Skip to main content
SpringerLink
Log in

User-Centered Design of Cues with Smart Glasses for Gait Rehabilitation in People with Parkinson’s Disease: A Methodology for the Analysis of Human Requirements and Cues Effectiveness

  • Conference paper
  • First Online:
Advances in Simulation and Digital Human Modeling (AHFE 2021)

Part of the book series: Lecture Notes in Networks and Systems ((LNNS,volume 264))

Included in the following conference series:

Abstract

As an alternative to the technical industrial mindset, User-Centered Design has proven to be an effective tool to realize products and services for the Healthcare sector. In this scenario, this project aims to develop an innovative wearable gait rehabilitation solution obtained by integrating the Smart Glasses Vuzix Blade into the smartphone-based CuPiD-system. The specific aims of the testing phase described in this paper were to observe how submitted visual, auditory, and vibratory cues influence the user’s gait; and which were the most impacting and efficient typologies of cues. To achieve these results, we analyze the users’ qualitative and quantitative feedback, respectively obtained from an interview and a specific gait analysis protocol.

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 129.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 169.99
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. Jämsén, A., Kukkonen, T.: Age-friendly society supports active ageing. In: Publications of Karelia University of Applied Sciences B, Handbooks and Article collections: 63, Karelia University of Applied Sciences (2020)

    Google Scholar 

  2. Pakulski, J.: Facing the challenges of an ageing society. In: Kendig, H., McDonald, P., Piggott, J. (eds.) Population Ageing and Australia’s Future, pp. 111–134. Anu Press, Australia (2016)

    Google Scholar 

  3. ActiveAdvice: What is Smart Health and How do People Benefit?. https://www.activeadvice.eu/news/concept-projects/what-is-smart-health-and-how-do-people-benefit/

  4. Farahani, B., Firouzi, F., Chang, V., Badaroglu, M., Constant, N., Mankodiya, K.: Towards fog-driven IoT eHealth: promises and challenges of IoT in medicine and healthcare. Future Gen. Comput. Syst. 78, 659–676 (2018)

    Article  Google Scholar 

  5. Van Gemert-Pijnen, J.E., et al.: A holistic framework to improve the uptake and impact of eHealth technologies. J. Med. Internet Res. 13(4), e111 (2011)

    Google Scholar 

  6. Imbesi, S., Mincolelli, G.: Design of smart devices for older people: a user centered approach for the collection of users’ needs. In: Ahram, T., Karwowski, W., Vergnano, A., Leali, F., Taiar, R. (eds.) IHSI 2020. AISC, vol. 1131, pp. 860–864. Springer, Cham (2020). https://doi.org/10.1007/978-3-030-39512-4_131

    Chapter  Google Scholar 

  7. Peterson, D.S., Horak, F.B.: Neural control of walking in people with parkinsonism. Physiology, 31(2), 95–107 (2015)

    Google Scholar 

  8. Hobert, M.A., Nussbaum, S., Heger, T., Berg, D., Maetzler, W., Heinzel, S.: Progressive gait deficits in parkinson’s disease: a wearable-based biannual 5-year prospective study. Front. Aging Neurosci. 11, 22 (2019)

    Google Scholar 

  9. Lee, S.J., Yoo, J.Y., Ryu, J.S., Park, H.K., Park, H.K., Chung, S.J.: The effects of visual and auditory cues on freezing of gait in patients with Parkinson disease. Am. J. Phys. Med. Rehabil. 91(1), 2–11 (2012)

    Google Scholar 

  10. Morris, M.E.: Locomotor training in people with Parkinson disease. Phys. Ther. 86(10), 1426–1435 (2006)

    Google Scholar 

  11. Ferrazzoli, D., Ortelli, P., Madeo, G., Giladi, N., Petzinger, G.M., Frazzitta, G.: Basal ganglia and beyond: the interplay between motor and cognitive aspects in Parkinson’s disease rehabilitation’. Neurosci. Biobehav. Rev. 90, 294–308 (2018)

    Google Scholar 

  12. Redgrave, P., et al.: Goal-directed and habitual control in the basal ganglia: implications for Parkinson’s disease. Nat. Rev. Neurosci. 11(11), 760–772 (2010)

    Google Scholar 

  13. Rubinstein, T.C., Giladi, N., Hausdorff, J.M.: The power of cueing to circumvent dopamine deficits: a review of physical therapy treatment of gait disturbances in Parkinson’s disease. Mov. Disord. 17(6), 1148–1160 (2002)

