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	<title>Aerospace medicine &#8211; Science</title>
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	<title>Aerospace medicine &#8211; Science</title>
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		<title>Machine Learning Spots Hidden Balance Loss at Moderate Altitudes Before Classic Hypoxia Symptoms Appear</title>
		<link>https://scienmag.com/machine-learning-spots-hidden-balance-loss-at-moderate-altitudes-before-classic-hypoxia-symptoms-appear/</link>
		
		<dc:creator><![CDATA[Teresa Odom]]></dc:creator>
		<pubDate>Fri, 16 Oct 2026 18:55:43 +0000</pubDate>
				<category><![CDATA[Science News]]></category>
		<category><![CDATA[Technology and Engineering]]></category>
		<category><![CDATA[Aerospace medicine]]></category>
		<category><![CDATA[altitude-related balance failure in pilots]]></category>
		<category><![CDATA[aviation hypoxia detection technology]]></category>
		<category><![CDATA[aviation safety]]></category>
		<category><![CDATA[bioengineering approaches to hypoxia detection]]></category>
		<category><![CDATA[center of pressure]]></category>
		<category><![CDATA[early detection of altitude-induced balance impairment]]></category>
		<category><![CDATA[Extra Trees]]></category>
		<category><![CDATA[feature selection]]></category>
		<category><![CDATA[hypoxia]]></category>
		<category><![CDATA[hypoxia symptom onset prediction]]></category>
		<category><![CDATA[impact of moderate altitude exposure on human balance]]></category>
		<category><![CDATA[Machine learning]]></category>
		<category><![CDATA[machine learning in aviation safety]]></category>
		<category><![CDATA[normobaric chamber]]></category>
		<category><![CDATA[normobaric hypoxia chamber experiments]]></category>
		<category><![CDATA[postural stability]]></category>
		<category><![CDATA[postural stability monitoring at high altitudes]]></category>
		<category><![CDATA[safety innovations in aerospace medicine]]></category>
		<category><![CDATA[sensory integration]]></category>
		<category><![CDATA[spatial disorientation]]></category>
		<category><![CDATA[subtle physiological changes before classic symptoms]]></category>
		<category><![CDATA[tree-based machine learning for physiological assessment]]></category>
		<category><![CDATA[XGBoost]]></category>
		<guid isPermaLink="false">https://scienmag.com/?p=288617</guid>

					<description><![CDATA[A new study combining statistics and machine learning shows that measurable postural instability emerges at simulated altitudes as low as 3,000 meters, well before classic hypoxia symptoms such as color vision loss appear.]]></description>
										<content:encoded><![CDATA[<p>Long before a pilot notices washed-out colors or feels lightheaded at altitude, the body&#8217;s balance machinery may already be quietly failing. That is the central message of a new study published in Frontiers in Bioengineering and Biotechnology, in which researchers combined classical statistics with tree-based machine learning to show that measurable postural instability emerges at simulated altitudes as low as 3,000 meters—well below the roughly 5,000-meter threshold at which conventional hypoxia symptoms such as color vision loss typically appear. The findings could reshape how aviation and aerospace safety systems detect hypoxia, one of the most insidious threats to crews operating in unpressurized or depressurized cabins.</p>
<p>The research team, led by Yasaman Baradaran of the BioSIS Lab at the University of Canberra together with colleagues at Embry-Riddle Aeronautical University, recruited thirty-one healthy young adults aged 19 to 23. Each participant was exposed to four simulated altitude conditions—sea level, 3,000 meters, 4,000 meters, and 5,000 meters—in a computer-controlled normobaric hypoxia chamber, with sessions spaced one week apart and delivered in randomized order. A normobaric chamber reduces the fraction of inspired oxygen at normal barometric pressure, a technique widely used in aviation and military training because it produces physiological effects equivalent to hypobaric exposure while avoiding the operational risks of actual altitude. Peripheral arterial oxygen saturation (SpO2) and heart rate were monitored continuously via fingertip pulse oximetry, and the statistically significant drop in SpO2 across altitude conditions confirmed that the hypoxic challenge was real and dose-dependent.</p>
