Additive Sensory Noise Effects on Operator Performance in a Lunar Landing Simulation.

INTRODUCTION: Adding noise to a system to improve a weak signal's detectability is known as stochastic resonance (SR). SR has been shown to improve sensory perception and cognitive performance in certain individuals, but it is unknown whether this performance improvement can translate to meaningful macrocognitive enhancements in performance for complex, operational tasks.OBJECTIVE: We investigated human operator performance in a lunar landing simulation while applying auditory white noise and/or noisy galvanic vestibular stimulation.METHODS: We measured performance (N = 16 subjects) while completing simulation trials in our Aerospace Research Simulator. Trials were completed with and without the influence of auditory white noise, noisy galvanic vestibular stimulation, and both simultaneously in a multimodal fashion. Performance was observed holistically and across subdimensions of the task, which included flight skill and perception. Subjective mental workload was collected after completing four trials in each treatment.RESULTS: We did not find broad operator improvement under the influence of noise, but a significant interaction was identified between subject and noise treatment, indicating that some subjects were impacted by additive noise. We also found significant interactions between subject and noise treatment in performance subdimensions of flight skill and perception. We found no significant main effects on mental workload.CONCLUSIONS: This study investigated the utility of using additive sensory noise to induce SR for complex tasks. While SR has been shown to improve aspects of performance, our results suggest additive noise does not yield operational performance changes for a broad population, but specific individuals may be affected.Sherman SO, Shen Y-Y, Gutierrez-Mendoza D, Schlittenhart M, Watson C, Clark TK, Anderson AP. Additive sensory noise effects on operator performance in a lunar landing simulation. Aerosp Med Hum Perform. 2023; 94(10):770-779.

Training augmentation using additive sensory noise in a lunar rover navigation task.

Background: The uncertain environments of future space missions means that astronauts will need to acquire new skills rapidly; thus, a non-invasive method to enhance learning of complex tasks is desirable. Stochastic resonance (SR) is a phenomenon where adding noise improves the throughput of a weak signal. SR has been shown to improve perception and cognitive performance in certain individuals. However, the learning of operational tasks and behavioral health effects of repeated noise exposure aimed to elicit SR are unknown. Objective: We evaluated the long-term impacts and acceptability of repeated auditory white noise (AWN) and/or noisy galvanic vestibular stimulation (nGVS) on operational learning and behavioral health. Methods: Subjects (n = 24) participated in a time longitudinal experiment to access learning and behavioral health. Subjects were assigned to one of our four treatments: sham, AWN (55 dB SPL), nGVS (0.5 mA), and their combination to create a multi-modal SR (MMSR) condition. To assess the effects of additive noise on learning, these treatments were administered continuously during a lunar rover simulation in virtual reality. To assess behavioral health, subjects completed daily, subjective questionnaires related to their mood, sleep, stress, and their perceived acceptance of noise stimulation. Results: We found that subjects learned the lunar rover task over time, as shown by significantly lower power required for the rover to complete traverses (p < 0.005) and increased object identification accuracy in the environment (p = 0.05), but this was not influenced by additive SR noise (p = 0.58). We found no influence of noise on mood or stress following stimulation (p > 0.09). We found marginally significant longitudinal effects of noise on behavioral health (p = 0.06) as measured by strain and sleep. We found slight differences in stimulation acceptability between treatment groups, and notably nGVS was found to be more distracting than sham (p = 0.006). Conclusion: Our results suggest that repeatedly administering sensory noise does not improve long-term operational learning performance or affect behavioral health. We also find that repetitive noise administration is acceptable in this context. While additive noise does not improve performance in this paradigm, if it were used for other contexts, it appears acceptable without negative longitudinal effects.

Effects of additive sensory noise on cognition.

