Results for “camera exposure time” — Page 13

NASA NTRSDate not supplied

Supervisory Control with Dual Tasking in Post G-Transition Vehicle Landings

BACKGROUND Landing during exploration spaceflight may consist of both planned automated supervisory control and unplanned crew override. Supervisory control, particularly when performed under cognitive load with additional monitoring tasks, is essential for ensuring overall mission success during landing contingencies. Evaluating performance in a relevant Human Landing System (HLS) supervisory landing task after long-duration microgravity exposure can help identify potential risks from human error and sensorimotor alterations. Adaptive changes in the sensorimotor system can manifest during g-transitions as spatial disorientation. Although training and landing aids facilitate successful landings despite disorientation, these adaptive changes may heighten cognitive demand, which must be considered in the landing strategy. It is important to characterize these effects as soon as possible following the G-transition while the sensorimotor system remains in a state of adaptive flux to inform appropriate countermeasures. METHODS A Multi-attribute Lunar Table Battery (MALTB) task was developed for an iOS tablet device to provide flexible crew testing and training capabilities in-flight and on the ground. Elements of the tablet task were derived from the Multi-Attribute Task Battery (MATB, Cegarra et al. 2020). The task requires crew members to study a map of a planned landing site and memorizing the terrain and surface landmarks to inform potential divert maneuvers during landing. The user will oversee a series of approaches through touchdown simulations on the tablet with an external camera view of the Lunar surface. The primary responsibility of the crew member will be to execute a divert if the guidance recommended site is erroneous (e.g., the guidance projected landing target is not within 10m of the planned landing site center), or the projected landing site is no longer suitable due to surface obstacles. Considering vehicle maneuverability and fuel reserves, the divert capabilities will diminish as the task progresses. In cases where a divert is initiated, a new landing target will need to be designated by the user and will be evaluated for the proximity to the original pre-planned site. A secondary operational monitoring task will challenge the user's cognitive reserve by requiring the user to maintain several gauges within acceptable limits and respond to a visual indicator while completing the landing approach. Outcome measures include distance from the planned landing site to the user-initiate divert landing location, ground slope at the new landing site, time to divert, the ability to accomplish the secondary monitoring tasks, and perceived workload. The tablet task is being evaluated in a ground-based study to determine the learning effect of first-time users. The tablet task will be utilized in a flight study to test performance multiple times postflight. Future potential testing in-flight have been identified for capsules with iOS tablet devices. Multi-attribute Lunar Table Battery Task MALTB comprises video footage of thirty distinct landing conditions. The landing scenarios feature various landing sites (n = 3), hazardous object sizes (n = 6), sun azimuth degrees (n = 4), camera modes (i.e., fixed or gimbaled), and navigation bias (i.e., true or false). Each seventy second trial uses a sixty-degree constant glideslope trajectory. The application architecture and layout include user identification setup and data storing, a guided walkthrough of the task and interface components, practice mode for task familiarization, and a modified Bedford workload scale administered following task completion. The time-based dependent measures are saved locally to the iOS Files application and post-processing scripts have been developed to evaluate the remaining measures of performance. RELEVANCE This project will deliver an operational demonstration of crew monitoring capability following spaceflight and identify potential deficits that may require remediation. Comparison of individual vestibular and cognitive changes with crew performance will help better characterize the landing risks associated with sensorimotor alterations. ACKNOWLEDGEMENTS: This project is funded by NASA’s Human Research Program Human Health Countermeasures Element. REFERENCES Cegarra J, Valery B, Avril E, Calmettes C, Navarro J (2020) OpenMATB: A Multi-Attribute Task Battery promoting task customization, software extensibility and experiment replicability. Behav Res Methods 52:1980-1990 doi: 10.3758/s13428-020-01364-w

Matthew McDonnell↗

NASA NTRS2011

A Miniaturized Video System for Monitoring Drosophila Behavior

Long-term spaceflight may induce a variety of harmful effects in astronauts, resulting in altered motor and cognitive behavior. The stresses experienced by humans in space - most significantly weightlessness (microgravity) and cosmic radiation - are difficult to accurately simulate on Earth. In fact, prolonged and concomitant exposure to microgravity and cosmic radiation can only be studied in space. Behavioral studies in space have focused on model organisms, including Drosophila melanogaster. Drosophila is often used due to its short life span and generational cycle, small size, and ease of maintenance. Additionally, the well-characterized genetics of Drosophila behavior on Earth can be applied to the analysis of results from spaceflights, provided that the behavior in space is accurately recorded. In 2001, the BioExplorer project introduced a low-cost option for researchers: the small satellite. While this approach enabled multiple inexpensive launches of biological experiments, it also imposed stringent restrictions on the monitoring systems in terms of size, mass, data bandwidth, and power consumption. Suggested parameters for size are on the order of 100 mm3 and 1 kg mass for the entire payload. For Drosophila behavioral studies, these engineering requirements are not met by commercially available systems. One system that does meet many requirements for behavioral studies in space is the actimeter. Actimeters use infrared light gates to track the number of times a fly crosses a boundary within a small container (3x3x40 mm). Unfortunately, the apparatus needed to monitor several flies at once would be larger than the capacity of the small satellite. A system is presented, which expands on the actimeter approach to achieve a highly compact, low-power, ultra-low bandwidth solution for simultaneous monitoring of the behavior of multiple flies in space. This also provides a simple, inexpensive alternative to the current systems for monitoring Drosophila populations in terrestrial experiments, and could be especially useful in field experiments in remote locations. Two practical limitations of the system should be noted: first, only walking flies can be observed - not flying - and second, although it enables population studies, tracking individual flies within the population is not currently possible. The system used video recording and an analog circuit to extract the average light changes as a function of time. Flies were held in a 5-cm diameter Petri dish and illuminated from below by a uniform light source. A miniature, monochrome CMOS (complementary metal-oxide semiconductor) video camera imaged the flies. This camera had automatic gain control, and this did not affect system performance. The camera was positioned 5-7 cm above the Petri dish such that the imaging area was 2.25 sq cm. With this basic setup, still images and continuous video of 15 flies at one time were obtained. To reduce the required data bandwidth by several orders of magnitude, a band-pass filter (0.3-10 Hz) circuit compressed the video signal and extracted changes in image luminance over time. The raw activity signal output of this circuit was recorded on a computer and digitally processed to extract the fly movement "events" from the waveform. These events corresponded to flies entering and leaving the image and were used for extracting activity parameters such as inter-event duration. The efficacy of the system in quantifying locomotor activity was evaluated by varying environmental temperature, then measuring the activity level of the flies.

Bhattacharya, Sharmila↗