Adaptation of Postural Sway in a Standing Position during Tilted Video Viewing Using Virtual Reality: A Comparison between Younger and Older Adults
Abstract
:1. Introduction
2. Materials and Methods
2.1. Study Design and Participants
2.2. Assessment of Physical Activity
2.3. Study Setting
2.4. Assessment of Center of Gravity
2.5. Statistical Analysis
3. Results
4. Discussion
5. Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Acknowledgments
Conflicts of Interest
References
- James, S.L.; Lucchesi, L.R.; Bisignano, C.; Castle, C.D.; Dingels, Z.V.; Fox, J.T.; Hamilton, E.B.; Henry, N.J.; Krohn, K.J.; Liu, Z.; et al. The global burden of falls: Global, regional and national estimates of morbidity and mortality from the Global Burden of Disease Study 2017. Inj. Prev. 2020, 26 (Suppl. 1), i3–i11. [Google Scholar] [CrossRef]
- Thomas, E.; Battaglia, G.; Patti, A.; Brusa, J.; Leonardi, V.; Palma, A.; Bellafiore, M. Physical activity programs for balance and fall prevention in elderly: A systematic review. Medicine 2019, 98, e16218. [Google Scholar] [CrossRef]
- Marquina, M.; Lorenzo-Calvo, J.; Rivilla-García, J.; García-Aliaga, A.; Refoyo Román, I. Effects on Strength, Power and Speed Execution Using Exercise Balls, Semi-Sphere Balance Balls and Suspension Training Devices: A Systematic Review. Int. J. Environ. Res. Public Health 2021, 18, 1026. [Google Scholar] [CrossRef]
- Guadagnoli, M.A.; Lee, T.D. Challenge point: A framework for conceptualizing the effects of various practice conditions in motor learning. J. Mot. Behav. 2004, 36, 212–224. [Google Scholar] [CrossRef]
- McCrea, P.H.; Eng, J.J.; Hodgson, A.J. Saturated muscle activation contributes to compensatory reaching strategies after stroke. J. Neurophysiol. 2005, 94, 2999–3008. [Google Scholar] [CrossRef]
- Sokołowska, B. Impact of Virtual Reality Cognitive and Motor Exercises on Brain Health. Int. J. Environ. Res. Public Health 2023, 20, 4150. [Google Scholar] [CrossRef]
- Bleakley, C.M.; Charles, D.; Porter-Armstrong, A.; McNeill, M.D.J.; McDonough, S.M.; McCormack, B. Gaming for health: A systematic review of the physical and cognitive effects of interactive computer games in older adults. J. Appl. Gerontol. 2015, 34, NP166–NP189. [Google Scholar] [CrossRef]
- Vázquez, F.L.; Otero, P.; García-Casal, J.A.; Blanco, V.; Torres, J.; Arrojo, M. Efficacy of video game-based interventions for active aging. a systematic literature review and meta-analysis. PLoS ONE 2018, 13, e0208192. [Google Scholar] [CrossRef]
- Soltani, P.; Andrade, R. The Influence of Virtual Reality Head-Mounted Displays on Balance Outcomes and Training Paradigms: A Systematic Review. Front. Sports Act. Living 2021, 2, 531535. [Google Scholar] [CrossRef]
- Urabe, Y.; Fukui, K.; Harada, K.; Tashiro, T.; Komiya, M.; Maeda, N. The Application of Balance Exercise Using Virtual Reality for Rehabilitation. Healthcare 2022, 10, 680. [Google Scholar] [CrossRef]
- Delgado, F.; Der Ananian, C. The Use of Virtual Reality Through Head-Mounted Display on Balance and Gait in Older Adults: A Scoping Review. Games Health J. 2021, 10, 2–12. [Google Scholar] [CrossRef]
- Puszczalowska-Lizis, E.; Bujas, P.; Jandzis, S.; Omorczyk, J.; Zak, M. Inter-gender differences of balance indicators in persons 60–90 years of age. Clin. Interv. Aging 2018, 13, 903–912. [Google Scholar] [CrossRef]
- Espinoza-Araneda, J.; Bravo-Carrasco, V.; Álvarez, C.; Marzuca-Nassr, G.N.; Muñoz-Mendoza, C.L.; Muñoz, J.; Caparrós-Manosalva, C. Postural Balance and Gait Parameters of Independent Older Adults: A Sex Difference Analysis. Int. J. Environ. Res. Public Health 2022, 19, 4064. [Google Scholar] [CrossRef]
- Blaszczyk, J.W.; Prince, F.; Raiche, M.; Hébert, R. Effect of ageing and vision on limb load asymmetry during quiet stance. J. Biomech. 2000, 33, 1243–1248. [Google Scholar] [CrossRef]
- Yang, Z. An Efficient Automatic Gait Anomaly Detection Method Based on Semisupervised Clustering. Comput. Intell. Neurosci. 2021, 2021, 8840156. [Google Scholar] [CrossRef]
- Raza, M.A.; Fisher, R.B. Vision-based approach to assess performance levels while eating. Mach. Vis. Appl. 2023, 34, 124. [Google Scholar] [CrossRef]
- G*Power 3.1. Available online: http://www.gpower.hhu.de/en.html (accessed on 15 February 2024).