Background: Adding noise to a system to improve a weak signal's throughput is known as stochastic resonance (SR). SR has been shown to improve sensory perception. Some limited research shows noise can also improve higher order processing, such as working memory, but it is unknown whether SR can broadly improve cognition. Objective: We investigated cognitive performance while applying auditory white noise (AWN) and/or noisy galvanic vestibular stimulation (nGVS). Methods: We measured cognitive performance (n = 13 subjects) while completing seven tasks in the cognition test battery (CTB). Cognition was assessed with and without the influence of AWN, nGVS, and both simultaneously. Performance in speed, accuracy, and efficiency was observed. A subjective questionnaire regarding preference for working in noisy environments was collected. Results: We did not find broad cognitive performance improvement under the influence of noise (p > 0.1). However, a significant interaction was found between subject and noise condition for accuracy (p = 0.023), indicating that some subjects exhibited cognitive changes with the addition of noise. Across all metrics, noisy environment preference may trend to be a potential indicator of whether subjects will exhibit SR cognitive benefits with a significant predictor in efficiency (p = 0.048). Conclusion: This study investigated using additive sensory noise to induce SR in overall cognition. Our results suggest that using noise to improve cognition is not applicable for a broad population; however, the effect of noise differs across individuals. Further, subjective questionnaires may be a means to identify which individuals are sensitive to SR cognitive benefits, but further investigation is needed.

Performance Risks During Surface Extravehicular Activity and Potential Mitigation Using Multimodal Displays.

BACKGROUND: Surface extravehicular activity (sEVA) will be a critical component of future human missions to the Moon. sEVA presents novel risks to astronaut crews not associated with microgravity operations due to fundamental differences in task demands, physiology, environment, and operations of working on the lunar surface. Multimodal spacesuit informatics displays have been proposed as a method of mitigating sEVA risk by increasing operator autonomy.METHODS: A formalized literature review was conducted. In total, 95 journal articles, conference papers, and technical reports were included. Characteristics of U.S. spacesuits were reviewed, ranging from the Apollo A7L to the xEMU Z-2.5. Multimodal display applications were then reviewed and assessed for their potential in aiding sEVA operations.RESULTS: Through literature review 25 performance impairments were identified. Performance impairments caused by the spacesuit represented the greatest number of sEVA challenges. Multimodal displays were mapped to impairments and approximately 36% of performance impairments could be aided by using display interfaces.DISCUSSION: Multimodal displays may provide additional benefits for alleviating performance impairments during sEVA. Utility of multimodal displays may be greater in certain performance impairment domains, such as spacesuit-related impairments.Zhang JY, Anderson AP. Performance risks during surface extravehicular activity and potential mitigation using multimodal displays. Aerosp Med Hum Perform. 2023; 94(1):34-41.

Modeling the Design Characteristics of Woven Textile Electrodes for long-Term ECG Monitoring.

An electrocardiograph records the periodic voltage generated by the heart over time. There is growing demand to continuously monitor the ECG for proactive health care and human performance optimization. To meet this demand, new conductive textile electrodes are being developed which offer an attractive alternative to adhesive gel electrodes but they come with their own challenges. The key challenge with textile electrodes is that the relationship between the manufacturing parameters and the ECG measurement is not well understood, making design an iterative process without the ability to prospectively develop woven electrodes with optimized performance. Here we address this challenge by applying the traditional skin-electrode interface circuit model to woven electrodes by constructing a parameterized model of the ECG system. Then the unknown parameters of the system are solved for with an iterative MATLAB optimizer using measured data captured with the woven electrodes. The results of this novel analysis confirm that yarn conductivity and total conductive area reduce skin electrode impedance. The results also indicate that electrode skin pressure and moisture require further investigation. By closing this gap in development, textile electrodes can be better designed and manufactured to meet the demands of long-term ECG capture.

Estimation of Subjectively Reported Trust, Mental Workload, and Situation Awareness Using Unobtrusive Measures.

