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Objective assessment of abnormal gait in patients with rheumatoid arthritis using a smartphone

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Abstract

A disturbance in gait pattern is a serious problem in patients with rheumatoid arthritis (RA). The aim of the present study was to examine the utility of the smartphone gait analysis application in patients with RA. The smartphone gait analysis application was used to assess 39 patients with RA (age 65.9 ± 10.0 years, disease duration 11.9 ± 9.4 years) and age-matched control individuals (mean age, 69.1 ± 5.8 years). For all RA patients, the following data were obtained: disease activity score (DAS) 28, modified health assessment questionnaire (mHAQ), and assessment of walking ability. Patients walked 20 m at their preferred speed, and trunk acceleration was measured using a Smartphone. After signal processing, we calculated the following gait parameters for each measurement terminal: peak frequency (PF), autocorrelation peak (AC), and coefficient of variance (CV) of the acceleration peak intervals. The gait parameters of RA and control groups were compared to examine the comparability of the 2 groups. Criterion-related validity was determined by evaluating the correlation between gait parameters and clinical parameters using Spearman’s correlation coefficient. The RA group showed significantly lower scores for the walking speed, AC, and CV than the control group. There were no significant differences in PF. PF (gait cycle) was mildly associated with gait speed (P < 0.05). AC (gait balance) was moderately associated with the DAS, mHAQ, gait ability, and gait speed (P < 0.05). CV (gait variability) was moderately associated with the DAS, gait ability, and gait speed (P < 0.05). This is the first study to examine the use of a smartphone device for gait pattern measurement. The results suggest that some gait parameters recorded using the smartphone represent an acceptable assessment tool for gait in patients with RA.

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Acknowledgments

We would like to thank all the volunteers for participating in the study. We would also like to acknowledge the students of the Department of Human Health Sciences at Kyoto University for assisting in the data collection.

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Authors and Affiliations

  1. Human Health Sciences, Graduate School of Medicine, Kyoto University, 53 Kawahara-cho, Shogoin, Sakyo-ku, Kyoto, 606-8507, Japan

    Minoru Yamada, Tomoki Aoyama, Shuhei Mori & Shu Nishiguchi

  2. Department of Medical Informatics, Kyoto University Hospital, Kyoto, Japan

    Kazuya Okamoto

  3. NTT Cyber Solutions Laboratories, Yokosuka, Japan

    Tatsuaki Ito & Shinyo Muto

  4. Nippon Telegraph and Telephone East Corporation, Sapporo, Japan

    Tatsuya Ishihara

  5. Department of Orthopaedic Surgery, Graduate School of Medicine, Kyoto University, Kyoto, Japan

    Hiroyuki Yoshitomi

  6. Department for the Control of Rheumatic Diseases, Graduate School of Medicine, Kyoto University, Kyoto, Japan

    Hiromu Ito

Authors
  1. Minoru Yamada
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  2. Tomoki Aoyama
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  3. Shuhei Mori
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  4. Shu Nishiguchi
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  5. Kazuya Okamoto
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  6. Tatsuaki Ito
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  7. Shinyo Muto
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  8. Tatsuya Ishihara
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  9. Hiroyuki Yoshitomi
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  10. Hiromu Ito
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Corresponding author

Correspondence to Minoru Yamada.

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Yamada, M., Aoyama, T., Mori, S. et al. Objective assessment of abnormal gait in patients with rheumatoid arthritis using a smartphone. Rheumatol Int 32, 3869–3874 (2012). https://doi.org/10.1007/s00296-011-2283-2

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  • DOI: https://doi.org/10.1007/s00296-011-2283-2

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