Advertisement

Easy Undressing with Soft Robotics

  • Tim Helps
  • Majid Taghavi
  • Sarah Manns
  • Ailie J. Turton
  • Jonathan Rossiter
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10965)

Abstract

Dexterity impairments affect many people worldwide, limiting their ability to easily perform daily tasks and to be independent. Difficulty getting dressed and undressed is commonly reported. Some research has been performed on robot-assisted dressing, where an external device helps the user put on and take off clothes. However, no wearable robotic technology or robotic assistive clothing has yet been proposed that actively helps the user dress. In this article, we introduce the concept of Smart Adaptive Clothing, which uses Soft Robotic technology to assist the user in dressing and undressing. We discuss how Soft Robotic technologies can be applied to Smart Adaptive Clothing and present a proof of concept study of a Pneumatic Smart Adaptive Belt. The belt weighs only 68 g, can expand by up to 14% in less than 6 s, and is demonstrated aiding undressing on a mannequin, achieving an extremely low undressing time of 1.7 s.

Keywords

Healthcare Adaptive clothing Soft robotics Wearable robotics 

Notes

Acknowledgements

Research supported by UK Engineering and Physical Sciences Research Council grants EP/M020460/1 and EP/M026388/1. Local graphic facilitator Bethan Mure was responsible for illustrations during focus groups described in [3]. More of Bethan’s work can be found at www.bmurecreative.co.uk

