The role of spatial acuity in a dynamic balancing task without gravitational cues

Vibrotactile feedback as a countermeasure for spatial disorientation

Spaceflight can make astronauts susceptible to spatial disorientation which is one of the leading causes of fatal aircraft accidents. In our experiment, blindfolded participants used a joystick to balance themselves while inside a multi-axis rotation device (MARS) in either the vertical or horizontal roll plane. On Day 1, in the vertical roll plane (Earth analog condition) participants could use gravitational cues and therefore had a good sense of their orientation. On Day 2, in the horizontal roll plane (spaceflight analog condition) participants could not use gravitational cues and rapidly became disoriented and showed minimal learning and poor performance. One potential countermeasure for spatial disorientation is vibrotactile feedback that conveys body orientation provided by small vibrating devices applied to the skin. Orientation-dependent vibrotactile feedback provided to one group enhanced performance in the spaceflight condition but the participants reported a conflict between the accurate vibrotactile cues and their erroneous perception of their orientation. Specialized vibrotactile training on Day 1 provided to another group resulted in significantly better learning and performance in the spaceflight analog task with vibrotactile cueing. In this training, participants in the Earth analog condition on Day 1 were required to disengage from the task of aligning with the gravitational vertical encoded by natural vestibular/somatosensory afference and had to align with randomized non-vertical directions of balance signaled by vibrotactile feedback. At the end of Day 2, we deactivated the vibrotactile feedback after both vibration-cued groups had practiced with it in the spaceflight analog condition. They performed as well as the group who did not have any vibrotactile feedback. We conclude that after appropriate training, vibrotactile orientation feedback augments dynamic spatial orientation and does not lead to any negative dependence.

Crash Prediction Using Deep Learning in a Disorienting Spaceflight Analog Balancing Task

Were astronauts forced to land on the surface of Mars using manual control of their vehicle, they would not have familiar gravitational cues because Mars’ gravity is only 0.38 g. They could become susceptible to spatial disorientation, potentially causing mission ending crashes. In our earlier studies, we secured blindfolded participants into a Multi-Axis Rotation System (MARS) device that was programmed to behave like an inverted pendulum. Participants used a joystick to stabilize around the balance point. We created a spaceflight analog condition by having participants dynamically balance in the horizontal roll plane, where they did not tilt relative to the gravitational vertical and therefore could not use gravitational cues to determine their position. We found 90% of participants in our spaceflight analog condition reported spatial disorientation and all of them showed it in their data. There was a high rate of crashing into boundaries that were set at ± 60° from the balance point. Our goal was to see whether we could use deep learning to predict the occurrence of crashes before they happened. We used stacked gated recurrent units (GRU) to predict crash events 800 ms in advance with an AUC (area under the curve) value of 99%. When we prioritized reducing false negatives we found it resulted in more false positives. We found that false negatives occurred when participants made destabilizing joystick deflections that rapidly moved the MARS away from the balance point. These unpredictable destabilizing joystick deflections, which occurred in the duration of time after the input data, are likely a result of spatial disorientation. If our model could work in real time, we calculated that immediate human action would result in the prevention of 80.7% of crashes, however, if we accounted for human reaction times (∼400 ms), only 30.3% of crashes could be prevented, suggesting that one solution could be an AI taking temporary control of the spacecraft during these moments.