Exoskeleton Training through Haptic Sensation Transfer in Immersive Virtual Environment
Publication: Construction Research Congress 2022
ABSTRACT
Exoskeleton as a human augmentation technology has shown a great potential for transforming the future civil engineering operations. However, the inappropriate use of exoskeleton could cause injuries and damages if the user is not well-trained. An effective procedural and operational training will make users more aware of the capabilities, restrictions, and risks associated with exoskeleton in civil engineering operations. At present, the low availability and high cost of exoskeleton systems make hands-on training less feasible. In addition, different designs of exoskeleton correspond with different activation procedures, muscular engagement, and motion boundaries, posing further challenges to exoskeleton training. We propose a “sensation transfer” approach that migrates the physical experience of wearing a real exoskeleton system to first-time users via a passive haptic system in an immersive virtual environment. The body motion and muscular engagement data of 15 experienced exoskeleton users were recorded and replayed in a virtual reality environment. Then, a set of haptic devices on key parts of the body (shoulders, elbows, hands, and waist) generate different patterns of haptic cues depending on the trainees’ accuracy of mimicking the actions. The sensation transfer method will enhance the haptic learning experience and therefore accelerate the training.
Get full access to this article
View all available purchase options and get full access to this chapter.
REFERENCES
Banala, S. K., Kim, S. H., Agrawal, S. K., and Scholz, J. P. (2009). “Robot Assisted Gait Training With Active Leg Exoskeleton (ALEX).” IEEE Transactions on Neural Systems and Rehabilitation Engineering, 17(1), 2–8.
bHaptics. 2021. Retrieved on Jun 9th from https://www.bhaptics.com/.
Cho Yong, K., Kim, K., Ma, S., and Ueda, J. “A Robotic Wearable Exoskeleton for Construction Worker?s Safety and Health.” Construction Research Congress 2018, 19–28.
Doniger, G. M., Beeri, M. S., Bahar-Fuchs, A., Gottlieb, A., Tkachov, A., Kenan, H., Livny, A., Bahat, Y., Sharon, H., Ben-Gal, O., Cohen, M., Zeilig, G., and Plotnik, M. (2018). “Virtual reality-based cognitive-motor training for middle-aged adults at high Alzheimer’s disease risk: A randomized controlled trial.” Alzheimer’s & Dementia: Translational Research & Clinical Interventions, 4, 118–129.
Hamilton, F., Rochester, L., Paul, L., Rafferty, D., O’Leary, C. P., and Evans, J. J. (2009). “Walking and talking: an investigation of cognitive—motor dual tasking in multiple sclerosis.” Multiple Sclerosis Journal, 15(10), 1215–1227.
He, Y., Eguren, D., Luu, T. P., and Contreras-Vidal, J. L. (2017). “Risk management and regulations for lower limb medical exoskeletons: a review.” Medical devices (Auckland, N.Z.), 10, 89–107.
Heuer, H. (2007). “Control of the dominant and nondominant hand: exploitation and taming of nonmuscular forces.” Experimental Brain Research, 178(3), 363–373.
Hong, M. B., Kim, G. T., and Yoon, Y. H. (2019). “ACE-Ankle: A Novel Sensorized RCM (Remote-Center-of-Motion) Ankle Mechanism for Military Purpose Exoskeleton.” Robotica, 37(12), 2209–2228.
Kagirov, I., Kapustin, A., Kipyatkova, I., Klyuzhev, K., Kudryavcev, A., Kudryavcev, I., Loskutov, Y., Ryumin, D., and Karpov, A. (2021). “Medical exoskeleton “Remotion” with an intelligent control system: Modeling, implementation, and testing.” Simulation Modelling Practice and Theory, 107, 102200.
Kim, S., Moore, A., Srinivasan, D., Akanmu, A., Barr, A., Harris-Adamson, C., Rempel, D. M., and Nussbaum, M. A. (2019). “Potential of Exoskeleton Technologies to Enhance Safety, Health, and Performance in Construction: Industry Perspectives and Future Research Directions.” IISE Transactions on Occupational Ergonomics and Human Factors, 7(3-4), 185–191.