References

  1. 1.
    Age UK: Later Life in the United Kingdom (2017)Google Scholar
  2. 2.
    Office for National Statistics: Family Resources Survey (2017)Google Scholar
  3. 3.
    Manns, S., Turton, A.: The occupational therapist, the doctor, the researcher, the roboticist, and the artist. BMJ Open, 7 (2017).  https://doi.org/10.1136/bmjopen-2017-016492.23
  4. 4.
    Walker, M.F.: Stroke rehabilitation: evidence-based or evidence-tinged? J. Rehabil. Med. 39, 193–197 (2007).  https://doi.org/10.2340/16501977-0063CrossRefGoogle Scholar
  5. 5.
    Azher, N., Saeed, M., Kalsoom, S.: Adaptive clothing for females with arthritis Impairment. Institute of Education and Research, University of the Punjab, Lahore (2012)Google Scholar
  6. 6.
    Legg, L., Drummond, A., Leonardi-Bee, J., et al.: Occupational therapy for patients with problems in personal activities of daily living after stroke: systematic review of randomised trials. BMJ 335, 922 (2007).  https://doi.org/10.1136/bmj.39343.466863.55CrossRefGoogle Scholar
  7. 7.
    LIFE writers: Artificial Muscle. LIFE Mag. pp. 87–88 (1960)Google Scholar
  8. 8.
    Agerholm, M., Lord, A.: The “Artificial Muscle” of Mckibben. Lancet 277, 660–661 (1961).  https://doi.org/10.1016/S0140-6736(61)91676-2CrossRefGoogle Scholar
  9. 9.
    Forlizzi, J.: Robotic products to assist the aging population. Interactions 12, 16 (2005).  https://doi.org/10.1145/1052438.1052454CrossRefGoogle Scholar
  10. 10.
    Gao, Y., Chang, H.J., Demiris, Y.: User modelling for personalised dressing assistance by humanoid robots. In: IEEE International Conference on Intelligent Robots Systems, pp. 1840–1845 (2015).  https://doi.org/10.1109/iros.2015.7353617
  11. 11.
    Yamazaki, K., Oya, R., Nagahama, K., et al.: Bottom dressing by a dual-arm robot using a clothing state estimation based on dynamic shape changes. Int. J. Adv. Robot. Syst. 13, 5 (2016).  https://doi.org/10.5772/61930CrossRefGoogle Scholar
  12. 12.
    Kapusta, A., Yu, W., Bhattacharjee, T., et al: Data-driven haptic perception for robot-assisted dressing. In: IEEE International Symposium on Robot and Human, RO-MAN 2016, pp. 451–458 (2016).  https://doi.org/10.1109/roman.2016.7745158
  13. 13.
    Park, Y.L., Chen, B.R., Young, D., et al.: Bio-inspired active soft orthotic device for ankle foot pathologies. In: IEEE International Conference on Intelligent Robots and Systems, pp. 4488–4495 (2011).  https://doi.org/10.1109/IROS.2011.6048620
  14. 14.
    Park, Y.L., Chen, B.R., Majidi, C., et al.: Active modular elastomer sleeve for soft wearable assistance robots. In: IEEE Conference on Intelligent Robots and Systems, pp. 1595–1602 (2012).  https://doi.org/10.1109/IROS.2012.6386158
  15. 15.
    Wehner, M., Quinlivan, B., Aubin, P.M., et al.: A lightweight soft exosuit for gait assistance, pp. 3347–3354 (2013).  https://doi.org/10.1109/icra.2013.6631046
  16. 16.
    Park, Y.L., Santos, J., Galloway, K.G., et al.: A soft wearable robotic device for active knee motions using flat pneumatic artificial muscles. In: Proceedings of IEEE International Conference on Robotics and Automation, pp. 4805–4810 (2014).  https://doi.org/10.1109/ICRA.2014.6907562
  17. 17.
    Stirling, L., Yu, C.H., Miller, J., et al.: Applicability of shape memory alloy wire for an active, soft orthotic. J. Mater. Eng. Perform. 20, 658–662 (2011).  https://doi.org/10.1007/s11665-011-9858-7CrossRefGoogle Scholar
  18. 18.
    Li, Y., Hashimoto, M.: Development of a lightweight walking assist wear using PVC gel artificial muscles. In: Proceedings of IEEE RAS EMBS International Conference on Biomedical Robotics and Biomechatronics, July 2016, pp. 686–691 (2016).  https://doi.org/10.1109/biorob.2016.7523706
  19. 19.
    Lee, S., Crea, S., Malcolm, P., et al.: Controlling negative and positive power at the ankle with a soft exosuit. In: Proceedings of the 2016 IEEE International Conference on Robotics and Automation (ICRA), pp 3509–3515 (2016).  https://doi.org/10.1109/icra.2016.7487531
  20. 20.
    Bae, J., De Rossi, S.M.M., O’Donnell, K., et al.: A soft exosuit for patients with stroke: feasibility study with a mobile off-board actuation unit. In: IEEE International Conference on Rehabilitation Robotics, pp. 131–138, September 2015.  https://doi.org/10.1109/icorr.2015.7281188
  21. 21.
    Galiana, I., Hammond, F.L., Howe, R.D., Popovic, M.B.: Wearable soft robotic device for post-stroke shoulder rehabilitation: identifying misalignments. In: IEEE International Conference on Intelligent Robots and Systems, pp. 317–322 (2012).  https://doi.org/10.1109/IROS.2012.6385786
  22. 22.
    Asbeck, A.T., Dyer, R.J., Larusson, A.F., Walsh, C.J.: Biologically-inspired soft exosuit. In: IEEE International Conference on Rehabilitation Robotics (2013).  https://doi.org/10.1109/ICORR.2013.6650455
  23. 23.
    Asbeck, A.T., Schmidt, K., Galiana, I., et al.: Multi-joint soft exosuit for gait assistance. In: Proceedings of IEEE International Conference on Robotics and Automation, pp. 6197–6204, June 2015.  https://doi.org/10.1109/icra.2015.7140069