OBJECTIVE: We use a set of unobtrusive measures to estimate subjectively reported trust, mental workload, and situation awareness (henceforth "TWSA"). BACKGROUND: Subjective questionnaires are commonly used to assess human cognitive states. However, they are obtrusive and usually impractical to administer during operations. Measures derived from actions operators take while working (which we call "embedded measures") have been proposed as an unobtrusive way to obtain TWSA estimates. Embedded measures have not been systematically investigated for each of TWSA, which prevents their operational utility. METHODS: Fifteen participants completed twelve trials of spaceflight-relevant tasks while using a simulated autonomous system. Embedded measures of TWSA were obtained during each trial and participants completed TWSA questionnaires after each trial. Statistical models incorporating our embedded measures were fit with various formulations, interaction effects, and levels of personalization to understand their benefits and improve model accuracy. RESULTS: The stepwise algorithm for building statistical models usually included embedded measures, which frequently corresponded to an intuitive increase or decrease in reported TWSA. Embedded measures alone could not accurately capture an operator's cognitive state, but combining the measures with readily observable task information or information about participants' backgrounds enabled the models to achieve good descriptive fit and accurate prediction of TWSA. CONCLUSION: Statistical models leveraging embedded measures of TWSA can be used to accurately estimate responses on subjective questionnaires that measure TWSA. APPLICATION: Our systematic approach to investigating embedded measures and fitting models allows for cognitive state estimation without disrupting tasks when administering questionnaires would be impractical.

A Qualitative Investigation of Space Exploration Medical Evacuation Risks.

INTRODUCTION: Exploration beyond low Earth orbit requires innovative solutions to support the crew medically, especially as the opportunity for timely evacuation to Earth diminishes. This includes assessing the risks and benefits that a complicated medical evacuation (MEDEVAC) poses to the injured crewmember, the crew, and the mission. This qualitative study identifies common MEDEVAC risk assessment principles used in spaceflight and other extreme environments to better inform future risk assessment tools and exploration mission concepts.METHODS: Semistructured interviews were conducted with subject matter experts in spaceflight and analog domains, including polar operations, undersea operations, combat medicine, and mountaineering. Transcripts were analyzed using the qualitative method of Thematic Analysis with the technique of consensus, co-occurrence, and comparison.RESULTS: Subject matter experts described 18 themes divided into two main categories: Primary Risk Considerations (e.g., crew, mission, resources, time) and Contributing Factors (e.g., psychological considerations, medical preparation, politics).DISCUSSION: Primary Risk Considerations can assess MEDEVAC risk across mission phases, with Contributing Factors acting as premission tools to adjust those risks. Inter- and intracategory connections identified medical support considerations, MEDEVAC support considerations, and philosophy as the most impactful Contributing Factors. Medical support considerations, psychological considerations, and political considerations were found to have unique aspects given the distances and societal impact of exploration vs. low Earth orbit spaceflight. The Contributing Factor theme of decision making was determined to be unique due to its impacts across both categories. These findings expand current considerations and are important inputs for exploration mission MEDEVAC Concepts of Operations.Almand A, Ko SY, Anderson A, Keller RJ, Zero M, Anderson AP, Laws JM, Lehnhardt K, Easter BD. A qualitative investigation of space exploration medical evacuation risks. Aerosp Med Hum Perform. 2023; 94(12):875-886.

Challenges in Quantifying Heel-Lift During Spacesuit Gait.

INTRODUCTION: Heel-lift is a subjectively reported fit issue in planetary spacesuit boot prototypes that has not yet been quantified. Inertial measurement units (IMUs) could quantify heel-lift but are susceptible to integration drift. This work evaluates the use of IMUs and drift-correction algorithms, such as zero-velocity (ZVUs) and zero-position updates (ZPUs), to quantify heel-lift during spacesuited gait.METHODS: Data was originally collected by Fineman et al. in 2018 to assess lower body relative coordination in the spacesuit. IMUs were mounted on the spacesuit lower legs (SLLs) and spacesuit operator's shank as three operators walked on a level walkway in three spacesuit padding conditions. Discrete wavelet transforms were used to identify foot-flat phase and heel-off for each step. Differences in heel-off timepoints were calculated in each step as a potential indicator of heel-lift, with spacesuit-delayed heel-off suggesting heel-lift. Average drift rates were estimated prior to and after applying ZVUs and ZPUs.RESULTS: Heel-off timepoint differences showed instances of spacesuit-delayed heel-off and instances of operator-delayed heel-off. Drift rates after applying ZVUs and ZPUs suggested an upper time bound of 0.03 s past heel-off to measure heel-lift magnitude with an accuracy of 1 cm.DISCUSSION: Results suggest that IMUs may not be appropriate for quantifying the presence and magnitude of heel lift. Operator-delayed heel-off suggests that the SLL may be expanding prior to heel-off, creating a false vertical acceleration signal interpreted by this study to be spacesuit heel-off. Quantifying heel-off will therefore require improvements in IMU mounting to mitigate the effects of SLL, or alternative sensor technologies.Boppana A, Priddy ST, Stirling L, Anderson AP. Challenges in quantifying heel-lift during spacesuit gait. Aerosp Med Hum Perform. 2022; 93(8):643-648.