- Lee, P.H.; Macfarlane, D.J.; Lam, T.H.; Stewart, S.M. Validity of the international physical activity questionnaire short form (IPAQ-SF): A systematic review. Int. J. Behav. Nutr. Phys. Act. 2011, 8, 115. [Google Scholar] [CrossRef]
- Nagasawa, Y.; Demura, S. Effects of Intensive Up-to-Exhaustion Walking Exercise on the Center of Gravity Sway. Int. J. Exp. Clin. Res. 2022, 6, 314–320. [Google Scholar] [CrossRef]
- Imaoka, Y.; Saba, N.; Vanhoestenberghe, A.; de Bruin, E.D. Triggering Postural Movements With Virtual Reality Technology in Healthy Young and Older Adults: A Cross-Sectional Validation Study for Early Dementia Screening. Front. Med. 2020, 7, 533675. [Google Scholar] [CrossRef]
- Muehlbauer, T.; Gollhofer, A.; Granacher, U. Associations Between Measures of Balance and Lower-Extremity Muscle Strength/Power in Healthy Individuals Across the Lifespan: A Systematic Review and Meta-Analysis. Sports Med. 2015, 45, 1671–1692. [Google Scholar] [CrossRef]
- O’Connor, K.W.; Loughlin, P.J.; Redfern, M.S.; Sparto, P.J. Postural adaptations to repeated optic flow stimulation in older adults. Gait Posture 2008, 28, 385–391. [Google Scholar] [CrossRef]
- Pechtl, K.S.; Jennings, J.R.; Redfern, M.S. Optic flow and attention alter locomotion differently in the young and old. Gait Posture 2020, 76, 1–6. [Google Scholar] [CrossRef]
- Era, P.; Sainio, P.; Koskinen, S.; Haavisto, P.; Vaara, M.; Aromaa, A. Postural balance in a random sample of 7979 subjects aged 30 years and over. Gerontology 2006, 52, 204–213. [Google Scholar] [CrossRef]
- Freitag, S.; Weyers, B.; Kuhlen, T.W. Examining rotation gain in CAVE-like virtual environments. IEEE Trans. Vis. Comput. Graph. 2016, 22, 1462–1471. [Google Scholar] [CrossRef]
- Häkkinen, J.; Vuori, T.; Puhakka, M. Postural stability and sickness symptoms after HMD use. In Proceedings of the IEEE International Conference on Systems, Man and Cybernetics, Yasmine Hammamet, Tunisia, 6–9 October 2002; Volume 1, pp. 147–152. [Google Scholar] [CrossRef]
- Jaeger, B.K.; Mourant, R.R. Comparison of simulator sickness using static and dynamic walking simulators. Proc. Hum. Factors Ergon. Soc. Annu. Meet. 2001, 45, 1896–1900. [Google Scholar] [CrossRef]
- Lawson, B. Motion sickness symptomatology and origins. In Handbook of Virtual Environments: Design, Implementation, and Applications, 2nd ed.; Hale, K.S., Stanney, K.M., Eds.; CRC Press: Boca Raton, FL, USA, 2014; pp. 531–600. [Google Scholar]
- Clemes, S.A.; Howarth, P.A. The menstrual cycle and susceptibility to virtual simulation sickness. J. Biol. Rhythms 2005, 20, 71–82. [Google Scholar] [CrossRef]
- Stanney, K.M.; Fidopiastis, C.; Foster, L. Virtual reality is sexist: But it does not have to be. Front. Robot. AI 2020, 7, 1–19. [Google Scholar] [CrossRef]
