Skip to main content
SpringerLink
Log in

Assessment of Daily-Life Reaching Performance After Stroke

  • Published:
Annals of Biomedical Engineering Aims and scope Submit manuscript

Abstract

For an optimal guidance of the rehabilitation therapy of stroke patients in an in-home setting, objective, and patient-specific performance assessment of arm movements is needed. In this study, metrics of hand movement relative to the pelvis and the sternum were estimated in 13 stroke subjects using a full body ambulatory movement analysis system, including 17 inertial sensors integrated in a body-worn suit. Results were compared with the level of arm impairment evaluated with the upper extremity part of the Fugl-Meyer Assessment scale (uFMA). Metrics of arm movement performance of the affected side, including size of work area, maximum reaching distance and movement range in vertical direction, were evaluated during a simulated daily-life task. These metrics appeared to strongly correlate with uFMA scores. Using this body-worn sensor system, metrics of the performance of arm movements can easily be measured and evaluated while the subject is ambulating in a simulated daily-life setting. Suggested metrics can be used to objectively assess the performance of the arm movements over a longer period in a daily-life setting. Further development of the body-worn sensing system is needed before it can be unobtrusively used in a daily-life setting.

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

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Figure 1
Figure 2
Figure 3

Similar content being viewed by others

Abbreviations

uFMA:

Upper extremity part of the Fugl-Meyer assessment scale (0–66 points)

IMU:

Inertial measurement unit

References

  1. Bergmann, J. H. M., and A. H. McGregor. Body-worn sensor design: what do patients and clinicians want? Ann. Biomed. Eng. 39:2299–2312, 2011.

    Article  CAS  PubMed  Google Scholar 

  2. Bussmann, J. B. J., W. L. J. Martens, J. H. M. Tulen, F. C. Schasfoort, H. J. G. Van Den Berg-Emons, and H. J. Stam. Measuring daily behavior using ambulatory accelerometry: the Activity Monitor. Behav. Res. Methods. Instrum. Comput. 33:349–356, 2001.

    Article  CAS  PubMed  Google Scholar 

  3. Cirstea, M. C., and L. F. Mindy. Compensatory strategies for reaching in stroke. Brain 123:940–953, 2000.

    Article  PubMed  Google Scholar 

  4. de los Reyes-Guzmán, A., I. Dimbwadyo-Terrer, F. Trincado-Alonso, F. Monasterio-Huelin, D. Torricelli, and A. Gil-Agudo. Quantitative assessment based on kinematic measures of functional impairments during upper extremity movements: a review. Clin. Biomech. 29:719–727, 2014.

    Article  Google Scholar 

  5. Dewald, J. P. A., V. Sheshadri, M. L. Dawson, and R. F. Beer. Upper-limb discoordination in hemiparetic stroke: implications for neurorehabilitation. Top Stroke Rehabil. 8:1–12, 2001.

    CAS  PubMed  Google Scholar 

  6. Dipietro, L., H. I. Krebs, S. E. Fasoli, B. T. Volpe, J. Stein, C. Bever, and N. Hogan. Changing motor synergies in chronic stroke. J. Neurophysiol. 98:757–768, 2007.

    Article  CAS  PubMed  Google Scholar 

  7. Ellis, M. D., T. Sukal, T. DeMott, and J. P. A. Dewald. Augmenting clinical evaluation of hemiparetic arm movement with a laboratory-based quantitative measurement of kinematics as a function of limb loading. Neurorehabil. Neural Repair 22:321–329, 2008.

    Article  PubMed Central  PubMed  Google Scholar 

  8. Ellis, M. D., T. Sukal-Moulton, and J. P. A. Dewald. Progressive shoulder abduction loading is a crucial element of arm rehabilitation in chronic stroke. Neurorehabil. Neural Repair 23:862–869, 2009.

    Article  PubMed Central  PubMed  Google Scholar 

  9. Fugl-Meyer, A. R., L. Jääskö, I. Leyman, S. Olsson, and S. Steglind. The post-stroke hemiplegic patient. 1. A method for evaluation of physical performance. Scand. J. Rehabil. Med. 7:13–31, 1975.

