The effects of a 12-week yoga program on the CoP of military pilots before and after a flight emergency simulation using Biosignals Plux force platform
Restricted accessResearch articleFirst published online June, 2024
The effects of a 12-week yoga program on the CoP of military pilots before and after a flight emergency simulation using Biosignals Plux force platform
This study examined the effects of Ashtanga Vinyasa Yoga Supta on Center of Pressure (CoP) displacement in healthy student pilots, using the Biosignals Plux force platform, under the premise that yoga would lead to improvements in postural control responses. CoP response was analyzed by the Plux (Portugal) one-dimensional force platform. A total of 18 military pilots participated in this study. The pilots were in their Portuguese Air Force Academy course “Masters in Military Aeronautics: Aviator Pilot Specialist,” also called Tirocinium. Participants were randomly assigned to yoga classes (intervention group) or a waiting list (control group) and completed a flight emergency protocol in a flight simulator. CoP displacement was collected before and after all these maneuvers had been completed and both measures occurred before (baseline values) and after a 12-week yoga program. Although the differences observed between groups are not significant, after calculating the effect size, we can theorize that the intervention group maintains CoP displacement before and after flight and the control group has a higher CoP displacement after flight simulation. CoP information collected through noninvasive portable devices such as the Biosignals Plux force platform can relay important information quickly and easily. Knowing under what circumstances pilots are affected can then lead to development or enhancement of training strategies to improve those psychophysiological responses. In this study the effects, while not significant, are present, so it may be necessary to add more weeks of training to make the yoga program effective.
HaoCChengLGuoL, et al. Detection of unrecognized spatial disorientation: a theoretical perspective. Technol Health Care2022; 30(S1): 469–480.
2.
Gil-CabreraJAguileraJSanchez-TenaM, et al. Aviation-associated spatial disorientation and incidence of visual illusions survey in military pilots. Int J Aerosp Psychol2020; 31(1): 17–24.
3.
Appiah-KubiKOWrightWG. Vestibular training promotes adaptation of multisensory integration in postural control. Gait Posture2019; 73: 215–220.
4.
YangYPuFLvX, et al. Comparison of postural responses to galvanic vestibular stimulation between pilots and the general populace. Biomed Res Int2015; 2015: 567690.
5.
VillacísCFuertesWEscobarL, et al. A new real-time flight simulator for military training using mechatronics and cyber-physical system methods. London: IntechOpen, 2019, pp.73–90.
6.
PolakEŚlugajRGardzińskaA. Postural control and psychophysical state following of flight simulator session in novice pilots. Front Public Health2022; 10: 788612.
7.
StanneyKMKennedyRSDrexlerJM, et al. Motion sickness and proprioceptive aftereffects following virtual environment exposure. Appl Ergon1999; 30(1): 27–38.
8.
MinBCChungSCMinYK, et al. Psychophysiological evaluation of simulator sickness evoked by a graphic simulator. Appl Ergon2004; 35(6): 549–556.
9.
BaltzleyDRKennedyRSBerbaumKS, et al. The time course of postflight simulator sickness symptoms. Aviat Space Environ Med1989; 60(11): 1043–1048.
10.
UngsTJ. Simulator induced syndrome: evidence for long-term aftereffects. Aviat Space Environ Med1989; 60(3): 252–255.
11.
GeyerDJBiggsAT. The persistent issue of simulator sickness in naval aviation training. Aerosp Med Hum Perform2018; 89(4): 396–405.
12.
KennedyRSFowlkesJELilienthalMG. Postural and performance changes following exposures to flight simulators. Aviat Space Environ Med1993; 64(10): 912–920.
13.
KennedyRSStanneyKM. Postural instability induced by virtual reality exposure: development of a certification protocol. Int J Hum Comput Interact1996; 8(1): 25–47.
LiRPetersonNWalterHJ, et al. Real-time visual feedback about postural activity increases postural instability and visually induced motion sickness. Gait Posture2018; 65: 251–255.
16.
StoffregenTAHettingerLJHaasMW, et al. Postural instability and motion sickness in a fixed-based flight simulator. Hum Factors2000; 42(3): 458–469.
17.
BonnetCTFaugloireERileyMA, et al. Motion sickness preceded by unstable displacements of the center of pressure. Hum Mov Sci2006; 25(6): 800–820.
18.
