Skip to main content
SpringerLink
Log in

Human Factors in Interfaces for Rehabilitation-Assistive Exoskeletons: A Critical Review and Research Agenda

  • Conference paper
  • First Online:
Human Interaction, Emerging Technologies and Future Applications II (IHIET 2020)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 1152))

  • 1932 Accesses

Abstract

Exoskeletons are wearable robots designed to restore or augment human physical abilities and, indirectly, cognitive functions. These devices can be classified based on the sector of application, the body part they are intended to support or enhance, the degree of assistance, and the source which they gather power from. Regardless of such technical features, exoskeletons are usually equipped with Human-Machine Interfaces (HMIs), allowing users to interact with the system, both physically and cognitively. The current paper critically reviews the state of the art of HMIs, and discusses the future challenges concerning Human Factors issues associated with the experience of utilisation of HMIs for wearable assistive exoskeletons in neuromotor rehabilitation settings. An overview of extant types of rehabilitative exoskeletons’ HMIs is provided, as well as a discussion on novel user experience research questions posed in light of the recent developments in the field.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 349.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 449.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. Exoskeleton Report. https://exoskeletonreport.com

  2. De Rossi, S.M.M., Vitiello, N., Lenzi, T., Ronsse, R., Koopman, B., Persichetti, A., Vecchi, F., Ijspeert, A.J., Van der Kooij, H., Carrozza, M.C.: Sensing pressure distribution on a lower-limb exoskeleton physical human-machine interface. Sensors 11(1), 207–227 (2011)

    Article  Google Scholar 

  3. Yandell, M.B., Quinlivan, B.T., Popov, D., Walsh, C., Zelik, K.E.: Physical interface dynamics alter how robotic exosuits augment human movement: implications for optimizing wearable assistive devices. J. Neuroeng. Rehabil. 14(40), 1–11 (2017)

    Google Scholar 

  4. Levesque, L., Pardoel, S., Lovrenovic, Z., Doumit, M.: Experimental comfort assessment of an active exoskeleton interface. In: 5th IEEE International Symposium on Robotics and Intelligent Sensors, pp. 38–43. IEEE Press, New York (2017)

    Google Scholar 

  5. Cappello, L., Binh, D.K., Yen, S.-C., Masia, L.: Design and preliminary characterization of a soft wearable exoskeleton for upper limb. In: 6th International Conference on Biomedical Robotics and Biomechatronics, pp. 623–630. IEEE Press, New York (2016)

    Google Scholar 

  6. Van der Grinten, M.P., Smitt, P.: Development of a practical method for measuring body part discomfort. Adv. Ind. Ergon. Saf. 4, 311–318 (1992)

    Google Scholar 

  7. Amirabdollahian, F., Ates, S., Basteris, A., Cesario, A., Buurke, J., Hermens, H., Hofs, D., Johansson, E., Mountain, G., Nasr, N., Nijenhuis, S.: Design, development and deployment of a hand/wrist exoskeleton for home-based rehabilitation after stroke - SCRIPT project. Robotica 32, 1331–1346 (2014)

    Article  Google Scholar 

  8. Chen, B., Ma, H., Qin, L.-Y., Guan, X., Chan, K.-M., Law, S.W., Qin, L., Liao, W.H.: Design of a lower extremity exoskeleton for motion assistance in paralyzed individuals. In: 8th Conference on Robotics and Biomimetics, pp. 144–149. IEEE Press, New York (2015)

    Google Scholar 

  9. Choi, H., Na, B., Lee, J., Kong, K.: A user interface system with see-through display for WalkON suit: a powered exoskeleton for complete paraplegics. Appl. Sci. 8, 2287 (2018)

    Article  Google Scholar 

  10. Walia, A.S., Kumar, N.: Powered lower limb exoskeleton featuring intuitive graphical user interface with analysis for physical rehabilitation progress. J. Sci. Ind. Res. 77, 342–344 (2018)

    Google Scholar 

  11. Baklouti, M., Monacelli, E., Guitteny, V., Couvet, S.: Intelligent assistive exoskeleton with vision based interface. In: International Conference on Smart Homes and Health Telematics, pp. 123–135. Springer, Berlin (2008)

    Google Scholar 

  12. Airò Farulla, G., Pianu, D., Cempini, M., Cortese, M., Russo, L.O., Indaco, M., Nerino, R., Chimienti, A., Oddo, C.M., Vitiello, N.: Vision-based pose estimation for robot-mediated hand telerehabilitation. Sensors 16, 208 (2016)

    Article  Google Scholar 

  13. Ianosi, A., Dimitrova, A., Noveanu, S., Tatar, O.M., Mândru, D.S.: Shoulder-elbow exoskeleton as rehabilitation exerciser. In: 7th International Conference on Advanced Concepts in Mechanical Engineering, vol. 147 (2016)