- Hua, G.; Li, L.; Liu, S. Multipath affinage stacked–hourglass networks for human pose estimation. Front. Comput. Sci. 2020, 14, 144701. [Google Scholar] [CrossRef]
- Liu, S.; Li, Y.; Hua, G. Human Pose Estimation in Video via Structured Space Learning and Halfway Temporal Evaluation. IEEE Trans. Circuits Syst. Video Technol. 2019, 29, 2029–2038. [Google Scholar] [CrossRef]
Younger Adults (n = 20) | Older Adults (n = 34) | p-Value | |
---|---|---|---|
Women (%) | 10 (50.0%) | 24 (70.6%) | - |
Age (years) | 23.15 ± 1.04 | 75.56 ± 5.26 | <0.001 a |
Height (cm) | 164.02 ± 6.86 | 157.05 ± 10.79 | <0.001 a |
Body weight (kg) | 58.99 ± 8.52 | 54.78 ± 11.08 | <0.001 a |
Body mass index (kg/m2) | 21.87 ± 2.43 | 22.05 ± 2.95 | 0.557 a |
IPAQ-SF | |||
Total PA (Mets*mins/week) | 1476.00 [770.25–2351.25] | 832.00 [396.00–1805.25] | <0.001 b |
Vigorous PA (Mets*mins/week) | 720.00 [0.00–960.00] | 0.00 [0.00–0.00] | <0.001 b |
Moderate PA (Mets*mins/week) | 420.00 [20.00–480.00] | 0.00 [0.00–480.00] | <0.001 b |
Walking (Mets*mins/week) | 297.00 [0.00–594.00] | 627.00 [321.750–1188.00] | <0.001 b |
Sedentary Time (min/day) | 600.00 [600.00–780.00] | 300.00 [180.00–555.00] | <0.001 b |
Generation | Interaction Effect (Generation × Condition) | Main Effect (Generation) | Main Effect (Condition) | ||||||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
Variables | Condition | Younger Adults (n = 20) | Older Adults (n = 34) | F | p-Value | η2 | Observed Power | F | p-Value | η2 | Observed Power | F | p-Value | η2 | Observed Power |
X-axis trajectory length (mm) | |||||||||||||||
Control | −0.45 [−2.22–0.58] | −0.82 [−2.10–1.08] | 1.035 | 0.359 | 0.020 | 0.227 | 0.866 | 0.356 | 0.016 | 0.150 | 1.691 | 0.189 | 0.031 | 0.349 | |
VR 30° | 2.02 [0.04–5.85] | 0.23 [−2.49–5.00] | |||||||||||||
VR 60° | 2.25 [−0.26–4.88] | 0.73 [−3.07–4.77] | |||||||||||||
Y-axis trajectory length (mm) | |||||||||||||||
Control | 2.05 [−5.20–5.33] | 0.85 [−0.88–3.70] | 3.436 | 0.036 | 0.062 | 0.633 | 4.210 | 0.045 | 0.075 | 0.522 | 8.346 | <0.001 | 0.138 | 0.959 | |
VR 30° | −4.15 [−7.66–1.03] | −0.58 [−5.43–3.23] | |||||||||||||
VR 60° | −5.58 [−7.12–−1.14] * | 1.08 [−4.08–3.91] ‡ | |||||||||||||
Total trajectory length (mm) | |||||||||||||||
Control | 86.92 [77.07–96.00] | 109.43 [91.68–142.88] ‡ | 7.878 | <0.001 | 0.132 | 0.936 | 33.724 | <0.001 | 0.393 | 1.000 | 8.809 | <0.001 | 0.145 | 0.959 | |
VR 30° | 83.55 [72.73–93.85] | 157.45 [125.53–249.02] †,‡ | |||||||||||||
VR 60° | 78.45 [65.10–107.06] | 188.85 [112.75–283.36] †,‡ | |||||||||||||
Trajectory length per unit time (mm/s) | |||||||||||||||
Control | 8.77 [7.82–9.69] | 11.40 [9.36–14.57] | 2.337 | 0.102 | 0.043 | 0.464 | 13.897 | <0.001 | 0.211 | 0.955 | 5.275 | 0.007 | 0.092 | 0.825 | |
VR 30° | 8.43 [7.34–9.48] | 15.90 [12.67–25.17] | |||||||||||||
VR 60° | 8.65 [6.91–10.79] | 19.08 [11.39–28.63] | |||||||||||||
Outer peripheral area (mm2) | |||||||||||||||