    Article  Google Scholar 

  14. Rocha, P.A., Porfírio, G.M., Ferraz, H.B., Trevisani, H.B.: Effects of external cues on gait parameters of Parkinson’s disease patients: a systematic review. Clin. Neurol. Neurosurg. 124, 127–134 (2014)

    Google Scholar 

  15. Lim, I., et al.: Effects of external rhythmical cueing on gait in patients with Parkinson’s disease: a systematic review. Clin. Rehabil. 19 (7), 695–713 (2005)

    Google Scholar 

  16. Sánchez-Ferro, Á., Maetzler, W.: Advances in sensor and wearable technologies for Parkinson’s disease. Mov. Disord. 31(9), 1257 (2016)

    Article  Google Scholar 

  17. Casamassima, F., Ferrari, A., Milosevic, B., Ginis, P., Farella, E., Rocchi, L.: A wearable system for gait training in subjects with Parkinson’s disease. Sensors 14(4), 6229–6246 (2014)

    Google Scholar 

  18. Ginis, P., et al.: Feasibility and effects of home-based smartphone-delivered automated feedback training for gait in people with Parkinson’s disease: a pilot randomized controlled trial’. Parkinsonism Rel. Disord. 22, 28–34 (2016)

    Google Scholar 

  19. Ferrari, A., Ginis, P., Nieuwboer, A., Greenlaw, R., Muddiman, A., Chiari, L.: Handling gait impairments of persons with parkinson’s disease by means of real-time biofeedback in a daily life environment. In: Chang, C.K., Chiari, L., Cao, Y., Jin, H., Mokhtari, M., Aloulou, H. (eds.) ICOST 2016. LNCS, vol. 9677, pp. 250–261. Springer, Cham (2016). https://doi.org/10.1007/978-3-319-39601-9_22

    Chapter  Google Scholar 

  20. Peterson, D.S., Smulders, K.: Cues and attention in parkinsonian gait: potential mechanisms and future directions. Front. Neurol. 6, 255 (2015)

    Google Scholar 

  21. Shams, L., Seitz, A.R.: Benefits of multisensory learning. Trends Cogn. Sci. 12(11), 411–417 (2008)

    Google Scholar 

  22. Davidsdottir, S., Cronin-Golomb, A., Lee, A.: Visual and spatial symptoms in Parkinson’s disease. Vis. Res. 45(10), 1285–1296 (2005)

    Google Scholar 

  23. Wiederhold, B.K.: Time to port augmented reality health apps to smart glasses? Cyberpsychol. Behav. Soc. Netw. 16(3), 157–158 (2013)

    Google Scholar 

  24. McNaney, R., et al.: Exploring the acceptability of google glass as an everyday assistive device for people with parkinson’s. In: Proceedings of the 32nd annual ACM conference on Human factors in computing systems - CHI 2014, Toronto, Ontario, Canada, pp. 2551–2554 (2014)

    Google Scholar 

  25. ‘Vuzix Blade®’. https://www.vuzix.com/products/blade-smart-glasses. Accessed 03 Dec 2020

  26. Assessment - mTEST3, mHealth Technologies. http://mhealthtechnologies.it/products-wearable-sensors-smartphone-apps/assessment-mtest3/. Accessed 05 Feb 2021

  27. Ginis, P., Heremans, E., Ferrari, A., Dockx, K., Canning, C.G., Nieuwboer, A.: Prolonged walking with a wearable system providing intelligent auditory input in people with parkinson’s disease. Front. Neurol. 8, 128 (2017)

    Article  Google Scholar 

  28. Ginis, P., et al.: Feasibility and effects of home-based smartphone-delivered automated feedback training for gait in people with Parkinson’s disease: a pilot randomized controlled trial. Parkinsonism Rel. Disord. 22, 28–34 (2016)

    Article  Google Scholar 

  29. Tudor-Locke, C., Han, H., Aguiar, E.J., et al.: How fast is fast enough? walking cadence (steps/min) as a practical estimate of intensity in adults: a narrative review Br. J. Sports Med. 52, 776–788 (2018)

    Google Scholar 

  30. Amblard, B., Cremieux, J., Marchand, A.R., Carblanc, A.: Lateral orientation and stabilization of human stance: static versus dynamic visual cues. Exp. Brain Res. 61, 21–37 (1985)

    Article  Google Scholar 

  31. Prokop, T., Schubert, M., Berger, M.: Visual influence on human locomotion modulation to changes in optic flow. Exp. Brain Res. 114, 63–70 (1997)

