Skip to main content
SpringerLink
Log in

Analysis of Ankle Joint Motions for 12 Different Activities of Daily Living in the Elderly Using the Pattern Recognition Approach

  • Regular Paper
  • Published:
International Journal of Precision Engineering and Manufacturing Aims and scope Submit manuscript

Abstract

The characteristics of ankle joint motions in the elderly that arise from a wide range of activities of daily living (ADLs) have not been adequately assessed using a quantitative and objective pattern recognition approach. The current study aims to analyze the characteristics of ankle joint motions for 12 different ADLs in the elderly through the pattern recognition approach; this study also aims to identify whether this analysis technique is effective, quantitative and objective in understanding the characteristics of ankle joint motions. Fifty elderly participants performed 12 ADLs that were selected based on Katz’s ADL indicators. Inertial measurement units were used to measure the ankle joint motions, and their patterns and similarities were analyzed using the pattern recognition approach. The results identified the inherent ankle joint motion features for each ADL. The similarities of the patterns of ADLs related to walking were very low (p < 0.25) for the ankle joint motions even though the range of motion and pattern shapes were similar to one another. The similarities of the patterns of ADLs related to sitting/rising were particularly high (p > 0.9) for dorsi/plantar flexion and low (p < 0.5) for abduction/adduction. The similarities of the patterns of ADLs related to lying/rising were high, particularly for dorsi/plantar flexion and inversion/eversion. The results suggest that applying a pattern recognition approach with a conventional kinematic analysis may be effective, quantitative, and objective in understanding the kinematic characteristics of ankle joints.

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

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5

Similar content being viewed by others

References

  1. Guay, M., Dubois, M., Corrada, M., Lapointe-Garant, M., & Kawas, C. (2014). Exponential increases in the prevalence of disability in the oldest old: A canadian national survey. Gerontology,60(5), 395–401.

    Google Scholar 

  2. Grabiner, M. D., & Enoka, R. M. (1995). Changes in movement capabilities with aging. Exercise and Sport Sciences Reviews,23(1), 65–104.

    Google Scholar 

  3. Vandervoort, A. A. (1992). Effects of aging on human neuromuscular function: Implications for exercise. Canadian journal of sport sciences,17(3), 178–184.

    Google Scholar 

  4. Doebler, S., & Glasgow, N. (2017). Relationships between deprivation and the self-reported health of older people in Northern Ireland. Journal of Aging and Health,29(4), 594–619.

    Google Scholar 

  5. Spirduso, W., & Cronin, D. (2001). Exercise dose-response effects on quality of life and independent living in older adults. Medicine & Science in Sports & Exercise,33(6), S598–S608.

    Google Scholar 

  6. Allison, L. K., Kiemel, T., & Jeka, J. J. (2018). Sensory-challenge balance exercises improve multisensory reweighting in fall-prone older adults. Journal of Neurologic Physical Therapy,42(2), 84–93.

    Google Scholar 

  7. Bobic Lucic, L., & Grazio, S. (2018). Impact of balance confidence on daily living activities of older people with knee osteoarthritis with regard to balance, physical function, pain, and quality of life-a preliminary report. Clinical Gerontologist,41(4), 357–365.

    Google Scholar 

  8. Hamed, A., Bohm, S., Mersmann, F., & Arampatzis, A. (2018). Exercises of dynamic stability under unstable conditions increase muscle strength and balance ability in the elderly. Scandinavian Journal of Medicine & Science in Sports,28(3), 961–971.

    Google Scholar 

  9. Jung, H., Ko, C., Kim, J. S., Lee, B., & Lim, D. (2015). Alterations of relative muscle contribution induced by hemiplegia: Straight and turning gaits. International Journal of Precision Engineering and Manufacturing,16(10), 2219–2227.

    Google Scholar 

  10. Kim, J., Oh, S. I., Cho, H., Kim, H. S., Chon, J., Lee, W. J., et al. (2015). Gait patterns of chronic ambulatory hemiplegic elderly compared with normal age-matched elderly. International Journal of Precision Engineering and Manufacturing,16(2), 385–392.

    Google Scholar 

  11. Aboutorabi, A., Arazpour, M., Farahmand, F., Bahramizadeh, M., Fadayevatan, R., & Abdollahi, E. (2018). Design and evaluation of vibratory shoe on balance control for elderly subjects. Disability and Rehabilitation: Assistive Technology,13(2), 173–177.

