Assessment of the brain ischemia during orthostatic stress and lower body negative pressure in air force pilots by near-infrared spectroscopy

Central blood volume loss to venous pooling in the lower extremities and vasoconstrictor response are commonly viewed as key factors to distinguish between individuals with high and low tolerance to orthostatic stress. In this study, we analyzed calf vasoconstriction as a function of venous pooling during simulated orthostatic stress. We hypothesized that high orthostatic tolerance (OT) would be associated with greater vasoconstrictor responses to venous pooling compared with low OT. Nineteen participants underwent continuous stepped lower body negative pressure at −10, −20, −30, −40, −50, and −60 mmHg each for 5 min or until exhibiting signs of presyncope. Ten participants completed the lower body negative pressure procedure without presyncope and were categorized with high OT; the remaining nine were categorized as having low OT. Near-infrared spectroscopy measurements of vasoconstriction (Hachiya T, Blaber A, Saito M. Acta Physiologica 193: 117–127, 2008) in calf muscles, along with heart rate (HR) responses for each participant, were evaluated in relation to calf blood volume, estimated by plethysmography. The slopes of this relationship between vasoconstriction and blood volume were not different between the high- and low-tolerance groups. However, the onset of vasoconstriction in the high-tolerance group was delayed. Greater HR increments in the low-tolerance group were also observed as a function of lower limb blood pooling. The delayed vasoconstriction and slower HR increments in the high-tolerance group to similar venous pooling in the low group may suggest a greater vascular reserve and possible delayed reduction in venous return.

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Mismatch between Tissue Partial Oxygen Pressure and Near-Infrared Spectroscopy Neuromonitoring of Tissue Respiration in Acute Brain Trauma: The Rationale for Implementing a Multimodal Monitoring Strategy

International Journal of Molecular Sciences ◽

10.3390/ijms22031122 ◽

2021 ◽

Vol 22 (3) ◽

pp. 1122

Author(s):

Mario Forcione ◽

Mario Ganau ◽

Lara Prisco ◽

Antonio Maria Chiarelli ◽

Andrea Bellelli ◽

...

Keyword(s):

Infrared Spectroscopy ◽

Near Infrared Spectroscopy ◽

Oxygen Pressure ◽

Near Infrared ◽

Optical Signal ◽

Brain Trauma ◽

Partial Oxygen Pressure ◽

Tissue Respiration ◽

The Brain ◽

Partial Oxygen

The brain tissue partial oxygen pressure (PbtO2) and near-infrared spectroscopy (NIRS) neuromonitoring are frequently compared in the management of acute moderate and severe traumatic brain injury patients; however, the relationship between their respective output parameters flows from the complex pathogenesis of tissue respiration after brain trauma. NIRS neuromonitoring overcomes certain limitations related to the heterogeneity of the pathology across the brain that cannot be adequately addressed by local-sample invasive neuromonitoring (e.g., PbtO2 neuromonitoring, microdialysis), and it allows clinicians to assess parameters that cannot otherwise be scanned. The anatomical co-registration of an NIRS signal with axial imaging (e.g., computerized tomography scan) enhances the optical signal, which can be changed by the anatomy of the lesions and the significance of the radiological assessment. These arguments led us to conclude that rather than aiming to substitute PbtO2 with tissue saturation, multiple types of NIRS should be included via multimodal systemic- and neuro-monitoring, whose values then are incorporated into biosignatures linked to patient status and prognosis. Discussion on the abnormalities in tissue respiration due to brain trauma and how they affect the PbtO2 and NIRS neuromonitoring is given.

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Functional Near Infrared Spectroscopy (fNIRS) based Odor Detection and Classification using Functional Data Analysis

10.1101/2021.02.13.431051 ◽

2021 ◽

Author(s):

Faezeh Moradi ◽

Shima T. Moein ◽

Issa Zakeri ◽

Kambiz Pourrezaei

Keyword(s):

Infrared Spectroscopy ◽

Data Analysis ◽

Near Infrared Spectroscopy ◽

Functional Data Analysis ◽

Functional Data ◽

Near Infrared ◽

Stimulus Condition ◽

Functional Near Infrared Spectroscopy ◽

Odor Detection ◽

The Brain

AbstractAn objective approach for odor detection is to analyze the brain activity using imaging techniques during the odor stimulation. In this study, Functional Near Infrared Spectroscopy (fNIRS) is used to record hemodynamic response from the frontal region of the brain by using a 4-channel fNIRS system. The fNIRs data is collected during the odor detection task in which the subjects were asked to press a button when they detect the given odor. Functional Data Analysis (FDA) was applied on fNIRs data to convert discrete measured samples of data to continuous smooth curves. The FDA method enables us to use the bases coefficients of fNIRS smoothed curves for features that represent the shape of the raw fNIRS signal. With the learning algorithm that we proposed, these features were used to train the support vector machine classifier. We evaluated the odor detection problem, in two binary classification cases: odorant vs. non-odorant and odorant vs. fingertapping. The model achieved a classification accuracy of 94.12% and 97.06% over the stimulus condition in the two cases, respectively. Moreover to find the actual predictors we used the extracted defined features (slope, standard deviation, and delta) to train our classifier. We achieved an average accuracy of 91.18 % on classifying odorant vs. non-odorant and an accuracy of 94.12% for odorant vs. fingertapping on the stimulus condition. The results determined that fNIRs signals of odorant and non-odorant are distinguishable without being affected by the motor activity during the experiment.These findings suggest that fNIRs measurement on the forehead could be potentially used for objective and comparably inexpensive assessment of odor detection in cases that the subjective report is unreliable.

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Brain–Computer Interfacing Using Functional Near-Infrared Spectroscopy (fNIRS)

Biosensors ◽

10.3390/bios11100389 ◽

2021 ◽

Vol 11 (10) ◽

pp. 389

Author(s):

Kogulan Paulmurugan ◽

Vimalan Vijayaragavan ◽

Sayantan Ghosh ◽

Parasuraman Padmanabhan ◽

Balázs Gulyás

Keyword(s):

Infrared Spectroscopy ◽

Near Infrared Spectroscopy ◽

Brain Function ◽

Near Infrared ◽

Functional Near Infrared Spectroscopy ◽

Non Invasive ◽

Neuron Function ◽

Brain Computer Interfacing ◽

The Brain ◽

Computer Interfacing

Functional Near-Infrared Spectroscopy (fNIRS) is a wearable optical spectroscopy system originally developed for continuous and non-invasive monitoring of brain function by measuring blood oxygen concentration. Recent advancements in brain–computer interfacing allow us to control the neuron function of the brain by combining it with fNIRS to regulate cognitive function. In this review manuscript, we provide information regarding current advancement in fNIRS and how it provides advantages in developing brain–computer interfacing to enable neuron function. We also briefly discuss about how we can use this technology for further applications.

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