<p>While seated in the chamber for a 30-minute acclimation period and then throughout testing, participants stood on a static force platform and completed eight standing tasks adapted from the modified Clinical Test of Sensory Integration and Balance protocol. These tasks were deliberately engineered to stress different sensory channels: normal stance, eyes closed, standing on foam, foam with eyes closed, foam with continuous side-to-side head movements to challenge the vestibular system, and the same combination with eyes closed, plus two Sharpened Romberg tandem heel-to-toe conditions with eyes open and closed. Each 30-second trial captured center-of-pressure (CoP) trajectories at 100 Hz, from which the team extracted fifteen sway measures spanning time-domain characteristics such as root-mean-square displacement, path length, sway area, and jerk, and frequency-domain descriptors such as total power, median frequency, and 95% power frequency, computed separately for anteroposterior, mediolateral, and resultant sway directions.</p>
<p>The statistical analysis told a nuanced story. Using Friedman tests with post hoc Wilcoxon signed-rank comparisons and Benjamini-Hochberg false discovery rate correction, the researchers found that no individual sway measure survived multiple-comparison correction—yet the nominal effects clustered strikingly in the foam-based and tandem tasks that place the greatest demands on multisensory integration. The strongest effect appeared in the condition requiring participants to stand on foam while rhythmically moving their heads, where sway total power rose markedly at 4,000 meters compared with both sea level and 5,000 meters. Elevated frequency-domain measures suggested faster, more energetically demanding corrective responses, while increased jerk on foam indicated reduced smoothness and stability. Together, these patterns imply that hypoxic participants needed more frequent and less efficient postural adjustments to stay upright when their sensory inputs were degraded.</p>
<p>Perhaps the most intriguing finding is that the relationship between altitude and sway is not linear. Moderate hypoxia at 3,000 to 4,000 meters increased sway variability and disrupted automatic postural control, but at 5,000 meters sway actually decreased under complex task conditions. The authors interpret this as a shift in motor strategy: moderate hypoxia appears to increase reliance on attentional resources, producing greater variability, whereas more severe hypoxia constrains motor output and suppresses exploratory movement—a stiffening that yields superficially stable but less adaptable control. This constrained strategy may be protective or energy-conserving under severe physiological stress, but it can mask subtle hypoxia-induced changes and reduce the flexibility needed for effective balance in operational settings. The confusion matrix from the machine learning analysis echoed this pattern, with the greatest misclassification occurring between sea level and 5,000 meters, including six sea-level observations predicted as 5,000 meters.</p>
<p>To move beyond the limits of univariate statistics, the team trained four tree-based ensemble classifiers—Random Forest, Gradient Boosting Decision Trees, Extra Trees, and XGBoost—to classify which altitude a participant had been exposed to, using 120 candidate features drawn from the fifteen sway measures across the eight standing conditions. Because the feature count nearly matched the number of observations, the researchers guarded against overfitting with a rigorous design: an 80:20 participant-level split into development and test sets, participant-grouped ten-fold nested cross-validation in which no participant ever appeared in both training and validation partitions, and feature ranking performed separately within every outer training fold so that held-out participants never influenced feature selection. Hyperparameters were tuned with randomized search and inner three-fold cross-validation, evaluating subsets from the single top-ranked feature up to the top thirty.</p>
<p>The optimized Extra Trees classifier achieved the best performance, reaching 70% four-class accuracy using 27 selected features. Extra Trees, or extremely randomized trees, build an ensemble of decision trees with randomized split thresholds, allowing the model to capture nonlinear relationships and complex interactions among sway variables while remaining robust to multicollinearity in high-dimensional data. The feature-importance rankings revealed that the most informative predictors came not from a single task but from a combination of normal stance, foam conditions, and tandem stance—spanning jerk, total power, median and 95% power frequencies in both anteroposterior and mediolateral directions. Notably, some tasks such as normal standing and tandem stance with eyes closed showed no significant effects in the univariate statistical analysis, yet proved sensitive to hypoxia in the multivariate classification. This discrepancy underscores a key methodological insight: individual sway measures may fail to reach statistical significance on their own, but their combined multivariate patterns still carry meaningful information about altitude-induced functional impairment.</p>
