Search Results (4)

The possibility of G-induced loss of consciousness (G-LOC) is a key concern when flying modern, high-performance aircraft. Currently, there are no identification methods available based on physiological data. This study aimed to determine whether specific pulse wave changes could be reliably identified using automatic computer algorithms to detect impending G-LOC. The pulse waves of 86 people who experienced G-LOC in a human centrifuge were analysed alongside an age-, gender-, nationality-, training-, and anti-G-equipment-matched control group using computer algorithm methods to analyse possible longer reductions in the G-LOC group. Based on this data, the study showed that centrifuge profiles with a gradual “onset run” using AGSM resulted in longer pulse wave flattening around the G-LOC in the G-LOC group than in the matched control group. However, this could not be verified in human centrifuge runs with active flight profiles and higher onset rates. Unfortunately, this means that the method used here would not currently be applicable in actual flight. In the future, the possibility of creating an identification method could be extended by incorporating additional physiological data. Full article

Prolonged +Gz acceleration during high-performance flight exposes pilots to the risk of G-induced loss of consciousness (G-LOC), a dangerous condition that compromises operational safety. To enable early detection without intrusive sensors, we present a vision-based warning system that analyzes facial action units (AUs) as physiological indicators of impending G-LOC. Our approach combines computer vision with physiological modeling to capture subtle facial microexpressions associated with cerebral hypoxia using widely available RGB cameras. We propose a novel Graph Convolution-Augmented Vision Transformer (GC-ViT) network architecture that effectively captures dynamic AU variations in pilots under G-LOC conditions by integrating global context modeling with vision Transformer. The proposed framework integrates a vision–semantics collaborative Transformer for robust AU feature extraction, where EfficientNet-based spatiotemporal modeling is enhanced by Transformer attention mechanisms to maintain recognition accuracy under high-G stress. Building upon this, we develop a graph-based physiological model that dynamically tracks interactions between critical AUs during G-LOC progression by learning the characteristic patterns of AU co-activation during centrifugal training. Experimental validation on centrifuge training datasets demonstrates strong performance, achieving an AUC-ROC of 0.898 and an AP score of 0.96, confirming the system’s ability to reliably identify characteristic patterns of AU co-activation during G-LOC events. Overall, this contact-free system offers an interpretable solution for rapid G-LOC detection, or as a complementary enhancement to existing aeromedical monitoring technologies. The non-invasive design demonstrates significant potential for improving safety in aerospace physiology applications without requiring modifications to current cockpit or centrifuge setups. Full article

Hyperglycemia, which arises in type 1 or 2 diabetes, leads to different complications, such as macrovascular disease, nephropathy, retinopathy, and neuropathy. In addition, different cognitive variations are associated with type 1 diabetes. Long-term changes in glucose metabolism might induce effects on the central nervous system (CNS) such as reduced mental performance and loss of consciousness, which could be implicated in neurotoxicity. The direct impact of hyperglycemia and elevated glucose concentrations on neuronal cells remains to be fully elucidated, primarily due to the multifaceted mechanisms underlying glucose neurotoxicity, including apoptosis, oxidative stress, and alterations in signaling cascades. The multifaceted mechanisms further complicate the study of the relationship between diabetes and neurodegeneration. Research in this field is continually advancing, with the aim of investigating these eventual connections and developing more effective preventive and therapeutic strategies. The present study aims to assess the damage induced by different glucose concentrations (from 25 to 150 mM) in a neuronal model, such as PC12 cells, rat pheochromocytoma cells. In glucose-exposed PC12 cells, we have tested oxidative stress, apoptosis, and cell migration by (a) viability screening, (b) intracellular levels of anion superoxide (O₂⁻), (c) extracellular levels of MDA and nitrites, (d) apoptosis, and (e) the wound healing assay. By the cell viability assay, it has emerged that glucose (25–150 mM) showed a stronger effect at the highest concentrations (100 and 150 mM). The increase in MDA and O₂⁻ levels was determined in PC12 cells treated with high glucose concentrations (6.5–8.8 fold for MDA). High concentrations (100 and 150 mM) significantly reduced the expression of full-length caspase-3 (2.8-fold and 4.2-fold decrease at 24 and 72 h) and caspase-9 (3.4-fold and 2.8-fold decrease at 24 h and 5-fold decrease at 72 h) compared with control conditions. Finally, the wound healing assay showed different scenarios during the several time points. Indeed, the wound closure rate was reduced in a dose-dependent manner (24 h: control 18%, G 50 mM 9%, 100 and 150 mM 8%; 48 h: control 26%, G 50 mM 20%, G 100 mM 13%, 150 mM 11%), following the treatment with three concentrations considered (50, 100, 150 mM). The results obtained in these experimental conditions highlight that glucose, at high concentrations, induced cell damage and corroborate the hypothesis that it could be involved in neurodegenerative diseases. Full article

Gravity in the head-to-toe direction, known as +Gz (G force), forces blood to pool in the lower body. Fighter pilots experience decreases in blood pressure when exposed to hypergravity in flight. Human centrifuge has been used to examine the G tolerance and anti-G straining maneuver (AGSM) techniques of military pilots. Some factors that may affect G tolerance have been reported but are still debated. The aim of this study was to investigate the physiological responses and anthropometric factors correlated with G tolerance. We retrospectively reviewed the training records of student pilots who underwent high G training. Variables were collected to examine their correlations with the outcome of 7.5G sustained for 15 s (7.5G profile). There were 873 trainees who underwent 7.5G profile training, 44 trainees (5.04%) could not sustain the test for 15 s. The group with a small heart rate (HR) increase (less than 10%) during the first 1–5 s of the 7.5G profile had a nearly ten-fold higher failing chance compared with the large HR increase group (adjusted odds ratio: 9.91; 95% confidence interval: 4.11–23.88). The chances of failure were inversely related to the HR increase percentage (p for trend <0.001). Factors, including body mass index, relaxed and straining G tolerance, and AGSM, were found to be negatively correlated with the outcome. Full article