Control | 90.62 [65.39–114.62] | 112.10 [73.80–147.38] | 0.305 | 0.738 | 0.006 | 0.097 | 6.960 | 0.011 | 0.118 | 0.735 | 0.999 | 0.372 | 0.019 | 0.220 | |
VR 30° | 87.40 [64.65–102.98] | 124.63 [87.95–244.08] | |||||||||||||
VR 60° | 71.98 [54.08–124.83] | 146.47 [75.05–320.21] | |||||||||||||
Rectangular area (mm2) | |||||||||||||||
Control | 150.82 [97.92–196.40] | 174.92 [95.18–271.08] | 0.115 | 0.892 | 0.002 | 0.067 | 4.531 | 0.038 | 0.080 | 0.551 | 0.779 | 0.462 | 0.015 | 0.180 | |
VR 30° | 131.70 [88.69–201.73] | 191.53 [136.54–417.10] | |||||||||||||
VR 60° | 110.90 [68.23–254.09] | 230.30 [108.96–616.88] |
Younger Adults (n = 20) | Older Adults (n = 34) | p-Value | Effect Size | ||||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|
Men (n = 10) | Women (n = 10) | Men (n = 10) | Women (n = 24) | Men vs. Women | Younger vs. Older Adults | Men vs. Women | Younger vs. Older Adults | ||||||
Variables | Condition | Younger Adults | Older Adults | Men | Women | Younger Adults | Older Adults | Men | Women | ||||
X-axis trajectory length (mm) | |||||||||||||
Control | −0.40 [−1.96–0.85] | −1.00 [−3.61–0.87] | −1.62 [−2.28–0.06] | −0.32 [−1.88–2.02] | 0.684 | 0.223 | 0.436 | 0.401 | −0.102 | 0.211 | −0.186 | 0.149 | |
VR 30° | 0.35 [−0.67–4.68] | 3.75 [1.98–7.05] | 6.15 [0.51–10.68] | −1.40 [−2.94–3.56] | 0.043 | 0.001 | 0.105 | 0.002 | 0.448 | −0.525 | 0.372 | −0.506 | |
VR 60° | −0.15 [−2.11–2.45] | 4.40 [1.90–6.51] | 6.33 [1.05–8.91] | −1.60 [−3.68–1.92] | 0.015 | 0.001 | 0.052 | 0.001 | 0.541 | −0.538 | 0.439 | −0.538 | |
Y-axis trajectory length (mm) | |||||||||||||
Control | 2.45 [−4.53–8.92] | 0.80 [−5.96–5.82] | 0.12 [−4.37–4.13] | 0.85 [−0.62–3.55] | 0.739 | 0.539 | 0.631 | 0.564 | −0.076 | 0.107 | −0.118 | 0.100 | |
VR 30° | −4.15 [−8.48–−1.33] | −4.32 [−7.67–1.94] | −3.60 [−7.24–1.19] | 0.20 [−4.22–3.37] | 0.796 | 0.127 | 0.912 | 0.101 | −0.068 | 0.266 | 0.034 | 0.285 | |
VR 60° | −6.05 [−8.30–−1.30] | −4.15 [−6.37–−0.22] | −4.62 [−10.13–−1.01] | −0.25 [−3.16–7.53] | 0.315 | 0.010 | 0.912 | 0.023 | 0.237 | 0.431 | 0.034 | 0.389 | |
Total trajectory length (mm) | |||||||||||||
Control | 80.78 [68.02–102.94] | 88.40 [81.85–92.41] | 113.82 [91.68–146.91] | 109.43 [90.18–142.03] | 0.579 | 0.724 | 0.035 | 0.010 | −0.135 | −0.065 | 0.473 | 0.434 | |
VR 30° | 78.42 [67.18–92.94] | 86.88 [76.58–106.32] | 213.70 [127.26–257.52] | 149.47 [115.21–231.66] | 0.218 | 0.341 | <0.001 | <0.001 | 0.287 | −0.169 | 0.777 | 0.609 | |
VR 60° | 78.45 [61.80–116.46] | 78.93 [67.17–105.98] | 186.65 [135.10–305.17] | 188.85 [110.42–270.24] | 0.912 | 0.589 | 0.002 | <0.001 | 0.034 | 0.164 | 0.676 | 0.642 | |
Trajectory length per unit time (mm/s) | |||||||||||||
Control | 8.15 [6.87–10.39] | 8.92 [8.27–9.34] | 11.50 [9.27–14.83] | 11.40 [9.44–14.51] | 0.579 | 0.897 | 0.035 | 0.006 | 0.135 | −0.023 | 0.473 | 0.460 | |