<p>The implications for aviation safety are substantial. Spatial disorientation remains a persistent contributor to pilot fatalities, and hypoxia is a known aggravating factor, particularly when visual references are degraded. Because postural control reflects the coordinated function of visual, vestibular, and somatosensory systems, objective sway measurement may serve as a sensitive early marker of hypoxic impairment—potentially flagging degradation at altitudes thousands of meters below where aviation regulators currently require supplemental oxygen. The authors suggest that integrating postural monitoring into operational safety systems could enhance early warning capabilities during unpressurized flight, cabin depressurization, or periods of high workload, informing decisions about supplemental oxygen use before perceptual symptoms such as color vision loss ever appear.</p>
<p>The study is not without limitations. The sample was modest and restricted to healthy young adults, limiting generalizability across age, sex, and occupational populations. The normobaric exposure paradigm, while physiologically equivalent in many respects, may not fully replicate hypobaric hypoxia encountered at true altitude, and the cross-sectional design could not capture adaptation or acclimatization effects across repeated exposures. The authors also note that model-agnostic interpretability tools such as SHAP values were not applied, and that conventional scalar sway features may miss the nonlinear temporal dynamics of postural control that fluctuation and recurrence quantification analyses could reveal. Future work with larger and more diverse cohorts, longitudinal designs, external validation, and integration with neurophysiological measures such as functional near-infrared spectroscopy or brain imaging will be needed before these findings can inform aviation procedures or oxygen requirements.</p>
<p>Even so, the study establishes a compelling proof of concept: hypoxia acts on the balance system in a multidimensional, stage-dependent way that only becomes fully visible when statistics and machine learning are used in tandem. By treating postural sway as a high-dimensional signature rather than a handful of scalar metrics, the approach detects subtle physiological changes that traditional group-level comparisons overlook. As machine learning continues to penetrate aerospace and biomedical monitoring, the humble force platform may become an unexpected sentinel—catching the silent onset of hypoxia in the wobble of a standing body long before the mind registers anything is wrong.</p>
<p><strong>Subject of Research:</strong> Effects of hypoxic altitude exposure on postural stability assessed with statistical analysis and machine learning classification of postural sway</p>
<p><strong>Article Title:</strong> Integrating machine learning and statistical techniques to evaluate postural stability during hypoxia</p>
<p><strong>Article References:</strong> Baradaran, Y., Shrestha, A., French, J., &amp; Ghahramani, M. (2026). Integrating machine learning and statistical techniques to evaluate postural stability during hypoxia. <em>Frontiers in Bioengineering and Biotechnology, 14</em>, Article 1886164. <a href="https://doi.org/10.3389/fbioe.2026.1886164" rel="noopener noreferrer">https://doi.org/10.3389/fbioe.2026.1886164</a></p>
<p><strong>Image Credits:</strong> AI Generated</p>
<p><strong>DOI:</strong> <a href="https://doi.org/10.3389/fbioe.2026.1886164" rel="noopener noreferrer">10.3389/fbioe.2026.1886164</a></p>
<p><strong>Keywords:</strong> hypoxia, postural stability, machine learning, Extra Trees, center of pressure, spatial disorientation, aviation safety, normobaric chamber, sensory integration, feature selection, XGBoost, aerospace medicine</p>
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		<post-id xmlns="com-wordpress:feed-additions:1">288617</post-id>	</item>
		<item>
		<title>FAA Physician-Scientist Joins UCF Aerospace Medicine Team</title>
		<link>https://scienmag.com/faa-physician-scientist-joins-ucf-aerospace-medicine-team/</link>
		
		<dc:creator><![CDATA[Ophelia Keating]]></dc:creator>
		<pubDate>Fri, 21 Aug 2026 21:20:55 +0000</pubDate>
				<category><![CDATA[Medicine]]></category>
		<category><![CDATA[aerospace medical education programs]]></category>
		<category><![CDATA[Aerospace medicine]]></category>
		<category><![CDATA[aerospace safety technology development]]></category>
		<category><![CDATA[astronaut health protection]]></category>
