Instrumental gait analysis in children with psoriatic arthritis using inertial sensors

Cover Page


Cite item

Full Text

Open Access Open Access
Restricted Access Access granted
Restricted Access Subscription or Fee Access

Abstract

BACKGROUND: Instrumental gait analysis (IGA) provides an objective and quantitative assessment of characteristic human movement patterns.

AIM: To analyze quantitative IGA parameters using inertial sensors in children with psoriatic arthritis (PsA) to identify early diagnostic markers and assess their potential application in evaluating the effectiveness of medical rehabilitation methods.

MATERIALS AND METHODS: The study included 34 children aged 11 to 17 years. The study group consisted of 17 children diagnosed with psoriasis and PsA (n=17). The control group included 17 children with conditions unrelated to significant neurological disorders or musculoskeletal abnormalities that could affect gait biomechanics (n=17). Gait parameters were recorded using the Stedis trainer, which utilizes eight biometric sensors placed on the lower extremities — on the feet, lower third of the shins, upper third of the thighs, sacrum, and at the level of the 12th thoracic vertebra. Spatiotemporal and kinematic gait parameters were analyzed.

RESULTS: A comparative analysis was conducted between the two groups: the control group (children without significant neurological or musculoskeletal abnormalities affecting gait biomechanics) and the PsA group. Children with PsA demonstrated an increased stance phase duration and single-limb support time on the affected lower limb compared to the control group. The swing phase duration of the affected limb was reduced by approximately 1.5% compared to the healthy limb. The foot-lift height of the affected limb was found to be 5 cm higher than that of the healthy limb. Compared with the control group, single-limb support time for the healthy leg in control group children was nearly 4% higher than in children with PsA. The differences were statistically significant (р=0.009). The swing phase duration for the affected lower limb in children with PsA was 2.3% higher than in the control group. The differences were statistically significant (р=0.019). The overall swing phase duration was nearly 4% higher in the control group (р=0.019), with statistically significant differences. The differences were statistically significant (р=0.019).

CONCLUSION: The development of a gait pattern characteristic of PsA is determined by own mechanisms distinct from those in other types of arthritis.

Full Text

Restricted Access

About the authors

Ulyana M. Kan

N.I. Pirogov Russian National Research Medical University

Email: polt2795@gmail.com
ORCID iD: 0009-0002-7445-9626

postgraduate student

Russian Federation, 1 Ostrovityanova str, Moscow, 117997

Olga A. Laisheva

N.I. Pirogov Russian National Research Medical University

Author for correspondence.
Email: olgalaisheva@mail.ru
ORCID iD: 0000-0002-8084-1277
SPIN-code: 8188-2819