VR 30° | 7.93 [6.79–9.37] | 8.75 [7.76–12.21] | 21.58 [12.86–26.02] | 15.08 [11.62–23.39] | 0.190 | 0.341 | <0.001 | 0.004 | 0.304 | −0.169 | 0.777 | 0.483 | |
VR 60° | 7.93 [6.23–11.75] | 9.25 [6.99–10.69] | 18.85 [13.64–30.83] | 19.08 [11.16–27.31] | 0.739 | 0.589 | 0.002 | <0.001 | 0.076 | 0.097 | 0.676 | 0.629 | |
Outer peripheral area (mm2) | |||||||||||||
Control | 86.32 [54.64–151.33] | 97.43 [74.33–111.21] | 122.85 [78.07–165.11] | 106.38 [73.80–142.38] | 0.684 | 0.696 | 0.393 | 0.564 | 0.102 | −0.071 | 0.203 | 0.104 | |
VR 30° | 84.17 [44.59–120.88] | 87.77 [69.32–107.84] | 201.30 [84.18–338.66] | 117.83 [90.45–157.96] | 0.739 | 0.304 | 0.052 | 0.046 | 0.085 | −0.181 | 0.439 | 0.344 | |
VR 60° | 79.88 [49.79–126.79] | 66.25 [54.43–119.81] | 163.35 [108.34–380.23] | 133.23 [69.94–295.14] | 0.912 | 0.445 | 0.063 | 0.013 | −0.034 | −0.136 | 0.423 | 0.421 | |
Rectangular area (mm2) | |||||||||||||
Control | 139.63 [77.79–283.65] | 159.65 [120.43–226.82] | 199.15 [112.05–377.66] | 161.03 [93.31–254.50] | 0.684 | 0.467 | 0.393 | 0.838 | 0.102 | −0.130 | 0.203 | 0.039 | |
VR 30° | 131.70 [55.60–248.45] | 137.88 [92.88–195.44] | 325.05 [131.16–679.30] | 179.70 [126.24–347.65] | 1.000 | 0.270 | 0.075 | 0.183 | 0.000 | −0.194 | 0.406 | 0.233 | |
VR 60° | 122.32 [60.49–274.91] | 95.35 [71.44–235.01] | 256.40 [184.33–658.20] | 214.18 [99.24–584.26] | 1.000 | 0.515 | 0.105 | 0.055 | −0.017 | −0.117 | 0.372 | 0.331 |
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content. |
© 2024 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
Share and Cite
Tashiro, T.; Maeda, N.; Abekura, T.; Mizuta, R.; Terao, Y.; Arima, S.; Onoue, S.; Urabe, Y. Adaptation of Postural Sway in a Standing Position during Tilted Video Viewing Using Virtual Reality: A Comparison between Younger and Older Adults. Sensors 2024, 24, 2718. https://doi.org/10.3390/s24092718
Tashiro T, Maeda N, Abekura T, Mizuta R, Terao Y, Arima S, Onoue S, Urabe Y. Adaptation of Postural Sway in a Standing Position during Tilted Video Viewing Using Virtual Reality: A Comparison between Younger and Older Adults. Sensors. 2024; 24(9):2718. https://doi.org/10.3390/s24092718
Chicago/Turabian StyleTashiro, Tsubasa, Noriaki Maeda, Takeru Abekura, Rami Mizuta, Yui Terao, Satoshi Arima, Satoshi Onoue, and Yukio Urabe. 2024. "Adaptation of Postural Sway in a Standing Position during Tilted Video Viewing Using Virtual Reality: A Comparison between Younger and Older Adults" Sensors 24, no. 9: 2718. https://doi.org/10.3390/s24092718
APA StyleTashiro, T., Maeda, N., Abekura, T., Mizuta, R., Terao, Y., Arima, S., Onoue, S., & Urabe, Y. (2024). Adaptation of Postural Sway in a Standing Position during Tilted Video Viewing Using Virtual Reality: A Comparison between Younger and Older Adults. Sensors, 24(9), 2718. https://doi.org/10.3390/s24092718