    Google Scholar 

  12. Arif, M. J., Koutsouris, D., Pavlopoulos, S., & El Emary, I. M. M. (2018). Retracted: Web services for telegeriatric and independent living of the elderly in their homes. Journal of Fundamental and Applied Sciences,10(4S), 694–705.

    Google Scholar 

  13. Jung, H., Kim, H. J., Kim, B. R., & Lim, D. (2017). Alterations of human responses by varying dynamic rotational perturbations on balance training equipment. International Journal of Precision Engineering and Manufacturing,18(9), 1269–1274.

    Google Scholar 

  14. Shumway-Cook, A., & Wollacott, M. H. (1996). Motor control: Theory and practical applications. Baltimore: Williams & Wilkins Inc..

    Google Scholar 

  15. Horak, F. B., Shupert, C. L., & Mirka, A. (1989). Components of postural dyscontrol in the elderly: A review. Neurobiology of Aging,10(6), 727–738.

    Google Scholar 

  16. Schenkman, M., & Butler, R. B. (1989). A model for multisystem evaluation treatment of individuals with Parkinson’s disease. Physical Therapy,69(11), 932–943.

    Google Scholar 

  17. Chodzko-Zajko, W. J., & Ringel, R. L. (1987). Physiological fitness measures and sensory and motor-performance in aging. Experimental Gerontology,22(5), 317–328.

    Google Scholar 

  18. Lexell, J., Taylor, C. C., & Sjostrom, M. (1988). What is the cause of the ageing atrophy? Total number, size and proportion of different fiber types studied in whole vastus lateralis muscle from 15- to 83-year-old men. Journal of the Neurological Sciences,84(2–3), 275–294.

    Google Scholar 

  19. Arnold, J. B., Mackintosh, S., Jones, S., & Thewlis, D. (2014). Differences in foot kinematics between young and older adults during walking. Gait & Posture,39(2), 689–694.

    Google Scholar 

  20. Flanagan, S., Salem, G. J., Wang, M. Y., Sanker, S. E., & Greendale, G. A. (2003). Squatting exercises in older adults: Kinematic and kinetic comparisons. Medicine and Science in Sports and Exercise,35(4), 635–643.

    Google Scholar 

  21. Toda, H., Nagano, A., & Luo, Z. (2015). Age and gender differences in the control of vertical ground reaction force by the hip, knee and ankle joints. Journal of Physical Therapy Science,27(6), 1833–1838.

    Google Scholar 

  22. Atzori, M., Cognolato, M., & Muller, H. (2016). Deep learning with convolutional neural networks applied to electromyography data: A resource for the classification of movements for prosthetic hands. Frontiers in Neurorobotics,10, 9.

    Google Scholar 

  23. Wojtczak, P., Amaral, T. G., Dias, O. P., Wolczowski, A., & Kurzynski, M. (2009). Hand movement recognition based on biosignal analysis. Engineering Applications of Artificial Intelligence,22(4–5), 608–615.

    Google Scholar 

  24. Dobbins, C., & Rawassizadeh, R. (2018). Towards clustering of mobileand smartwatch accelerometer data for physical activity recognition. Informatics,5, 22.

    Google Scholar 

  25. Paulo, J., Asvadi, A., Peixoto, P., & Amorim, P. (2017). Human gait pattern changes detection system: A multimodal vision-based and novelty detection learning approach. Biocybernetics and Biomedical Engineering,37(4), 701–717.

    Google Scholar 

  26. Katz, S., Downs, T. D., Cash, H. R., & Grotz, R. C. (2003). Progress in development of the index of ADL. The Gerontologist,10(1_Part_1), 20–30.

    Google Scholar 

  27. Neumann, D. (2009). Kinesiology of the musculoskeletal system: Foundations for rehabilitation (2nd edn). In Chapter 14: Ankle and Foot. Amsterdam: Elsevier Inc.

  28. Lloyd, S. (1982). Least-squares quantization in PCM. IEEE Transactions on Information Theory,28(2), 129–137.

    MathSciNet  MATH  Google Scholar 

  29. Rabiner, L., & Gold, B. (1975). Theory and application of digital signal processing (p. 777). Englewood Cliffs: Prentice-Hall.

