SHADE: Absorption spectroscopy enhancement with ambient light estimation and narrow-band detection

Sherkat, Habib; Pinto-Orellana, Marco Antonio; Mirtaheri, Peyman

doi:10.1016/j.ijleo.2020.165116

Cited by 6 publications

(4 citation statements)

References 23 publications

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“…Loss of contact between the probe’s surface and skin is commonly caused by subject movement. When it occurs, resultant contamination in FD-DOS/DCS measurements from ambient light and source light that has not traveled through tissue can lead to noisy data, discontinuous data shifts, and detector saturation [ 26 , 42 ]. Inconsistent contact also worsens motion artifacts in the data and hinders measurement reproducibility [ 26 , 43 , 44 ].…”

Section: Methodsmentioning

confidence: 99%

Chassis-based fiber-coupled optical probe design for reproducible quantitative diffuse optical spectroscopy measurements

Matlis,

Zhang,

Benson

et al. 2024

PLoS ONE

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Advanced optical neuromonitoring of cerebral hemodynamics with hybrid diffuse optical spectroscopy (DOS) and diffuse correlation spectroscopy (DCS) methods holds promise for non-invasive characterization of brain health in critically ill patients. However, the methods’ fiber-coupled patient interfaces (probes) are challenging to apply in emergent clinical scenarios that require rapid and reproducible attachment to the head. To address this challenge, we developed a novel chassis-based optical probe design for DOS/DCS measurements and validated its measurement accuracy and reproducibility against conventional, manually held measurements of cerebral hemodynamics in pediatric swine (n = 20). The chassis-based probe design comprises a detachable fiber housing which snaps into a 3D-printed, circumferential chassis piece that is secured to the skin. To validate its reproducibility, eight measurement repetitions of cerebral tissue blood flow index (BFI), oxygen saturation (StO2), and oxy-, deoxy- and total hemoglobin concentration were acquired at the same demarcated measurement location for each pig. The probe was detached after each measurement. Of the eight measurements, four were acquired by placing the probe into a secured chassis, and four were visually aligned and manually held. We compared the absolute value and intra-subject coefficient of variation (CV) of chassis versus manual measurements. No significant differences were observed in either absolute value or CV between chassis and manual measurements (p > 0.05). However, the CV for BFI (mean ± SD: manual, 19.5% ± 9.6; chassis, 19.0% ± 10.8) was significantly higher than StO2 (manual, 5.8% ± 6.7; chassis, 6.6% ± 7.1) regardless of measurement methodology (p<0.001). The chassis-based DOS/DCS probe design facilitated rapid probe attachment/re-attachment and demonstrated comparable accuracy and reproducibility to conventional, manual alignment. In the future, this design may be adapted for clinical applications to allow for non-invasive monitoring of cerebral health during pediatric critical care.

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Section: Methodsmentioning

confidence: 99%

Chassis-based fiber-coupled optical probe design for reproducible quantitative diffuse optical spectroscopy measurements

Matlis,

Zhang,

Benson

et al. 2024

PLoS ONE

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“…where ε is the molar extinction coefficient, a μ represents the absorption system, 1 λ and 2 λ represent red light and near-infrared light, and the ratio of absorption coefficient can be approximately simplified to be equivalent to the ratio of reflected light intensity [10,11] , namely:…”

Section: The Detection Principle Of Blood Oxygen Sensormentioning

confidence: 99%

Study on Compensation of Blood Oxygen Sensor’s Ambient Light Based on GA-BP Neural Network

Zhu

Wang

2023

J. Phys.: Conf. Ser.

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In order to reduce the interference of ambient light on near-infrared blood oxygen sensors (used to measure oxygen saturation of human tissue or oxygen saturation of circulating blood during Extracorporeal membrane oxygenation treatment) and improve the measurement accuracy of a blood oxygen sensor, a compensation method of ambient light interference is proposed. This method does not need an ambient light sensor or an additional circuit. The interference intensity of ambient light is calculated by changing the light intensity value emitted by the LED in the sensor and combining the light intensity value received by the sensor. The Genetic Algorithms-Back Propagation(GA-BP) neural network is modeled, the detection light intensity value and the ambient light interference evaluation values are taken as the input characteristics, the blood gas analysis true value is taken as the expected output, and the network model is used for prediction. The results show that the accuracy of this method is higher than the traditional fitting results, and the error between the network prediction value and the true value of blood gas analysis is basically within 5%.

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“…Ambient light can significantly affect fNIRS' signal quality, mainly if the experiment is not conducted in a controlled environment. Sherkat et al ( 2020 ) recently introduced an efficient empirical compensation algorithm to mitigate the non-stationary impact of ambient light on the fNIRS data. In this approach, the system dynamically measures the ambient light.…”

Section: Hybrid Eeg-fnirs-based Bcimentioning

confidence: 99%

Analysis of Human Gait Using Hybrid EEG-fNIRS-Based BCI System: A Review

Khan

Naseer

Yazidi

et al. 2021

Front. Hum. Neurosci.

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Human gait is a complex activity that requires high coordination between the central nervous system, the limb, and the musculoskeletal system. More research is needed to understand the latter coordination's complexity in designing better and more effective rehabilitation strategies for gait disorders. Electroencephalogram (EEG) and functional near-infrared spectroscopy (fNIRS) are among the most used technologies for monitoring brain activities due to portability, non-invasiveness, and relatively low cost compared to others. Fusing EEG and fNIRS is a well-known and established methodology proven to enhance brain–computer interface (BCI) performance in terms of classification accuracy, number of control commands, and response time. Although there has been significant research exploring hybrid BCI (hBCI) involving both EEG and fNIRS for different types of tasks and human activities, human gait remains still underinvestigated. In this article, we aim to shed light on the recent development in the analysis of human gait using a hybrid EEG-fNIRS-based BCI system. The current review has followed guidelines of preferred reporting items for systematic reviews and meta-Analyses (PRISMA) during the data collection and selection phase. In this review, we put a particular focus on the commonly used signal processing and machine learning algorithms, as well as survey the potential applications of gait analysis. We distill some of the critical findings of this survey as follows. First, hardware specifications and experimental paradigms should be carefully considered because of their direct impact on the quality of gait assessment. Second, since both modalities, EEG and fNIRS, are sensitive to motion artifacts, instrumental, and physiological noises, there is a quest for more robust and sophisticated signal processing algorithms. Third, hybrid temporal and spatial features, obtained by virtue of fusing EEG and fNIRS and associated with cortical activation, can help better identify the correlation between brain activation and gait. In conclusion, hBCI (EEG + fNIRS) system is not yet much explored for the lower limb due to its complexity compared to the higher limb. Existing BCI systems for gait monitoring tend to only focus on one modality. We foresee a vast potential in adopting hBCI in gait analysis. Imminent technical breakthroughs are expected using hybrid EEG-fNIRS-based BCI for gait to control assistive devices and Monitor neuro-plasticity in neuro-rehabilitation. However, although those hybrid systems perform well in a controlled experimental environment when it comes to adopting them as a certified medical device in real-life clinical applications, there is still a long way to go.

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SHADE: Absorption spectroscopy enhancement with ambient light estimation and narrow-band detection

Cited by 6 publications

References 23 publications

Chassis-based fiber-coupled optical probe design for reproducible quantitative diffuse optical spectroscopy measurements

Chassis-based fiber-coupled optical probe design for reproducible quantitative diffuse optical spectroscopy measurements

Study on Compensation of Blood Oxygen Sensor’s Ambient Light Based on GA-BP Neural Network

Analysis of Human Gait Using Hybrid EEG-fNIRS-Based BCI System: A Review

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