Utility of the Full ECG Waveform for Stress Classification.

The detection of psychological stress using the electrocardiogram (ECG) signal is most commonly based on the detection of the R peak-the most prominent part of the ECG waveform-and the heart rate variability (HRV) measurements derived from it. For stress detection algorithms focused on short-duration time windows, there is potential benefit in including HRV features derived from the detection of smaller peaks within the ECG waveform: the P, Q, S, and T waves. However, the potential drawback of using these small peaks is their smaller magnitude and subsequent susceptibility to noise, making them more difficult to reliably detect. In this work, we demonstrate the potential benefits of including smaller waves within binary stress classification using a pre-existing data set of ECG recordings from 57 participants (aged 18-40) with a self-reported fear of spiders during exposure to videos of spiders. We also present an analysis of the performance of an automated peak detection algorithm and the reliability of detection for each of the smaller parts of the ECG waveform. We compared two models, one with only R peak features and one with small peak features. They were similar in precision, recall, F1, area under ROC curve (AUC), and accuracy, with the greatest differences less than the standard deviations of each metric. There was a significant difference in the Akaike Information Criterion (AIC), which represented the information loss of the model. The inclusion of novel small peak features made the model 4.29×1028 times more probable to minimize the information loss, and the small peak features showed higher regression coefficients than the R peak features, indicating a stronger relationship with acute psychological stress. This difference and further analysis of the novel features suggest that small peak intervals could be indicative of independent processes within the heart, reflecting a psychophysiological response to stress that has not yet been leveraged in stress detection algorithms.

The influence of perceived stress on the human microbiome.

OBJECTIVE: Microbial dysbiosis, a shift from commensal to pathogenic microbiota, is often associated with mental health and the gut-brain axis, where dysbiosis in the gut may be linked to dysfunction in the brain. Many studies focus on dysbiosis induced by clinical events or traumatic incidents; however, many professions in austere or demanding environments may encounter continuously compounded stressors. This study seeks to explore the relationship between microbial populations and stress, both perceived and biochemical. RESULTS: Eight individuals enrolled in the study to provide a longitudinal assessment of the impact of stress on gut health, with four individuals providing enough samples for analysis. Eleven core microbial genera were identified, although the relative abundance of these genera and other members of the microbial population shifted over time. Although our results indicate a potential relationship between perceived stress and microbial composition of the gut, no association with biochemical stress was observed. Increases in perceived stress seem to elucidate a change in potentially beneficial Bacteroides, with a loss in Firmicutes phyla. This shift occurred in multiple individuals, whereas using cortisol as a stress biomarker showed contradictory responses. These preliminary data provide a potential mechanism for gut monitoring, while identifying targets for downstream modulation.

Isolation and confinement due to the COVID-19 pandemic: Lessons for human spaceflight.

Background: Astronauts live and work in isolated, confined, extreme (ICE) environments that create both high stress and the need for high performance. The COVID-19 pandemic created ICE-like conditions across the globe by confining people to their homes under the ever-present threat of disease. Our goal is to understand the impact of prior experience in ICE on coping, using the pandemic as a pseudo space analog environment. Methods: We administered a survey three times with 7 days between administrations. A total of 82 participants completed all three survey sessions, and these participants were divided into three groups for analysis. The first group is those with prior experience in an ICE environment (n = 17; 7F/10 M), the second is those aged 30-55 with a master's or doctoral degree and without prior experience (n = 22; 10F/12 M), and the third is the general population (n = 43; 27F/16 M). Linear mixed models were used for statistical analysis of the results, given the unequal sample sizes. Results: The experienced group did not show healthier mental health scores than the astronaut-like group, but both groups displayed higher scores than the general population. However, work productivity scores for the experienced group were higher on average than the other two groups. Discussion: Results suggest that prior experience in ICE may improve the capability to maintain productivity-corresponding to the idea of resilience. However, experience may not improve mental health maintenance, suggesting that other approaches are needed to prepare astronauts for the mental health stressors of long-duration exploration missions.