    Google Scholar 

  30. Riley, P. O., Della Croce, U., & Kerrigan, D. C. (2001). Effect of age on lower extremity joint moment contributions to gait speed. Gait & Posture,14(3), 264–270.

    Google Scholar 

  31. Protopapadaki, A., Drechsler, W. I., Cramp, M. C., Coutts, F. J., & Scott, O. M. (2007). Hip, knee, ankle kinematics and kinetics during stair ascent and descent in healthy young individuals. Clinical Biomechanics,22(2), 203–210.

    Google Scholar 

  32. Reeves, N. D., Spanjaard, M., Mohagheghi, A. A., Baltzopoulos, V., & Maganaris, C. N. (2008). The demands of stair descent relative to maximum capacities in elderly and young adults. Journal of Electromyography and Kinesiology,18(2), 218–227.

    Google Scholar 

  33. Eun, S. D. (2006). An investigation of the effect of the height of wteps on the joint moment of lower extremities of the elderly while walking downstairs. Korean Journal of Sport Biomechanics,16(4), 31–38.

    Google Scholar 

  34. Hemmerich, A., Brown, H., Smith, S., Marthandam, S. S. K., & Wyss, U. P. (2006). Hip, knee, and ankle kinematics of high range of motion activities of daily living. Journal of Orthopaedic Research,24(4), 770–781.

    Google Scholar 

  35. Menz, H. B., Lord, S. R., & Fitzpatrick, R. C. (2007). A structural equation model relating impaired sensorimotor function, fear of falling and gait patterns in older people. Gait & Posture,25(2), 243–249.

    Google Scholar 

  36. Thies, S. B., Richardson, J. K., & Ashton-Miller, J. A. (2005). Effects of surface irregularity and lighting on step variability during gait: A study in healthy young and older women. Gait & Posture,22(1), 26–31.

    Google Scholar 

  37. Kim, D. G., & Kang, H. J. (2017). An analysis on the comparison of the center of pressure, gait angle, and gait time between female college students and elderly women. The Official Journal of the Korean Academy of Kinesiology,19(2), 61–67.

    Google Scholar 

  38. Marks, R. (1997). The effect of restricting arm swing during normal locomotion. Biomedical Sciences Instrumentation,33, 209–215.

    Google Scholar 

Download references

Acknowledgements

This research was supported by a Grant of the Korea Health Technology R&D Project through the Korea Health Industry Development Institute (KHIDI), funded by the Ministry of Health & Welfare (Grant No. HI15C2149), Republic of Korea.

Author information

Author notes

  1. Hansol Seo and Sung-Chul Jun have contributed equally to this work as co-first authors.

Authors and Affiliations

  1. Department of Mechanical Engineering, Sejong University, 209 Neungdong-ro, Gwangjin-gu, Seoul, 05006, Republic of Korea

    Hansol Seo & Dohyung Lim

  2. Senior Products Industrial Center, Busan Techno Park, Busan, 47046, South Korea

    Sung-Chul Jun

  3. Department of Rehabilitation Medicine, Pusan National University School of Medicine, Yangsan, 50621, South Korea

    Sung-Chul Jun & Chang-Hyung Lee

  4. Seongnam Senior Experience Complex, Eulji University, Seongnam, 13503, South Korea

    Dukyoung Jung

  5. Biomedical System and Technology Group, Korea Institute of Industrial Technology, Cheonan, 31056, South Korea

    Jaesoo Hong

  6. Department of Biomedical Engineering, Yonsei University, Wonju, 26493, South Korea

    Han-Sung Kim

Authors
  1. Hansol Seo
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Sung-Chul Jun
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Dukyoung Jung
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Jaesoo Hong
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Chang-Hyung Lee
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Han-Sung Kim
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Dohyung Lim
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Dohyung Lim.

Ethics declarations

Conflict of interest

The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Seo, H., Jun, SC., Jung, D. et al. Analysis of Ankle Joint Motions for 12 Different Activities of Daily Living in the Elderly Using the Pattern Recognition Approach. Int. J. Precis. Eng. Manuf. 21, 1113–1126 (2020). https://doi.org/10.1007/s12541-020-00316-w

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s12541-020-00316-w

Keywords

Search

Navigation