Cite

Blood glucose level has important significance for medical diagnosis. Blood glucose measurement in traditional methods requires collecting blood samples several times a day, which causes discomfort, environmental pollution and so on. As a "fingerprint" spectrum for molecular recognition, Raman spectroscopy has attracted attention in blood glucose measurement. However, blood glucose level is low and spectral signal of glucose is easy to be influenced by noise and other components. To improve accuracy of blood glucose concentration estimation by Raman spectroscopy, we carried out the Raman blood glucose measurement in vitro, the interferograms of blood samples in different glucose concentrations were measured by the self-developed Spatial Heterodyne Raman Spectrometer (SHRS), and converted the interferograms to one-dimensional spectroscopic data using Fourier transform. In order to get data with higher quality, we used wavelet decomposition to remove the noise and sparse representation to remove the signal baseline. Then, selected the spectroscopy at 500-2500 cm -1 as input, and the corresponding blood glucose concentration value as label, use particle swarm optimization-support vector regression (PSO-SVR) algorithm to construct the blood glucose concentration estimation model. The results show that the R 2 of test set is 0.8041 and the RMSE is 1.8580. And the accuracy of blood glucose concentration estimation was evaluated by the Clark Error Grid. The model based on PSO-SVR can achieve accurate estimation of blood glucose concentration. This method has important research significance and application potential for blood glucose measurement.

show abstract

“…For example, flexible wearable strain sensors are attached to the human body to monitor joint movement information, and inertial sensors are used together to improve training performances [ 5 ] and warn injury [ 6 ] during movement. Flexible wearable sensors can monitor the cardiovascular vital signs continuously and in real-time, including ECG [ 7 , 8 ], heart rate [ 9 , 10 ], blood pressure [ 11 ], blood oxygen [ 12 ], and blood glucose [ 13 , 14 ]. Advances in new materials, advanced manufacturing, and flexible electronics technologies have improved comfort, real-time, and precision and expanded the range of applications.…”

Section: Introductionmentioning

confidence: 99%

A Review of Recent Advances in Vital Signals Monitoring of Sports and Health via Flexible Wearable Sensors

Sun

Guo

Yang

et al. 2022

Sensors

View full text Add to dashboard Cite

In recent years, vital signals monitoring in sports and health have been considered the research focus in the field of wearable sensing technologies. Typical signals include bioelectrical signals, biophysical signals, and biochemical signals, which have applications in the fields of athletic training, medical diagnosis and prevention, and rehabilitation. In particular, since the COVID-19 pandemic, there has been a dramatic increase in real-time interest in personal health. This has created an urgent need for flexible, wearable, portable, and real-time monitoring sensors to remotely monitor these signals in response to health management. To this end, the paper reviews recent advances in flexible wearable sensors for monitoring vital signals in sports and health. More precisely, emerging wearable devices and systems for health and exercise-related vital signals (e.g., ECG, EEG, EMG, inertia, body movements, heart rate, blood, sweat, and interstitial fluid) are reviewed first. Then, the paper creatively presents multidimensional and multimodal wearable sensors and systems. The paper also summarizes the current challenges and limitations and future directions of wearable sensors for vital typical signal detection. Through the review, the paper finds that these signals can be effectively monitored and used for health management (e.g., disease prediction) thanks to advanced manufacturing, flexible electronics, IoT, and artificial intelligence algorithms; however, wearable sensors and systems with multidimensional and multimodal are more compliant.

show abstract

Noninvasive Blood and Tissue Analysis: Raman Spectroscopy, One Perspective for Monitoring of Glucose and Beyond

Cited by 10 publications

References 40 publications

Noninvasive in-vivo monitoring of plasma volume and hematocrit using the FRD-PVOH device: from cozy to cold

Noninvasive in-vivo monitoring of plasma volume and hematocrit using the FRD-PVOH device: from cozy to cold

Blood glucose concentration estimation by Raman spectroscopy based on particle swarm optimized SVR

A Review of Recent Advances in Vital Signals Monitoring of Sports and Health via Flexible Wearable Sensors

Contact Info

Product

Resources

About