Skip to main content
SpringerLink
Log in
Book cover

Human Behavior Understanding pp 146–159Cite as

Activity Patterns in Stroke Patients - Is There a Trend in Behaviour During Rehabilitation?

  • Conference paper
  • First Online:

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 9277))

Abstract

We describe stroke patients’ activity patterns and trends based on motion data acquired during their stay in an ambulatory day-care centre. Our aim was to explore and quantify intensity and development in the patients’ activity patterns as these may change during the rehabilitation process. We analyse motion data recordings from wearable inertial measurement units of eleven patients up to eleven days, totally 102 recording days. Using logic rules, we extract activity primitives, including affected arm move, sit, stand, walking, etc. from selected channels of the continuous median-filtered sensor data. Using relative duration of the activity primitives, we examine patient activity patterns regarding independence in mobility, distribution of walking over the days and trends in using the affected body side. Due to the heterogeneity of patients’ behaviour, we focused on analysing patient-specific activity patterns. Our exploration showed that the rule-based activity primitive analysis is beneficial to understand individual patient activity.

This is a preview of subscription content, 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   34.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD   44.99
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

Learn about institutional subscriptions

References

  1. Bourbonnais, D., Noven, S.V.: Weakness in patients with hemiparesis. Am. J. Occup. Ther. 43(5), 313–319 (1989). http://dx.doi.org/10.5014/ajot.43.5.313

    Article  Google Scholar 

  2. Burns, A., Greene, B.R., McGrath, M.J., OShea, T.J., Kuris, B., Ayer, S.M., Stroiescu, F., Cionca, V.: Shimmer ™- a wireless sensor platform for noninvasive biomedical research. IEEE Sens. J. 10(9), 1527–1534 (2010). http://dx.doi.org/10.1109/JSEN.2010.2045498

    Article  Google Scholar 

  3. Cirstea, M.C.: Compensatory strategies for reaching in stroke. Brain 123(5), 940–953 (2000). http://dx.doi.org/10.1093/brain/123.5.940

    Article  Google Scholar 

  4. Del Din, S., Patel, S., Cobelli, C., Bonato, P.: Estimating fugl-meyer clinical scores in stroke survivors using wearable sensors. In: 2011 Annual International Conference of the IEEE Engineering in Medicine and Biology Society, August 2011. http://dx.doi.org/10.1109/IEMBS.2011.6091444

  5. Di Fabio, R.P., Badke, M.B., Duncan, P.W.: Adapting human postural reflexes following localized cerebrovascular lesion: analysis of bilateral long latency responses. Brain Res. 363(2), 257–264 (1986)

    Article  Google Scholar 

  6. Fugl-Meyer, A.R., Jääskö, L., Leyman, I., Olsson, S., Steglind, S.: The post-stroke hemiplegic patient. 1. a method for evaluation of physical performance. Scand. J. Rehabil. Med. 7(1), 13–31 (1974). http://www.neurophys.gu.se/digitalAssets/1328/1328802_the_post-stroke-hemiplegic_patient.pdf

    Google Scholar 

  7. Gietzelt, M., Wolf, K., Kohlmann, M., Marschollek, M., Haux, R., et al.: Measurement of accelerometry-based gait parameters in people with and without dementia in the field. Meth. Inf. Med. 52(4), 319–325 (2013)

    Article  Google Scholar 

  8. Hine, N., Judson, A., Ashraf, S.N., Arnott, J., Sixsmith, A., Brown, S., Garner, P.: Modelling the behaviour of elderly people as a means of monitoring well being. In: Ardissono, L., Brna, P., Mitrović, A. (eds.) UM 2005. LNCS (LNAI), vol. 3538, pp. 241–250. Springer, Heidelberg (2005). http://dx.doi.org/10.1007/11527886_32

    Chapter  Google Scholar 

  9. Iosa, M., Fusco, A., Morone, G., Pratesi, L., Coiro, P., Venturiero, V., De Angelis, D., Bragoni, M., Paolucci, S.: Assessment of upper-body dynamic stability during walking in patients with subacute stroke. J. Rehabil. Res. Dev. 49(3), 439–450 (2012)

    Article  Google Scholar 

  10. Knorr, B., Hughes, R., Sherrill, D., Stein, J., Akay, M., Bonato, P.: Quantitative measures of functional upper limb movement in persons after stroke. In: Conference Proceedings of the 2nd International IEEE EMBS Conference on Neural Engineering (2005). http://dx.doi.org/10.1109/CNE.2005.1419604

  11. Murphy, T.H., Corbett, D.: Plasticity during stroke recovery: from synapse to behaviour. Nat. Rev. Neurosci. 10(12), 861–872 (2009). http://www.nature.com/nrn/journal/v10/n12/pdf/nrn2735.pdf

    Article  Google Scholar 

  12. Parnandi, Wade, E., Mataric, M.: Motor function assessment using wearable inertial sensors. In: 2010 Annual International Conference of the IEEE on Engineering in Medicine and Biology Society (EMBC), pp. 86–89 (2010). http://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=5626156