A machine learning approach to identify stochastic resonance in human perceptual thresholds.

BACKGROUND: Stochastic resonance (SR) is achieved when a faint signal is improved with the addition of the appropriate amount of white noise. Perceptual thresholds are expected to follow a characteristic performance improvement curve as a function of the white noise level added (i.e., thresholds are reduced with an optimal amount of added white noise, beyond which excessive white noise is no longer beneficial). Since SR exhibition in perceptual thresholds is defined by a shape rather than a statistical difference, the presence of SR is typically identified qualitatively. The current state-of-the-art is for blinded human judges to categorize the presence of SR by visually examining data. While categorizations are made with subject data intermixed within a balanced, simulated dataset, which accounts for false positives, this method is still subjective and prone to human error. NEW METHOD: We use a logistic regression (LR) trained on engineered features in order to quantitatively classify exhibition of SR. The LR was trained on datasets simulated from a model for SR performance enhancement. RESULTS: We implemented the algorithmic classification process in 6 perceptual threshold test cases, informed by the literature and parameters were defined by experimental subject data. Comparison to Existing Method(s): We report algorithmic classifications of SR exhibition, considering the 6 test cases, that outperform existing subjective methods in accuracy (p < 0.05). CONCLUSIONS: We demonstrate that algorithmic classification can effectively identify SR in perceptual thresholds, providing a rigorous, objective, and quantitative approach to identifying the presence of SR.

Side-by-Side Comparison of Human Perception and Performance Using Augmented, Hybrid, and Virtual Reality.

Alternative reality (XR) technologies, including physical, augmented, hybrid, and virtual reality, offer ways for engineered spaces to be evaluated. Traditionally, practitioners (such as those designing spacecraft habitats) have relied on physical mockups to perform such design evaluations, but digital XR technologies present several streamlining advantages over their physical counterparts. These digital environments vary in their level of virtuality, and consequently have different effects on human perception and performance, with respect to a completely physical mockup environment. To date, very little has been done to characterize and quantify such differences in human perception and performance across XR environments of equal fidelity for the same end application. Here, we show that perception and performance in the virtual reality environment most closely mirror those in the physical reality environment, as measured through volumetric assessment and functional task experiments. These experiments required subjects to judge the dimensions of 3D objects and perform operational tasks presented via checklists. Our results highlight the potential for virtual reality systems to accelerate the iterative design of engineered spaces relative to the use of physical mockups, while preserving the human perception and performance characteristics of a completely physical environment. These findings also elucidate specific advantages and disadvantages to specific digital XR technologies with respect to one another and the physical reality baseline. Practitioners may inform their selection of an XR modality for their specific end application based on this comparative analysis, as it contextualizes the niche for each technology in the realm of iterative design for engineered spaces.

Detection of the Complete ECG Waveform with Woven Textile Electrodes.

Wearable physiological monitoring systems are becoming increasingly prevalent in the push toward autonomous health monitoring and offer new modalities for playful and purposeful interaction within human computer interaction (HCI). Sensing systems that can be integrated into garments and, therefore, daily activities offer promising pathways toward ubiquitous integration. The electrocardiogram (ECG) signal is commonly monitored in healthcare and is increasingly utilized as a method of determining emotional and psychological state; however, the complete ECG waveform with the P, Q, R, S, and T peaks is not commonly used, due to the challenges associated with collecting the full waveform with wearable systems. We present woven textile electrodes as an option for garment-integrated ECG monitoring systems that are capable of capturing the complete ECG waveform. In this work, we present the changes in the peak detection performance caused by different sizes, patterns, and thread types with data from 10 human participants. These testing results provide empirically-derived guidelines for future woven textile electrodes, present a path forward for assessing design decisions, and highlight the importance of testing novel wearable sensor systems with more than a single individual.