  24. 24.
    Asbeck, A.T., Schmidt, K., Walsh, C.J.: Soft exosuit for hip assistance. Robot. Auton. Syst. 73, 102–110 (2015).  https://doi.org/10.1016/j.robot.2014.09.025CrossRefGoogle Scholar
  25. 25.
    Yuen, M., Cherian, A., Case, J.C., et al.: Conformable actuation and sensing with robotic fabric. In: IEEE International Conference on Intelligent Robots and Systems, pp. 580–586 (2014).  https://doi.org/10.1109/IROS.2014.6942618
  26. 26.
    Chenal, T.P., Case, J.C., Paik, J., Kramer, R.K.: Variable stiffness fabrics with embedded shape memory materials for wearable applications. In: IEEE International Conference on Intelligent Robots and Systems, pp. 2827–2831 (2014).  https://doi.org/10.1109/IROS.2014.6942950
  27. 27.
    Yalcintas, M., Dai, H.: Magnetorheological and electrorheological materials in adaptive structures and their performance comparison. Smart Mater. Struct. 8, 560 (1999).  https://doi.org/10.1088/0964-1726/8/5/306CrossRefGoogle Scholar
  28. 28.
    Shintake, J., Rosset, S., Schubert, B., et al.: Versatile Soft grippers with intrinsic electroadhesion based on multifunctional polymer actuators. Adv. Mater. 28, 231–238 (2016).  https://doi.org/10.1002/adma.201504264CrossRefGoogle Scholar
  29. 29.
    Imamura, H., Kadooka, K., Taya, M.: A variable stiffness dielectric elastomer actuator based on electrostatic chucking. Soft Matter 13, 3440–3448 (2017).  https://doi.org/10.1039/C7SM00546FCrossRefGoogle Scholar
  30. 30.
    Brown, E., Rodenberg, N., Amend, J., et al.: Universal robotic gripper based on the jamming of granular material. Proc. Natl. Acad. Sci. 107, 18809–18814 (2010).  https://doi.org/10.1073/pnas.1003250107CrossRefGoogle Scholar
  31. 31.
    Taghavi, M., Helps, T., Huang, B., Rossiter, J.: 3D-printed ready-to-use variable-stiffness structures. IEEE Robot. Autom. Lett. 3, 2402–2407 (2018).  https://doi.org/10.1109/LRA.2018.2812917CrossRefGoogle Scholar
  32. 32.
    Haines, C.S., Lima, M.D., Li, N., et al.: Artificial muscles from fishing line and sewing thread. Science 343, 868–872 (2014).  https://doi.org/10.1126/science.1246906CrossRefGoogle Scholar
  33. 33.
    Madden, J.D.W., Vandesteeg, N.A., Anquetil, P.A., et al.: Artificial muscle technology: physical principles and naval prospects. IEEE J. Ocean. Eng. 29, 706–728 (2004).  https://doi.org/10.1109/JOE.2004.833135CrossRefGoogle Scholar
  34. 34.
    Daerden, F., Lefeber, D., Verrelst, B., Van Ham, R.: Pleated pneumatic artificial muscles: compliant robotic actuators. In: Proceedings of 2001 IEEE/RSJ International Conference on Intelligent Robots and Systems, vol. 4, pp. 1958–1963 (2001).  https://doi.org/10.1109/iros.2001.976360
  35. 35.
    Niiyama, R., Rus, D., Kim, S.: Pouch motors: printable/inflatable soft actuators for robotics. In: Proceedings of 2014 IEEE International Conference on Robotics and Automation, pp. 6332–6337 (2014).  https://doi.org/10.1109/icra.2014.6907793
  36. 36.
    Veale, A.J., Anderson, I.A., Xie, S.Q.: The smart Peano fluidic muscle: a low profile flexible orthosis actuator that feels pain. vol. 9435, p. 94351V (2015).  https://doi.org/10.1117/12.2084130
  37. 37.
    Yang, D., Verma, M.S., So, J.-H., et al.: Buckling pneumatic linear actuators inspired by muscle. Adv. Mater. Technol. 1, 1600055 (2016).  https://doi.org/10.1002/admt.201600055CrossRefGoogle Scholar
  38. 38.
    Li, S., Vogt, D.M., Rus, D., Wood, R.J.: Fluid-driven origami-inspired artificial muscles. Proc. Natl. Acad. Sci. 114, 13132–13137 (2017).  https://doi.org/10.1073/pnas.1713450114CrossRefGoogle Scholar
  39. 39.
    Wang, J., Wang, J.: Shape memory effect of TiNi-based springs trained by constraint annealing. Met. Mater. Int. 19, 295 (2013).  https://doi.org/10.1007/s12540-013-2025-yCrossRefGoogle Scholar
  40. 40.
    Belforte, G., Eula, G., Ivanov, A., Visan, A.L.: Bellows textile muscle. J. Text. Inst. 105, 356–364 (2014).  https://doi.org/10.1080/00405000.2013.840414CrossRefGoogle Scholar
  41. 41.
    Helps, T., Rossiter, J.: Proprioceptive flexible fluidic actuators using conductive working fluids. Soft Robot. 5, 175–189 (2018).  https://doi.org/10.1089/soro.2017.0012CrossRefGoogle Scholar
  42. 42.
    Hawkes, E.W., Christensen, D.L., Okamura, A.M.: Design and implementation of a 300% strain soft artificial muscle, pp. 4022–4029 (2016).  https://doi.org/10.1109/icra.2016.7487592

Copyright information

© Springer International Publishing AG, part of Springer Nature 2018

Authors and Affiliations

  • Tim Helps
    • 1
    • 2
  • Majid Taghavi
    • 1
    • 2
  • Sarah Manns
    • 3
  • Ailie J. Turton
    • 4
  • Jonathan Rossiter
    • 1
    • 2
  1. 1.Department of Engineering MathematicsUniversity of BristolBristolUK
  2. 2.Bristol Robotics LaboratoryBristolUK
  3. 3.Faculty of Health and Applied SciencesUniversity of the West of EnglandBristolUK
  4. 4.Department of Allied Health ProfessionsUniversity of the West of EnglandBristolUK

Personalised recommendations