  13. Patel, S., Hughes, R., Hester, T., Stein, J., Akay, M., Dy, J., Bonato, P.: A novel approach to monitor rehabilitation outcomes in stroke survivors using wearable technology. Proc. IEEE 98(3), 450–461 (2010). http://dx.doi.org/10.1109/JPROC.2009.2038727

    Article  Google Scholar 

  14. Rashidi, P., Cook, D.J., Holder, L.B., Schmitter-Edgecombe, M.: Discovering activities to recognize and track in a smart environment. IEEE Trans. Knowl. Data Eng. 23(4), 527–539 (2011). http://dx.doi.org/10.1109/TKDE.2010.148

    Article  Google Scholar 

  15. Robben, S., Pol, M., Kröse, B.: Longitudinal ambient sensor monitoring for functional health assessments: a case study. In: Proceedings of the 2014 ACM International Joint Conference on Pervasive and Ubiquitous Computing: Adjunct Publication, UbiComp 2014 Adjunct, pp. 1209–1216. ACM, New York (2014). http://doi.acm.org/10.1145/2638728.2638812

  16. Salah, A.A., Morros, R., Luque, J., Segura, C., Hernando, J., Ambekar, O., Schouten, B., Pauwels, E.: Multimodal identification and localization of users in a smart environment. J. Multimodal User Interfaces 2(2), 75–91 (2008). http://dx.doi.org/10.1007/s12193-008-0008-y

    Article  Google Scholar 

  17. Seiderer, A., Hammer, S., Andre, E., Mayr, M., Rist, T.: Exploring digital image frames for lifestyle intervention to improve well-being of older adults. In: Proceedings of the 5th International Conference on Digital Health 2015 - DH 15 (2015). http://dx.doi.org/10.1145/2750511.2750514

  18. Seiter, J., Derungs, A., Schuster-Amft, C., Amft, O., Troester, G.: Daily life activity routine discovery in hemiparetic rehabilitation patients using topic models. Meth. Inf. Med. 54(2), 248–255 (2015). http://dx.doi.org/10.3414/ME14-01-0082

    Article  Google Scholar 

  19. Spina, G., Roberts, F., Weppner, J., Lukowicz, P., Amft, O.: Crntc+: a smartphone-based sensor processing framework for prototyping personal healthcare applications. In: 2013 7th International Conference on Pervasive Computing Technologies for Healthcare (PervasiveHealth), pp. 252–255, May 2013

    Google Scholar 

  20. Suryadevara, N., Mukhopadhyay, S.C., Wang, R., Rayudu, R.: Forecasting the behavior of an elderly using wireless sensors data in a smart home. Eng. Appl. Artif. Intell. 26(10), 2641–2652 (2013)

    Article  Google Scholar 

  21. Tabar, A.M., Keshavarz, A., Aghajan, H.: Smart home care network using sensor fusion and distributed vision-based reasoning. In: Proceedings of the 4th ACM international workshop on Video surveillance and sensor networks - VSSN 06 (2006). http://dx.doi.org/10.1145/1178782.1178804

  22. Wolf, S.L., Catlin, P.A., Ellis, M., Archer, A.L., Morgan, B., Piacentino, A.: Assessing wolf motor function test as outcome measure for research in patients after stroke. Stroke 32(7), 1635–1639 (2001)

    Article  Google Scholar 

Download references

Acknowledgements

We are thankful to the study participants and the therapists at the Reha Rheinfelden. This work was supported by the EU Marie Curie Network iCareNet, grant number 264738 and the Dutch Technology Foundation STW grant number 12184.

Author information

Authors and Affiliations

  1. ACTLab, Chair of Sensor Technology, University of Passau, Passau, Germany

    Adrian Derungs & Oliver Amft

  2. Wearable Computing Laboratory, ETH Zrich, Zürich, Switzerland

    Julia Seiter

  3. Research Department, Reha Rheinfelden, Rheinfelden, Switzerland

    Corina Schuster-Amft

Authors
  1. Adrian Derungs
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Julia Seiter
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Corina Schuster-Amft
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Oliver Amft
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Adrian Derungs .

Editor information

Editors and Affiliations

  1. Computer Engineering Dept, Bogazici University, Bebek, Istanbul, Turkey

    Albert Ali Salah

  2. HvA University of Applied Sciences, Amsterdam, Noord-Holland, The Netherlands

    Ben J.A. Kröse

  3. Washington State University, Pullman, Washington, USA

    Diane J. Cook

Rights and permissions

Reprints and permissions

Copyright information

© 2015 Springer International Publishing Switzerland

About this paper

Cite this paper

Derungs, A., Seiter, J., Schuster-Amft, C., Amft, O. (2015). Activity Patterns in Stroke Patients - Is There a Trend in Behaviour During Rehabilitation?. In: Salah, A., Kröse, B., Cook, D. (eds) Human Behavior Understanding. Lecture Notes in Computer Science(), vol 9277. Springer, Cham. https://doi.org/10.1007/978-3-319-24195-1_11

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-24195-1_11

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-24194-4

  • Online ISBN: 978-3-319-24195-1

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics

Search

Navigation