Dynamic foot morphology explained through 4D scanning and shape modeling.

A detailed understanding of foot morphology can enable the design of more comfortable and better fitting footwear. However, foot morphology varies widely within the population, and changes dynamically as the foot is loaded during stance. This study presents a parametric statistical shape model from 4D foot scans to capture both the inter- and intra-individual variability in foot morphology. Thirty subjects walked on a treadmill while 4D scans of their right foot were taken at 90 frames-per second during stance phase. Each subject's height, weight, foot length, foot width, arch length, and sex were also recorded. The 4D scans were all registered to a common high-quality foot scan, and a principal component analysis was done on all processed 4D scans. Elastic-net linear regression models were built to predict the principal component scores, which were then inverse transformed into 4D scans. The best performing model was selected with leave-one-out cross-validation. The chosen model predicts foot morphology across stance phase with a root-mean-square error of 5.2 ± 2.0 mm and a mean Hausdorff distance of 25.5 ± 13.4 mm. This study shows that statistical shape modeling can be used to predict dynamic changes in foot morphology across the population. The model can be used to investigate and improve foot-footwear interaction, allowing for better fitting and more comfortable footwear.

Proposed mechanism for reduced jugular vein flow in microgravity.

Internal jugular flow is reduced in space compared with supine values, which can be associated with internal jugular vein (IJV) thrombosis. The mechanism is unknown but important to understand to prevent potentially serious vein thromboses on long duration flights. We used a novel, microgravity-focused numerical model of the cranial vascular circulation to develop hypotheses for the reduced flow. This model includes the effects of removing hydrostatic gradients and tissue compressive forces - unique effects of weightlessness. The IJV in the model incorporates sensitivity to transmural pressure across the vein, which can dramatically affect resistance and flow in the vein. The model predicts reduced IJV flow in space. Although tissue weight in the neck is reduced in weightlessness, increasing transmural pressure, this is more than offset by the reduction in venous pressure produced by the loss of hydrostatic gradients and tissue pressures throughout the body. This results in a negative transmural pressure and increased IJV resistance. Unlike the IJV, the walls of the vertebral plexus are rigid; transmural pressure does not affect its resistance and so its flow increases in microgravity. This overall result is supported by spaceflight measurements, showing reduced IJV area inflight compared with supine values preflight. Significantly, this hypothesis suggests that interventions that further decrease internal IJV pressure (such as lower body negative pressure), which are not assisted by other drainage mechanisms (e.g. gravity), might lead to stagnant flow or IJV collapse with reduced flow, which could increase rather than decrease the risk of venous thrombosis.

Galvanic Vestibular Stimulation Produces Cross-Modal Improvements in Visual Thresholds.

BACKGROUND: Stochastic resonance (SR) refers to a faint signal being enhanced with the addition of white noise. Previous studies have found that vestibular perceptual thresholds are lowered with noisy galvanic vestibular stimulation (i.e., "in-channel" SR). Auditory white noise has been shown to improve tactile and visual thresholds, suggesting "cross-modal" SR. OBJECTIVE: We investigated galvanic vestibular white noise (nGVS) (n = 9 subjects) to determine the cross-modal effects on visual and auditory thresholds. METHODS: We measured auditory and visual perceptual thresholds of human subjects across a swath of different nGVS levels in order to determine if some individual-subject determined best nGVS level elicited a reduction in thresholds as compared the no noise condition (sham). RESULTS: We found improvement in visual thresholds (by an average of 18%, p = 0.014). Subjects with higher (worse) visual thresholds with no stimulation (sham) improved more than those with lower thresholds (p = 0.04). Auditory thresholds were unchanged by vestibular stimulation. CONCLUSION: These results are the first demonstration of cross-modal improvement with galvanic vestibular stimulation, indicating galvanic vestibular white noise can produce cross-modal improvements in some sensory channels, but not all.

