Back to the future—revisiting Skylab data on ocular counter-rolling and motion sickness

In the early 1970s, nine astronauts participated in missions to the Skylab space station. During two preflight testing sessions at the Naval Aerospace Medical Research Laboratory in Pensacola, the amplitudes of their ocular counter-rolling (OCR) during body tilts were assessed to determine if their vestibular functions were within normal ranges. We recently re-evaluated this data to determine asymmetry of each astronaut’s OCR response and their OCR slope from sigmoid fits during static leftward and rightward body tilts, which we then compared with their Coriolis sickness susceptibility index (CSSI) on the ground, their motion sickness symptom scores during 0 g maneuvers in parabolic flight, and the severity of the symptoms of space motion sickness (SMS) they reported during their spaceflights. We arranged the astronauts in rank order for SMS severity based on the SMS symptoms they reported during spaceflight and the amount of anti-motion sickness medication they used. As previously reported, the OCR amplitudes of these astronauts were within the normal range. We determined that the OCR amplitudes were not correlated with SMS severity ranking, CSSI, or motion sickness symptoms experienced during parabolic flight. Indices of asymmetry in the OCR reflex were generally small and poorly correlated with SMS scores; however, the only subject with a high index of asymmetry also ranked highly for SMS. Although OCR slope, CSSI, and motion sickness symptoms induced during parabolic flight were each only moderately correlated with SMS severity ranking (rho = 0.41–0.44), a combined index that included all three parameters with equal weighting was significantly correlated with SMS severity ranking (rho = 0.71, p = 0.015). These results demonstrate the challenge of predicting an individual’s susceptibility to SMS by measuring a single test parameter in a terrestrial environment and from a limited sample size

A sensitive data analysis approach for detecting changes in dynamic postural stability

Understanding the mechanisms of instability can aid in reducing fall risk. As a sensitive measure of fall risk, the distance between the center of pressure (COP) and center of mass (COM) is currently assessed through discrete points assumed to represent physiological important fall mechanisms. However, it is unclear if these discrete points are appropriate measures of fall risk. Statistical parametric mapping (SPM) is a waveform analysis technique that removes this possibly biased a priori approach. Sixteen healthy young adults (8 males, 8 females; Age: 29 ± 3.6 years, Height: 1.7 ± 0.9 m, Mass: 75 ± 16 kg) performed two tasks that disturbed dynamic stability: voluntary stepping at different step lengths, and forward perturbations at different accelerations. COP-COM distance magnitudes were extracted during the first step in both tasks at discrete points typically assessed in previous research. Discrete point analysis (DPA) was performed on these discrete points and SPM analysis was completed on the COP-COM distance waveform. The results from the study found that SPM analysis identified equivalent significant differences to DPA and identified additional significant differences elsewhere in the COP-COM distance waveform that were not able to be detected by DPA. Two key advantages from using SPM: (1) reduction of possibly biased a priori selection, and (2) increased efficiency and reduced time-cost in data post-processing as inherent variability can limit the detection of discrete points resulting in identifying physiologically different discrete points across trials. This study suggests the use of SPM as a sensitive data analysis approach in detecting fall risk as an alternative to DPA