    CAS  PubMed  Google Scholar 

  10. Geyh, S., A. Cieza, J. Schouten, H. Dickson, P. Frommelt, Z. Omar, N. Kostanjsek, H. Ring, and G. Stucki. ICF Core Sets for stroke. J. Rehabil. Med. 36:135–141, 2004.

    Article  Google Scholar 

  11. Giansanti, D., V. Macellari, G. Maccioni, and V. Macellari. The development and test of a device for the reconstruction of 3-D position and orientation by means of a kinematic sensor assembly with rate gyroscopes and accelerometers. IEEE Trans. Biomed. Eng. 52:1271–1277, 2005.

    Article  PubMed  Google Scholar 

  12. Kamper, D. G., A. N. McKenna-Cole, L. E. Kahn, and D. J. Reinkensmeyer. Alterations in reaching after stroke and their relation to movement direction and impairment severity. Arch. Phys. Med. Rehabil. 83:702–707, 2002.

    Article  PubMed  Google Scholar 

  13. Kollen, B., G. Kwakkel, and E. Lindeman. Functional recovery after stroke: a review of current developments in stroke rehabilitation research. Rev. Recent. Clin. Trials. 1:75–80, 2006.

    Article  PubMed  Google Scholar 

  14. Krabben, T., B. I. Molier, A. Houwink, J. S. Rietman, J. H. Buurke, and G. B. Prange. Circle drawing as evaluative movement task in stroke rehabilitation: an explorative study. J. Neuroeng. Rehabil. 8:15, 2011.

    Article  PubMed Central  PubMed  Google Scholar 

  15. Lorussi, F., S. Galatolo, R. Bartalesi, and D. De Rossi. Modeling and characterization of extensible wearable textile-based electrogoniometers. IEEE Sens. J. 13:217–228, 2013.

    Article  Google Scholar 

  16. Luinge, H. J., and P. H. Veltink. Measuring orientation of human body segments using miniature gyroscopes and accelerometers. Med. Biol. Eng. Comput. 43:273–282, 2005.

    Article  CAS  PubMed  Google Scholar 

  17. Lyle, R. C. A performance test for assessment of upper limb function in physical rehabilitation treatment and research. Int. J. Rehabil. Res. 4:483–492, 1981.

    Article  CAS  PubMed  Google Scholar 

  18. Merdler, T., D. G. Liebermann, M. F. Levin, and S. Berman. Arm-plane representation of shoulder compensation during pointing movements in patients with stroke. J. Electromyogr. Kinesiol. 23:938–947, 2013.

    Article  PubMed  Google Scholar 

  19. Murphy, M. A., C. Willén, and K. S. Sunnerhagen. Kinematic variables quantifying upper-extremity performance after stroke during reaching and drinking from a glass. Neurorehabil. Neural. Repair. 25:71–80, 2011.

    Article  Google Scholar 

  20. Pérez, R., Ú. Costa, M. Torrent, J. Solana, E. Opisso, C. Cáceres, J. M. Tormos, J. Medina, and E. J. Gómez. Upper limb portable motion analysis system based on inertial technology for neurorehabilitation purposes. Sensors 10:10733–10751, 2010.

    Article  PubMed Central  PubMed  Google Scholar 

  21. Roetenberg, D., P. J. Slycke, and P. H. Veltink. Ambulatory position and orientation tracking fusing magnetic and inertial sensing. IEEE Trans. Biomed. Eng. 54:883–890, 2007.

    Article  PubMed  Google Scholar 

  22. Roetenberg, D., H. Luinge, and P. Slycke. Xsens MVN: full 6DOF Human Motion Tracking Using Miniature Inertial Sensors. Xsens Motion Technologies BV, Technical Report,s 2009.

  23. Roorda, L. D., A. Houwink, W. Smits, I. W. Molenaar, and A. C. Geurts. Measuring upper limb capacity in post stroke patients: development, fit of the monotone homogeneity model, unidimensionality, fit of the double monotonicity model, differential item functioning, internal consistency, and feasibility of the stroke upper limb capacity scale, SULCS. Arch. Phys. Med. Rehabil. 92:214–227, 2011.