		<category><![CDATA[aviation health and safety policy]]></category>
		<category><![CDATA[commercial spaceflight health risks]]></category>
		<category><![CDATA[extreme environment medicine]]></category>
		<category><![CDATA[interdisciplinary collaboration in aerospace medicine]]></category>
		<category><![CDATA[long-duration space exploration health]]></category>
		<category><![CDATA[pilot certification and human factors]]></category>
		<category><![CDATA[space travel medical challenges]]></category>
		<category><![CDATA[UCF College of Medicine]]></category>
		<guid isPermaLink="false">https://scienmag.com/faa-physician-scientist-joins-ucf-aerospace-medicine-team/</guid>

					<description><![CDATA[Melchor Antuñano, an aerospace medicine specialist who spent 34 years helping shape aviation health and safety policy in the United States, has joined the University of Central Florida’s College of Medicine. His appointment places one of the field’s most experienced leaders at the center of UCF’s effort to build a major program focused on the [&#8230;]]]></description>
										<content:encoded><![CDATA[<p>Melchor Antuñano, an aerospace medicine specialist who spent 34 years helping shape aviation health and safety policy in the United States, has joined the University of Central Florida’s College of Medicine. His appointment places one of the field’s most experienced leaders at the center of UCF’s effort to build a major program focused on the medical challenges of flight, space travel and extreme environments. Antuñano will serve as a professor, chief technologist and medical innovation officer, bringing decades of experience in aviation physiology, pilot certification, human factors and aerospace safety to a university preparing for a new era of commercial spaceflight and long-duration exploration.</p>
<p>At UCF, Antuñano will help develop technologies and procedures designed to protect astronauts, pilots and passengers from the physical stresses of flight. He will also contribute to the creation of a master’s degree in aerospace medicine and a residency program for physicians who want to specialize in the health risks associated with aviation and space travel. His work will extend beyond the College of Medicine, with teaching and collaboration planned across UCF’s colleges. The goal is to connect medicine with engineering, computer science, psychology and other disciplines capable of solving problems that become increasingly complex as humans travel farther and remain in hostile environments longer.</p>
<p>Antuñano is also joining UCF’s Center for Aerospace and Extreme Environments Medicine, known as CASEEM. The multidisciplinary center is designed to investigate how the human body responds to conditions such as microgravity, radiation, isolation, extreme temperatures and restricted mobility. These stresses can affect nearly every major physiological system. Microgravity, for example, causes fluids to shift toward the upper body, changes cardiovascular regulation and accelerates bone and muscle loss. Radiation exposure may damage cells and increase long-term health risks, while isolation and disrupted sleep can affect cognition, mood and decision-making. Research addressing these challenges may also generate medical innovations for patients on Earth, including improved remote monitoring, compact diagnostic devices and new approaches to preventing tissue damage.</p>
<p>The center’s research will not be limited to astronauts. CASEEM is intended to serve people operating in other extreme environments, including military personnel, deep-sea explorers, mountain climbers and emergency responders. These populations face overlapping medical problems: limited access to care, environmental stress, delayed evacuation and the need to make rapid decisions with incomplete information. Aerospace medicine therefore depends on more than treating illness after it occurs. It emphasizes prevention, risk assessment, physiological monitoring and the design of systems that allow people to remain healthy and effective under pressure. Antuñano’s new role will focus on translating that knowledge into practical tools, clinical procedures and training programs.</p>
<p>Before becoming a physician, Antuñano had already begun working in emergency care and aviation. Born in Mexico City, he volunteered with the Red Cross and a national rescue squad as a paramedic, rescue worker and emergency medical technician. His early experiences taught him to improvise when equipment and resources were limited. He has recalled constructing a red emergency light for his car from a cooking pot because he could not afford a standard device. That resourcefulness later became a defining feature of his scientific career, influencing how he approached laboratory research, medical technology and operational safety.</p>