MD, Dr. Sci. (Medicine), Professor

Russian Federation, 1 Ostrovityanova str, Moscow, 117997

References

  1. Skvortsov DV. Diagnosis of motor pathology by instrumental methods: gait analysis stabilometry. Andreev TM, editor. Moscow, 2007. 640 p. (In Russ.)
  2. Roberts M, Mongeon D, Prince F. Biomechanical parameters for gait analysis: a systematic review of healthy human gait. Physical Therapy and Rehabilitation. 2017;4(1):6. doi: 10.7243/2055-2386-4-6
  3. Baker R. Gait analysis methods in rehabilitation. Journal of neuroengineering and rehabilitation. 2006;3(1):4. doi: 10.1186/1743-0003-3-4 EDN: PUURIU
  4. Berner K, Cockcroft J, Louw Q. Kinematics and temporospatial parameters during gait from inertial motion capture in adults with and without HIV: a validity and reliability study. BioMed Eng OnLine. 2020;19(1):57. doi: 10.1186/s12938-020-00802-2 EDN: LSSHXB
  5. Abbass SJ. Kinematic analysis of human gait cycle. Nahrain University, College of Engineering Journal. 2014;16(2):208–222.
  6. Mo S, Chow DHK. Accuracy of three methods in gait event detection during overground running. Gait Posture. 2018;59:93–8. doi: 10.1016/j.gaitpost.2017.10.009
  7. Ewins D, Collins T. Clinical Gait Analysis. Clinical Engineering Academic Press. 2014:389–406. doi: 10.1016/B978-0-12-396961-3.00025-1
  8. Hillman SJ, Stansfield BW, Richardson AM, Robb JE. Development of temporal and distance parameters of gait in normal children. Gait & Posture. 2009;29:81–85. doi: 10.1016/j.gaitpost.2008.06.012
  9. Kluge F, Gaßner H, Hannink J, et al. Towards mobile gait analysis: concurrent validity and test-retest reliability of an inertial measurement system for the assessment of spatio-temporal gait parameters. Sensors. 2017;17:1522. doi: 10.3390/s17071522
  10. Sass P, Hassan G. Lower extremity abnormalities in children. American Family Physician. 2003;36(3):22–27.
  11. Johnston L, Eastwood D, Jacobs B. Variations in normal gait development, Symposium. Surgery and Orthopaedics, Paediatrics and Child Health. 2014;24(5):204–207. doi: 10.1016/j.paed.2014.03.006
  12. Inman VT, Ralston HJ, Frank T. Human Walking. London: Williams and Wilkins; 1981.
  13. Kochergin SN, Tamrazova OB, Stadnikova AS. Analysis in children and employees of the Medical Council of the Republic. 2016;2:77–10.
  14. Alekseeva EI. Juvenile idiopathic arthritis: clinical picture, diagnosis, treatment. Current Pediatrics. 2015;14(1):78–94. doi: 10.15690/vsp.v14i1.1266 EDN: TIHOVF
  15. Chebysheva SN, Geppe NA, Zholobova ES, et al. Clinical features of psoriatic arthritis in childhood. Doctor.Ru. 2020;19(10):22–26. doi: 10.31550/1727-2378-2020-19-10-22-26 EDN: BRNISF
  16. Molochkov VA, Yakubovskaya ES, Mylov NM. Psoriasis and psoriatic arthritis. Clinic, diagnosis, treatment. Moscow: Monica; 2015. p. 26. (In Russ.)
  17. Lee K, Armstrong AU. Review of the results of treatment of patients with psoriasis. Dermatol Clin. 2012;30(1):61–72. doi: 10.1016/j.det.2011.08.012
  18. Adaskevich VP, Katina MA. Clinical features of psoriasis in children and adolescents. Medical Council of the Republic. 2018;2:83–88.
  19. Chen S, Lach J, Lo B, Yang G-Z. Toward pervasive gait analysis with wearable sensors: a systematic review. J Biomed Heal Informatics. 2016;20:1521–37. doi: 10.1109/JBHI.2016.2608720
  20. Iosa M, Picerno P, Paolucci S, Morone G. Wearable inertial sensors for human movement analysis. Expert Rev Med Devices. 2016;13:641-659. doi: 10.1080/17434440.2016.1198694
  21. Picerno P. 25 years of lower limb joint kinematics by using inertial and magnetic sensors: a review of methodological approaches. Gait Posture. 2017;51:239–46. doi: 10.1016/j.gaitpost.2016.11.008
  22. Mikhailova AA, Korchazhkina NB, Kotenko KV, Koneva ES. Experience in the use of robotic biomechanical medical rehabilitation techniques in patients after acute cerebrovascular accident. Problems of Balneology, Physiotherapy and Exercise Therapy. 2021;98(3-2):127–128. (In Russ.) EDN: OOEAJW
  23. Kotenko KV, Khan MA, Korchazhkina NB, et al. Modern non-drug technologies of medical rehabilitation of children. Moscow: GEOTAR-Media; 2022. 440 р. (In Russ.) doi: 10.33029/9704-7062-6-MTM-2022-1-440 EDN: IBGAKQ

Supplementary files

Supplementary Files
Action
1. JATS XML
Download
2. Fig. 1. Comparative analysis of the "Healthy lower limb" data in patients with diagnoses of psoriasis, psoriatic arthritis and a control group. M_K — arithmetic mean of children in the control group; m_K — standard deviation; M_PsA — arithmetic mean. Children with PsA; m_PsA — standard deviation.

Download (120KB)
Indexing metadata
3. Fig. 2. Comparative analysis of the "Affected lower limb" data in patients with diagnoses of psoriasis, psoriatic arthritis and a control group. M_K — arithmetic mean of children in the control group; m_K — standard deviation; M_PsA — arithmetic mean. Children with PsA; m_PsA — standard deviation.

Download (117KB)
Indexing metadata
4. Fig. 3. Kinematic changes in gait parameters in the hip joint.

Download (90KB)
Indexing metadata
5. Fig. 4. Kinematic changes in gait parameters in the knee joint.

Download (85KB)
Indexing metadata
6. Fig. 5. Kinematic changes in gait parameters in the ankle joint.

Download (93KB)
Indexing metadata

Copyright (c) 2025 Eco-Vector


СМИ зарегистрировано Федеральной службой по надзору в сфере связи, информационных технологий и массовых коммуникаций (Роскомнадзор).
Регистрационный номер и дата принятия решения о регистрации СМИ: серия ПИ № ФС 77 - 86508 от 11.12.2023. 
СМИ зарегистрировано Федеральной службой по надзору в сфере связи, информационных технологий и массовых коммуникаций (Роскомнадзор).
Регистрационный номер и дата принятия решения о регистрации СМИ: серия ЭЛ № ФС 77 - 80650 от 15.03.2021 г.