DOI QR코드

DOI QR Code

Intelligent Soft Suit That Can Autonomously Augment Strength and Protect the Human Body (Exoskin)

인간 신체를 자율적으로 보조하고 보호하는 지능형 소프트 슈트(엑소스킨)

  • Published : 2021.02.01

Abstract

Innovative developments in wearable and artificial intelligence technologies are accelerating the emergence of a soft suit that can autonomously augment a body's own strength and protect the human body. In this paper, we define the concept of "Exoskin," a new concept specifically derived from the "Road to an Intelligent Information Society" (Technology Development Map 2035) as predicted by the Electronics and Telecommunications Research Institute. In addition, we analyze the development status of each element of this technology and forecast its future development.

Keywords

References

  1. 통계청, "생명표, 국가승인통계 제101035호," 2017.
  2. Wikipedia, "E-textiles," https://en.wikipedia.org/wiki/E-textiles
  3. Wikipedia, "Transhumanism," https://en.wikipedia.org/wiki/Transhumanism
  4. 박소영, "인공지능 시대 인간의 신체와 문학적 형상화-사이보그, 트랜스휴먼, 포스트휴먼 그리고 뉴로맨서," 제41권 제4호, 2019, pp. 1157-1190.
  5. 이동우 외, "착용형 근력증강 기술 동향," 전자통신동향분석, 제32권 제4호, 2017, pp. 21-30. https://doi.org/10.22648/ETRI.2017.J.320403
  6. F.A. Panizzolo et al., "A biologically-inspired multi-joint soft exosuit that can reduce the energy cost of loaded walking," J. Neuroeng. Rehabilitation, vol. 13, 2016, pp. 1-14. https://doi.org/10.1186/s12984-015-0109-2
  7. L.N. Awad et al., "A soft robotic exosuit improves walking in patients after stroke," Sci. Translational Medicine, vol. 9, no. 400, 2017, doi: 10.1126/scirobotics.aah4416.
  8. B.T. Quinlivan et al., "Assistance magnitude versus metabolic cost reductions for a tethered multiarticular soft exosuit," Sci. Robotics, vol. 2, no. 2, 2017, doi: 10.1126/scirobotics.aah4416
  9. J. Kim et al., "Reducing the metabolic rate of walking and running with a versatile, portable exosuit." Sci., vol. 365, no. 6454, 2019, pp. 668-672. https://doi.org/10.1126/science.aav7536
  10. L.N. Awad et al., "The ReWalk ReStore™ soft robotic exosuit: a multi-site clinical trial of the safety, reliability, and feasibility of exosuit-augmented post-stroke gait rehabilitation." J. Neuroeng. Rehabilitation, vol. 17, 2020, pp. 1-11. https://doi.org/10.1186/s12984-019-0634-5
  11. https://www.sigmedics.com/
  12. https://www.hankyung.com/it/article/202007239901Y
  13. 신형철 외, "신체 기능의 이상이나 저하를 극복하기 위한 휴먼청각 및 근력 증강 원천 기술 개발," 한국전자통신연구원 3연차 보고서, 2019. 11.
  14. https://www.hexoskin.com/
  15. https://www.catapultsports.com/
  16. https://www.helite.com/
  17. https://www.tangobelt.com/
  18. https://www.wolkairbag.com/
  19. https://www.hip-hope.com/
  20. S. Hong et al., "Wearable thermoelectrics for personalized thermoregulation," Sci. Advances, vol. 5, no. 5, 2019, doi: 10.1126/sciadv.aaw0536.
  21. R.S. Johannson and A.B. Vallbo, "Tactile sensibility in the human hand: receptive field and absolute densities of four types of mechanoreceptive units in glabrous skin area," J. Physiol, vol. 281, 1978, pp. 101-123. https://doi.org/10.1113/jphysiol.1978.sp012411
  22. A. Chortos et al., "Pursuing prosthetic electronic skin," Nature Mater, vol. 15, 2016, doi: 10.1038/nmat4671.
  23. I. You et al., "E-skin tactile sensor matrix pixelated by position-registered conductive microparticles creating pressure-sensitive selectors," Adv. Func. Mater., 2018, 28, 1801858.
  24. N. Bai et al., "Graded intrafillable architecture-based iontronic pressure sensor with ultra-broad-range high sensitivity," Nature Commun., vol. 11, 2020, doi: 10.1038/s41467-019-14054-9.
  25. S. Chun et al., "Self-Powered Pressure- and Vibration-Sensitive Tactile Sensors for Learning Technique-Based Neural Finger Skin," Nano Lett., vol. 19, no. 5, 2019, pp. 3305-3312. https://doi.org/10.1021/acs.nanolett.9b00922
  26. Q. Hua et al., "Skin-inspired highly stretchable and conformable matrix networks for multifunctional sensing." Nature Commun., vol. 9, no. 1, 2018, pp. 1-11. https://doi.org/10.1038/s41467-017-02088-w
  27. S. Lee et al., "Nanomesh pressure sensor for monitoring finger manipulation without sensory interference," Sci., vol. 370, no. 6519, pp. 966-970. https://doi.org/10.1126/science.abc9735
  28. F. Ershad et al., "Ultra-conformal drawn-on-skin electronics for multifunctional motion artifact-free sensing and point-of-care treatment," Nature Commun., vol. 11, July. 2020, doi: 10.1038/s41467-020-17619-1
  29. M. Ding et al., "Control of Walking Assist Exoskeleton With Time-delay Based on the Prediction of Plantar Force," IEEE Access, vol. 8, 2020, pp. 138642-138651. https://doi.org/10.1109/access.2020.3010644
  30. I. Kang et al., "Electromyography (EMG) signal contributions in speed and slope estimation using robotic exoskeletons," in Proc. IEEE Int. Conf. Rehabilitation Robot. (Roeonro, Canada), June 2019, doi: 10.1109/ICORR.2019.8779433.
  31. D. Molinaro et al., "Biological Hip Torque Estimation using a Robotic Hip Exoskeleton," in Proc. IEEE RAS/EMBS Int. Conf. Biomed. Roboti. Biomechatronics (New York, USA), 2020, doi: 10.1109/BioRob49111.2020.9224334.
  32. X.B. Peng et al., "Learning Agile Robotic Locomotion Skills by Imitating Animals," arXiv preprint, 2020, arXiv:2004.00784.
  33. H. Tan et al., "Tactile sensory coding and learning with bio-inspired optoelectronic spiking afferent nerves," Nature Commun., vol. 11, 2020, doi: 10.1038/s41467-020-15105-2
  34. S. Sundaram et al., "Learning the signatures of the human grasp using a scalable tactile glove," Nature, vol. 569, no. 7758, 2019, pp. 698-702. https://doi.org/10.1038/s41586-019-1234-z