<p>During medical school at the National Autonomous University of Mexico, Antuñano encountered aviation medicine and began volunteering at the Mexican government’s National Center of Aviation Medicine. There, he studied aviation physiology, including the effects of altitude and the operation of pressure-related training systems. He also gained experience in human factors during aircraft accident investigations and in the medical certification of pilots. Aviation medicine examines how flight environments influence the body and how human limitations can interact with aircraft design, workload, fatigue and decision-making. The discipline is crucial because a pilot’s health can affect not only individual survival but also the safety of everyone aboard an aircraft.</p>
<p>Antuñano later pursued postgraduate training in the United States after discovering that Wright State University School of Medicine in Dayton, Ohio, offered the country’s only civilian aerospace medicine residency program at the time. He reportedly wrote to senior federal officials, including President Ronald Reagan, to learn where he could receive specialized training. At Wright State, he earned both a residency and a master’s degree in aerospace medicine. His graduate research examined a portable head-cooling system intended to protect Air Force personnel from heat exposure. To conduct the experiments, he created a makeshift thermal chamber in the kitchen of a residents’ lounge by combining heaters and other equipment. The project earned him the Aerospace Medical Association’s Young Investigator Award.</p>
<p>His research career continued with a two-year postdoctoral fellowship through the National Research Council at the U.S. Air Force School of Aerospace Medicine. He then worked as a contract scientist developing personal cooling technology for people wearing protective suits against nuclear, biological and chemical hazards. Such suits can prevent heat from escaping the body, creating a serious risk of heat stress during demanding operations. Cooling systems must therefore remove enough heat to protect the wearer without restricting movement or interfering with breathing, communication or protective performance. This combination of physiology, engineering and operational design became a foundation for Antuñano’s later work in aviation and aerospace safety.</p>
<p>Antuñano joined the Federal Aviation Administration in 1992 and held leadership positions in its Medical Education and Medical Certification divisions at the Civil Aerospace Medical Institute in Oklahoma City. The institute evaluates aviation health risks, trains physicians who conduct pilot examinations in the United States and approximately 90 other countries, and performs research in aerospace medicine and human factors. Antuñano became its director in 2001 and remained in the position until retiring earlier this year, making him the longest-serving director in the institute’s history and the longest-serving senior executive in the FAA’s history. At UCF, he will now apply that operational experience to a rapidly changing field in which private space companies, expanding commercial launch activity and plans for lunar and Martian missions are creating new medical questions. The university has also opened an aerospace medicine clinic that provides medical certification examinations for astronauts and pilots in the region. Antuñano says his next mission is to advance research while training future physicians, scientists and innovators who can turn extreme-environment medicine into safer exploration and better healthcare on Earth.</p>
<p><strong>Subject of Research</strong>: Aerospace medicine, aviation physiology, space medicine, human factors, medical innovation and health risks in extreme environments.</p>
<p><strong>Article Title</strong>: FAA Aerospace Medicine Leader Melchor Antuñano Joins UCF to Advance Human Health in Space and Extreme Environments</p>
<p><strong>Web References</strong>:<br />
https://med.ucf.edu/aerospace-medicine/<br />
https://med.ucf.edu/aerospace-medicine/caseem-center-for-aerospace/<br />
https://mediasvc.eurekalert.org/Api/v1/Multimedia/d4fcab99-5f02-4ef3-bacd-b9086bd35cfb/Rendition/low-res/Content/Public</p>
<p><strong>References</strong>: UCF College of Medicine; Federal Aviation Administration Civil Aerospace Medical Institute; Aerospace Medical Association.</p>
<p><strong>Image Credits</strong>: Photo by UCF College of Medicine.</p>
<p><strong>Keywords</strong>: Space medicine, space research, medical specialties, aviation, airplanes, spacecraft, aircraft, aerospace medicine.</p>
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