    Article  PubMed  Google Scholar 

  24. Subramanian, S. K., J. Yamanaka, G. Chilingaryan, and M. F. Levin. Validity of movement pattern kinematics as measures of arm motor impairment poststroke. Stroke 41:2303–2308, 2010.

    Article  PubMed  Google Scholar 

  25. Sunderland, A., D. J. Tinson, E. L. Bradley, D. F. Hewer, and D. T. Wade. Enhanced physical therapy improves recovery of arm function after stroke: a randomized controlled trial. J. Neurol. Neurosurg. Psychiatr. 55:530–535, 1992.

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  26. Thies, S. B., P. A. Tresadern, L. P. Kenney, J. Smith, D. Howard, J. Y. Goulermas, C. Smith, and J. Rigby. Movement variability in stroke patients and controls performing two upper limb functional tasks: a new assessment methodology. J. Neuroeng. Rehabil. 6:1–12, 2009.

    Article  Google Scholar 

  27. Uswatte, G., W. L. Foo, H. Olmstead, K. Lopez, A. Holand, and L. B. Simms. Ambulatory monitoring of arm movement using accelerometry: an objective measure of upper-extremity rehabilitation in persons with chronic stroke. Arch. Phys. Med. Rehabil. 86:1498–1501, 2005.

    Article  PubMed  Google Scholar 

  28. van Dokkum, L., I. Hauret, D. Mottet, J. Froger, J. Métrot, and I. Laffont. The contribution of kinematics in the assessment of upper limb motor recovery early after stroke. Neurorehabil. Neural Repair 28:4–12, 2014.

    Article  PubMed  Google Scholar 

  29. Veltink, P. H., F. B. van Meulen, B. J. F. van Beijnum, B. Klaassen, H. J. Hermens, E. Droog, M. Weusthof, F. Lorussi, A. Tognetti, J. Reenalda, C. D. M. Nikamp, C. Baten, J. H. Buurke, J. Held, A. Luft, H. Luinge, G. De Toma, C. Mancusso, R. Paradiso. Daily-life tele-monitoring of motor performance in stroke survivors. 13th International Symposium on 3D Analysis of Human Movement, 3D-AHM 2014, 14-17 July 2014, Lausanne, Switzerland. Extended abstract pp. 159–162, 2014.

  30. Wagner, J. M., J. A. Rhodes, and C. Patten. Reproducibility and minimal detectable change of three-dimensional kinematic analysis of reaching tasks in people with hemiparesis after stroke. Phys. Therapy 88:652–663, 2008.

    Article  Google Scholar 

  31. Zheng, H., N. D. Black, and N. D. Harris. Position-sensing technologies for movement analysis in stroke rehabilitation. Med. Biol. Eng. Comput. 43:413–420, 2005.

    Article  CAS  PubMed  Google Scholar 

Download references

Acknowledgments

The authors would like to thank Dirk Weenk for his assistance in data collection of this study and all participants of the clinical trial. This study is part of the INTERACTION project, which is partially funded by the European Commission under the 7th Framework Programme (FP7-ICT-2011-7-287351).

Author information

Authors and Affiliations

  1. Biomedical Signals and Systems, MIRA - Institute for Biomedical Technology and Technical Medicine, University of Twente, PO Box 217, 7500 AE, Enschede, The Netherlands

    Fokke B. van Meulen, Jasper Reenalda, Jaap H. Buurke & Peter H. Veltink

  2. Roessingh Research and Development, Roessingh Rehabilitation Hospital, Roessinghsbleekweg 33b, 7522 AH, Enschede, The Netherlands

    Jasper Reenalda & Jaap H. Buurke

Authors
  1. Fokke B. van Meulen
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Jasper Reenalda
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Jaap H. Buurke
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Peter H. Veltink
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Fokke B. van Meulen.

Additional information

Associate Editor Amit Gefen oversaw the review of this article.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

van Meulen, F.B., Reenalda, J., Buurke, J.H. et al. Assessment of Daily-Life Reaching Performance After Stroke. Ann Biomed Eng 43, 478–486 (2015). https://doi.org/10.1007/s10439-014-1198-y

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10439-014-1198-y

Keywords

Search

Navigation