    Article  Google Scholar 

  32. Winfree, K.N., Pretzer-Aboff, I., Hilgart, D., et al.: The effect of step-synchronized vibration on patients with Parkinson’s disease: case studies on subjects with freezing of gait or an implanted deep brain stimulator. In: IEEE Transactions on Neural Systems and Rehabilitation Engineering: a Publication of the IEEE Engineering in Medicine and Biology Society, vol. 21, no. 5, pp. 806–811 (2013)

    Google Scholar 

  33. Woerd, E.S., Oostenveld, R., Bloem, B.R., Lange, F.P., Praamstra, P.: Effects of rhythmic stimulus presentation on oscillatory brain activity: the physiology of cueing in Parkinson’s disease. NeuroImage: Clin. 9, 300–309 (2015)

    Google Scholar 

  34. Moore, E., Schaefer, R.S., Bastin, M.E., Roberts, N., Overy, K.: Diffusion tensor MRI tractography reveals increased fractional anisotropy (FA) in arcuate fasciculus following music-cued motor training. Brain Cogn. 116, 40–46 (2017)

    Article  Google Scholar 

  35. Thaut, M.H.: Neurologic music therapy in cognitive rehabilitation. Music Percept. 27(4), 281–285 (2010)

    Google Scholar 

  36. Iosa, M., et al.: The golden ratio of gait harmony: repetitive proportions of repetitive gait phases. BioMed Res. Int. 918642, 7 (2013)

    Google Scholar 

  37. Dozza, M., Horak, F.B., Chiari, L.: Auditory biofeedback substitutes for loss of sensory information in maintaining stance. Exper. Brain Res. 178(1), 37–48 (2007)

    Article  Google Scholar 

  38. Maetzler, W., Nieuwhof, F., Hasmann, S.E., Bloem, B.R.: Emerging therapies for gait disability and balance impairment: promises and pitfalls. Mov. Disord. 28, 1576–1586 (2013)

    Article  Google Scholar 

  39. Monje, M.H.G., Foffani, G., Obeso, J., Sánchez-Ferro, Á.: New sensor and wearable technologies to aid in the diagnosis and treatment monitoring of parkinson’s disease. Ann. Rev. Biomed. Eng. 21(1), 111–143 (2019)

    Google Scholar 

  40. Dorsey, E.R., et al.: Moving Parkinson care to the home, Mov. Disord. 31(9), 1258–1262 (2016)

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Department of Architecture, University of Ferrara, Via della Ghiara 36, 44123, Ferrara, Italy

    Silvia Imbesi, Filippo Petrocchi & Giuseppe Mincolelli

  2. Department of Electrical, Electronic, and Information Engineering, University of Bologna, Bologna, Italy

    Mattia Corzani & Lorenzo Chiari

  3. IRCCS Istituto delle Scienze Neurologiche di Bologna, Bologna, Italy

    Giovanna Lopane

Authors
  1. Silvia Imbesi
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Mattia Corzani
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Filippo Petrocchi
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Giovanna Lopane
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Lorenzo Chiari
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Giuseppe Mincolelli
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Silvia Imbesi .

Editor information

Editors and Affiliations

  1. U.S. Army Research Laboratory, Orlando, FL, USA

    Julia L. Wright

  2. Soar Tech, Orlando, FL, USA

    Daniel Barber

  3. Department of Product Development, University of Antwerp, Antwerp, Belgium

    Sofia Scataglini

  4. Biomedical Research and Environmental, NASA Lyndon Johnson Space Center, Houston, TX, USA

    Sudhakar L. Rajulu

Ethics declarations

At this link, there are all the cues described in this paper and the tables of the parameters obtained from the tests.

https://drive.google.com/drive/folders/1qQU0cwB9wR8wnMF0–5fyy0CXpRBa-81?usp=sharing

Rights and permissions

Reprints and permissions

Copyright information

© 2021 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

Imbesi, S., Corzani, M., Petrocchi, F., Lopane, G., Chiari, L., Mincolelli, G. (2021). User-Centered Design of Cues with Smart Glasses for Gait Rehabilitation in People with Parkinson’s Disease: A Methodology for the Analysis of Human Requirements and Cues Effectiveness. In: Wright, J.L., Barber, D., Scataglini, S., Rajulu, S.L. (eds) Advances in Simulation and Digital Human Modeling. AHFE 2021. Lecture Notes in Networks and Systems, vol 264. Springer, Cham. https://doi.org/10.1007/978-3-030-79763-8_42

Download citation

Publish with us

Policies and ethics

Search

Navigation