ChardonnetJMirzaeiMMérienneF. Features of the postural sway signal as indicators to estimate and predict visually induced motion sickness in virtual reality. Int J Hum-Comput Int2017; 33(10): 771–785.
19.
PereiraN. A Realização Do Tirocínio Pela Academia Da Força Aérea Portuguesa. Trabalho de Investigação Individual – Curso De Promoção A Oficial Superior Da Força Aérea – Instituto De Estudos Superiores Militares. Lisbon: IUM Instituto Universitário Militar; c2019 [about 1 screen]. https://comum.rcaap.pt/bitstream/10400.26/12480/1/Cap%20Rodrigues%20Pereira.pdf (2009, 24January2023).
20.
SharmaL. Benefits of yoga in sports: a study. Int J Phys Educ Sports Health2015; 1: 30–32.
21.
Government of India. Explaining Yoga as a Sport. Ministry of Ayush. YOGA BLOG. Ministry of Ayush, Government of India. c2020 – [about 1 screen]. https://yoga.ayush.gov.in/blog?q=56 (2020, accessed 24 January 2023).
22.
ShambhuTKumarSDPrabhuP. Effect of practicing yoga on cervical vestibular evoked myogenic potential. Eur Arch Otorhinolaryngol2017; 274(10): 3811–3815.
23.
BalaguruPSSRD. Effect of pranayama training on vital capacity, respiratory pressures, and respiratory endurance of young healthy volunteers. Natl J Physiol Pharm Pharmacol2022; 12(2): 173–183.
24.
DesikacharKBragdonLBossartC. The yoga of healing: exploring yoga’s holistic model for health and well-being. Int J Yoga Therap2005; 15(1): 17–39.
25.
Le ClairKRiachC. Postural stability measures: what to measure and for how long. Clin Biomech1996; 11(3): 176–178.
26.
LinDSeolHNussbaumMA, et al. Reliability of COP-based postural sway measures and age-related differences. Gait Posture2008; 28(2): 337–342.
27.
DoyleRJHsiao-WeckslerETRaganBG, et al. Generalizability of center of pressure measures of quiet standing. Gait Posture2007; 25(2): 166–171.
28.
GrayVLIvanovaTDGarlandSJ. Reliability of center of pressure measures within and between sessions in individuals post-stroke and healthy controls. Gait Posture2014; 40(1): 198–203.
29.
GaulAO’KeeffeCDominguezMC, et al. Quantification of neural activity in FMR1 premutation carriers during a dynamic sway task using source localization. Annu Int Conf IEEE Eng Med Biol Soc2020; 2020: 2909–2912.
30.
ChenXPWangLJChangXQ, et al. Tai Chi and yoga for improving balance on one leg: a neuroimaging and biomechanics study. Front Neurol2021; 12: 746599.
31.
NiMMooneyKRichardsL, et al. Comparative impacts of Tai Chi, balance training, and a specially-designed yoga program on balance in older fallers. Arch Phys Med Rehabil2014; 95(9): 1620–1628.e30.
32.
PintoDPMoreiraPVSMenegaldoLL. Postural control adaptations in yoga single-leg support postures: comparison between practitioners and nonpractitioners. Motor Control2022; 26(3): 412–429.
33.
HoJTumkayaTAryalS, et al. Moving beyond P values: data analysis with estimation graphics. Nat Methods2019; 16(7): 565–566.
34.
McGoughJJFaraoneSV. Estimating the size of treatment effects: moving beyond p values. Psychiatry2009; 6(10): 21–29.
35.
Chmura KraemerHPeriyakoilVSNodaA. Kappa coefficients in medical research. Stat Med2002; 21(14): 2109–2129.
36.
LandisJRKochGG. The measurement of observer agreement for categorical data. Biometrics1977; 33(1): 159–174.
37.
LakensD. Calculating and reporting effect sizes to facilitate cumulative science: a practical primer for t-tests and ANOVAs. Front Psychol2013; 4: 863.
38.
SullivanGMFeinnR. Using effect size-or why the P value is not enough. J Grad Med Educ2012; 4(3): 279–282.
39.
PohlertT. PMCMR: calculate pairwise multiple comparisons of mean rank sums. [R package]. http://CRAN.R-project.org/package=PMCMR (2015, accessed 27 January 2023).
40.
R Core Team. R: a language and environment for statistical computing. (Version 4.1) [Computer software]. https://cran.r-project.org (2021, accessed 27 January 2023).