    Google Scholar 

  14. Lu, Z., Tong, K., Zhang, X.: Myoelectric pattern recognition for controlling a robotic hand: a feasibility study in stroke. IEEE Trans. Biomed. Eng. 66(2), 365–372 (2019)

    Article  Google Scholar 

  15. Al-Quraishi, M.S., Elamvazuthi, I., Daud, S.A., Parasuraman, S., Borboni, A.: EEG-based control for upper and lower limb exoskeletons and prostheses: a systematic review. Sensors 18, 3342 (2018)

    Article  Google Scholar 

  16. Frolov, A.A., Mokienko, O., Lyukmanov, R., Biryukova, E., Kotov, S., Turbina, L., Nadareyshvily, G., Bushkova, Y.: Post-stroke rehabilitation training with a motor-imagery-based Brain-Computer Interface (BCI)-controlled hand exoskeleton: a randomized controlled multicenter trial. Front. Neurosci. 11, 400 (2017)

    Article  Google Scholar 

  17. Crea, S., Nann, M., Trigili, E., Cordella, F., Baldoni, A., Turbina, L., Nadareyshvily, G., Bushkova, Y.: Feasibility and safety of shared EEG/EOG and vision-guided autonomous whole-arm exoskeleton control to perform activities of daily living. Sci. Rep. 8, 10823 (2018)

    Article  Google Scholar 

  18. Wang, K.-J., You, K., Chen, F., Huang, Z., Mao, Z.-H.: Human-machine interface using eye saccade and facial expression physiological signals to improve the maneuverability of wearable robots. In: International Symposium on Wearable & Rehabilitation Robotics. IEEE Press, New York (2017)

    Google Scholar 

  19. Kawase, T., Sakurada, T., Koike, Y., Kansaku, K.: A hybrid BMI-based exoskeleton for paresis: EMG control for assisting arm movements. J. Neural Eng. 14, 016015 (2017)

    Article  Google Scholar 

  20. Jochumsen, M., Cremoux, S., Robinault, L., Lauber, J., Arceo, J.C., Navid, M.S., Nedergaard, R.W., Rashid, U., Haavik, H., Niazi, I.K.: Investigation of optimal afferent feedback modality for inducing neural plasticity with a self-paced brain-computer interface. Sensors 18, 3761 (2018)

    Article  Google Scholar 

  21. Bouteraa, Y., Abdallah, I.B., Elmogy, A.M.: Training of hand rehabilitation using low cost exoskeleton and vision-based game interface. J. Intell. Robot. Syst. 96, 31–47 (2019)

    Article  Google Scholar 

  22. Hidayah, R., Chamarthy, S., Shah, A., Fitzgerald-Maguire, M., Agrawal, S.K.: Walking with augmented reality: a preliminary assessment of visual feedback with a cable-driven active leg exoskeleton (C-ALEX). IEEE Robot. Autom. Lett. 4(4), 3948–3954 (2019)

    Article  Google Scholar 

  23. Hu, J., Hou, Z.-G., Chen, Y., Peng, L., Peng, L.: Task-oriented active training based on adaptive impedance control with iLeg–A horizontal exoskeleton for lower limb rehabilitation. In: International Conference on Robotics and Biomimetics, pp. 2025–2030. IEEE Press, New York (2013)

    Google Scholar 

  24. Chowdhury, A., Meena, Y.K., Raza, H., Bhushan, B., Uttam, A.K., Pandey, N., Hashmi, A.A., Bajpai, A., Dutta, A., Prasad, G.: Active physical practice followed by mental practice BCI-driven hand exoskeleton: a pilot trial for clinical effectiveness and usability. IEEE J. Biomed. Health Inform. 22(6), 1786–1795 (2018)

    Article  Google Scholar 

  25. Ableitner, T., Soekadar, S., Strobbe, C., Schilling, A., Zimmermann, G.: Interaction techniques for a neural-guided hand exoskeleton. In: 8th International Conference on Current and Future Trends of Information and Communication Technologies in Healthcare, pp. 442–446. Elsevier, Amsterdam (2018)

    Google Scholar 

  26. López-Larraz, E., Trincado-Alonso, F., Rajasekaran, V., Pérez-Nombela, S., del-Ama, A.J., Aranda, J., Minguez, J., Gil-Agudo, A., Montesano, L.: Control of an ambulatory exoskeleton with a brain-machine interface for spinal cord injury gait rehabilitation. Front. Neurosci. 10, 359 (2016)

    Google Scholar 

  27. Simkins, M., Fedulow, I., Kim, H., Abrams, G., Byl, N., Rosen, J.: Robotic rehabilitation game design for chronic stroke. Games Health J. 1(6), 422–430 (2012)