Lee, S. H., Cui, J., Liu, L., Su, M. C., Zheng, L., and Yeh, S. C. (2021). “An Evidence-Based Intelligent Method for Upper-Limb Motor Assessment via a VR Training System on Stroke Rehabilitation.” IEEE Access, 9, 65871–65881.
Lindgren, R. (2012). “Generating a learning stance through perspective-taking in a virtual environment.” Comput. Hum. Behav., 28(4), 1130–1139.
Liu, J., Cramer, S. C., and Reinkensmeyer, D. J. (2006). “Learning to perform a new movement with robotic assistance: comparison of haptic guidance and visual demonstration.” Journal of neuroengineering and rehabilitation, 3, 20–20.
Sanngoen, W., Nillnawarad, S., and Patchim, S. “Design and development of low-cost assistive device for lower limb exoskeleton robot.” Proc., 2017 10th International Conference on Human System Interactions (HSI), 148–153.
Schüler, T., Santos, L. F. D., and Hoermann, S. “Designing virtual environments for motor rehabilitation: Towards a framework for the integration of best-practice information.” Proc., 2015 International Conference on Virtual Rehabilitation (ICVR), 145–146.
Shi, Y., Kang, J., Xia, P., Tyagi, O., Mehta, R. K., and Du, J. (2021). “Spatial knowledge and firefighters’ wayfinding performance: A virtual reality search and rescue experiment.” Safety Science, 105231.
van Breda, E., Verwulgen, S., Saeys, W., Wuyts, K., Peeters, T., and Truijen, S. (2017). “Vibrotactile feedback as a tool to improve motor learning and sports performance: a systematic review.” BMJ Open Sport Exerc Med, 3(1), e000216.
van Herpen, F. H. M., van Dijsseldonk, R. B., Rijken, H., Keijsers, N. L. W., Louwerens, J. W. K., and van Nes, I. J. W. (2019). “Case Report: Description of two fractures during the use of a powered exoskeleton.” Spinal Cord Series and Cases, 5(1), 99.
Wang, S., Wang, L., Meijneke, C., Asseldonk, E. V., Hoellinger, T., Cheron, G., Ivanenko, Y., Scaleia, V. L., Sylos-Labini, F., Molinari, M., Tamburella, F., Pisotta, I., Thorsteinsson, F., Ilzkovitz, M., Gancet, J., Nevatia, Y., Hauffe, R., Zanow, F., and Kooij, H. V. D. (2015). “Design and Control of the MINDWALKER Exoskeleton.” IEEE Transactions on Neural Systems and Rehabilitation Engineering, 23(2), 277–286.
Williams, C. K., and Carnahan, H. (2014). “Motor learning perspectives on haptic training for the upper extremities.” IEEE Trans Haptics, 7(2), 240–250.
Xsens. 2021. Retrieved on Jun 9th from https://www.xsens.com/.
Yang, C. J., Zhang, J. F., Chen, Y., Dong, Y. M., and Zhang, Y. (2008). “A Review of exoskeleton-type systems and their key technologies.” Proceedings of the Institution of Mechanical Engineers, Part C: Journal of Mechanical Engineering Science, 222(8), 1599–1612.
Young, A. J., Gannon, H., and Ferris, D. P. (2017). “A Biomechanical Comparison of Proportional Electromyography Control to Biological Torque Control Using a Powered Hip Exoskeleton.” Frontiers in Bioengineering and Biotechnology, 5, 37.
Yu, H., Choi, I. S., Han, K.-L., Choi, J. Y., Chung, G., and Suh, J. (2018). “Development of a upper-limb exoskeleton robot for refractory construction.” Control Engineering Practice, 72, 104–113.
Zhu, Z., Dutta, A., and Dai, F. (2021). “Exoskeletons for manual material handling – A review and implication for construction applications.” Automation in Construction, 122, 103493.
Information & Authors
Information
Published In
Construction Research Congress 2022
Pages: 560 - 569
History
Published online: Mar 7, 2022
Authors
Metrics & Citations
Metrics
Citations
Download citation
If you have the appropriate software installed, you can download article citation data to the citation manager of your choice. Simply select your manager software from the list below and click Download.