Woven electrocardiogram (ECG) electrodes for health monitoring in operational environments.

Electrical signals produced within the human body can reveal information about a wide variety of physiological processes including physical activity, cardiac health, and psychological state. The industry standard for physiological signal detection is the use of adhesive electrodes that stick onto the skin. These electrodes can irritate the skin over long periods of time and are not reusable, making them a challenge for use in operational environments. Further, these electrodes often require gel to improve signal transduction, leading to changes in signal quality as these gels dry over time. Wearable sensors for operational environments should be comfortable, unobtrusive, and non-stigmatizing while maintaining signal quality high enough to allow the detection of health states. Here, we present the development and test of a set of woven textile electrodes of 8 different sizes for chest-mounted, 3-lead electrocardiogram (ECG) monitoring. Ten male subjects were tested with each of the woven electrode sizes and with one set of adhesive electrodes. A derived performance metric and signal-to-noise ratio were calculated for each set of electrodes for comparison between them. The smallest sized electrodes were found to be least effective, while the 6th of the 8 sizes were found to be most effective.

Textile Electrocardiogram (ECG) Electrodes for Wearable Health Monitoring.

Wearable health-monitoring systems should be comfortable, non-stigmatizing, and able to achieve high data quality. Smart textiles with electronic elements integrated directly into fabrics offer a way to embed sensors into clothing seamlessly to serve these purposes. In this work, we demonstrate the feasibility of electrocardiogram (ECG) monitoring with sewn textile electrodes instead of traditional gel electrodes in a 3-lead, chest-mounted configuration. The textile electrodes are sewn with silver-coated thread in an overlapping zig zag pattern into an inextensible fabric. Sensor validation included ECG monitoring and comfort surveys with human subjects, stretch testing, and wash cycling. The electrodes were tested with the BIOPAC MP160 ECG data acquisition module. Sensors were placed on 8 subjects (5 males and 3 females) with double-sided tape. To detect differences in R peak detectability between traditional and sewn sensors, effect size was set at 10% of a sample mean for heart rate (HR) and R-R interval. Paired student's t-tests were run between adhesive and sewn electrode data for R-R interval and average HR, and a Wilcoxon signed-rank test was run for comfort. No statistically significant difference was found between the traditional and textile electrodes (R-R interval: t = 1.43, p > 0.1; HR: t = - 0.70, p > 0.5; comfort: V = 15,p > 0.5).

Portable Autorefractors for Detecting Axial Length Changes in Space.

INTRODUCTION: We evaluated the reproducibility of two portable, self-administered autorefractors (Netra and SVOne Pro) to assess the time course of visual changes on the ISS. METHODS: We measured cycloplegic refractive error at 5 visits at least a week apart in 13 subjects (6 women, 7 men, 30 ± 9 yr) using both devices seated and also prone with lower body positive pressure (LBPP) applied. Axial length was measured with an optical biometer. Subjects completed a questionnaire on device preferences. RESULTS: The SVOne seated intrasession reproducibility coefficient (RPC) was 0.37 diopters (D), while the Netra's was 0.41 D. Intersession seated results were: RPC = 0.67 D for the SVOne and RPC = 0.54 D for the Netra. The average seated to prone LBPP differences were significantly different from zero for both the SVOne and Netra. The SVOne was preferred in four out of five categories on the questionnaire and took half the time to complete a measurement set compared to the Netra. DISCUSSION: Users preferred the SVOne and it took less time. An SVOne refraction change of 0.67 D from baseline would happen by chance less than 5% of the time. If multiple separate measurements were taken, the detection limit could be reduced (e.g., three repeated measurements could reduce it to 0.38 D). Since astronauts with visual changes show spherical equivalent changes of 0.5 to 1.0 D, in-flight autorefractors could help determine the time course of refractive changes in space from which changes in axial length could be inferred.Masterova KS, Anderson AP, Cowan DR, Fellows AM, Zegans ME, Buckey JC. Portable autorefractors for detecting axial length changes in space. Aerosp Med Hum Perform. 2018; 89(8):724-730.