    Article  Google Scholar 

  28. Gui, K., Liu, H., Zhang, D.: Toward multimodal human-robot interaction to enhance active participation of users in gait rehabilitation. IEEE Trans. Neur. Syst. Rehab. Eng. 25(11), 254–2066 (2017)

    Google Scholar 

  29. Sullivan, J.L., Bhagat, N.A., Yozbatiran, N., Paranjape, R., Losey, C.G., Grossman, R.G., Contreras-Vidal, J.L., Francisco, G.E., O’Malley, M.K.: Improving robotic stroke rehabilitation by incorporating neural intent detection: preliminary results from a clinical trial. In: International Conference on Rehabilitation Robotics, pp. 122–127. IEEE Press, New York (2017)

    Google Scholar 

  30. Liu, D., Chen, W., Pei, Z., Wang, J.: A brain-controlled lower-limb exoskeleton for human gait training. Rev. Sci. Instrum. 88, 104302 (2017)

    Article  Google Scholar 

  31. Costa, Á., Asín-Prieto, G., González-Vargas, J., Iáñez, E., Moreno, J.C., Del-Ama, A.J., Gil-Agudo, Á., Azorín, J.M.: Attention level measurement during exoskeleton rehabilitation through a BMI system. In: Wearable Robotics: Challenges and Trends, Biosystem & Biorobotics, pp. 243–247. Springer, Cham (2017)

    Google Scholar 

  32. Sarter, N.B., Woods, D.D.: How in the world did we ever get into that mode? Mode error and awareness in supervisory control. Hum. Fact. 37(1), 5–19 (1995)

    Article  Google Scholar 

  33. Hancock, P.A., Billings, D.R., Schaefer, K.E., Chen, J.Y.C., de Visser, E.J., Parasuraman, R.: A meta-analysis of factors affecting trust in human-robot interaction. Hum. Factors 53(5), 517–527 (2011)

    Article  Google Scholar 

  34. Benabid, A.L., Costecalde, T., Eliseyev, A., Charvet, G., Verney, A., Karakas, S., Foerster, M., Lambert, A., Morinière, B., Abroug, N., Schaeffer, M.C.: An exoskeleton controlled by an epidural wireless brain-machine interface in a tetraplegic patient: a proof-of-concept demonstration. Lancet Neurol. 18, 1112–1122 (2019)

    Article  Google Scholar 

Download references

Acknowledgments

This paper has received funding from the European Union’s Horizon 2020 research and innovation programme, via an Open Call issued and executed under Project EUROBENCH (gran agreement N° 779963). http://eurobench2020.eu.

Author information

Authors and Affiliations

  1. Department of Psychology, University of Bologna, Via Filippo Re 10, 40126, Bologna, Italy

    Davide Giusino, Federico Fraboni, Giuseppe Rainieri, Marco De Angelis, Annagrazia Tria, Laura Maria Alessandra La Bara & Luca Pietrantoni

  2. Interdepartmental Centre for Industrial Research in Advanced Mechanical Engineering Applications and Materials Technology, University of Bologna, Via Zamboni 18, 40126, Bologna, Italy

    Davide Giusino, Laura Maria Alessandra La Bara & Luca Pietrantoni

Authors
  1. Davide Giusino
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Federico Fraboni
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Giuseppe Rainieri
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Marco De Angelis
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Annagrazia Tria
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Laura Maria Alessandra La Bara
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Luca Pietrantoni
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Davide Giusino .

Editor information

Editors and Affiliations

  1. Institute for Advanced Systems Engineering, University of Central Florida, Orlando, FL, USA

    Tareq Ahram

  2. Campus du Moulin de la Housse, Université de Reims Champagne Ardenne GRESPI, Reims Cedex, France

    Redha Taiar

  3. Département de l’appareil locomoteur, Champ de l’Air, Centre Hospitalier Universitaire Vaudois (CHUV), Lausanne, Switzerland

    Vincent Gremeaux-Bader

  4. Laboratory of Movement Analysis and Measurement, École Polytechnique Fédérale de Lausanne, Lausanne, Switzerland

    Kamiar Aminian

Rights and permissions

Reprints and permissions

Copyright information

© 2020 The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Giusino, D. et al. (2020). Human Factors in Interfaces for Rehabilitation-Assistive Exoskeletons: A Critical Review and Research Agenda. In: Ahram, T., Taiar, R., Gremeaux-Bader, V., Aminian, K. (eds) Human Interaction, Emerging Technologies and Future Applications II. IHIET 2020. Advances in Intelligent Systems and Computing, vol 1152. Springer, Cham. https://doi.org/10.1007/978-3-030-44267-5_53

Download citation

  • DOI: https://doi.org/10.1007/978-3-030-44267-5_53

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-44266-8

  • Online ISBN: 978-3-030-44267-5

  • eBook Packages: EngineeringEngineering (R0)

Publish with us

Policies and ethics

Search

Navigation