Agreement between the GAITRite® System and the Wearable Sensor BTS G-Walk® for measurement of gait parameters in healthy adults and Parkinson's disease patients

Slávka Vítečková, Hana Horáková, Kamila Poláková, Radim Krupička, Evžen Růžička, Hana Brožová, Slávka Vítečková, Hana Horáková, Kamila Poláková, Radim Krupička, Evžen Růžička, Hana Brožová

Abstract

Background: Nowadays, the most widely used types of wearable sensors in gait analysis are inertial sensors. The aim of the study was to assess the agreement between two different systems for measuring gait parameters (inertial sensor vs. electronic walkway) on healthy control subjects (HC) and patients with Parkinson's disease (PD).

Methods: Forty healthy volunteers (26 men, 14 women, mean age 58.7 ± 7.7 years) participated in the study and 24 PD patients (19 men, five women, mean age 62.7 ± 9.8 years). Each participant walked across an electronic walkway, GAITRite, with embedded pressure sensors at their preferred walking speed. Concurrently a G-Walk sensor was attached with a semi-elastic belt to the L5 spinal segment of the subject. Walking speed, cadence, stride duration, stride length, stance, swing, single support and double support phase values were compared between both systems.

Results: The Passing-Bablock regression slope line manifested the values closest to 1.00 for cadence and stride duration (0.99 ≤ 1.00) in both groups. The slope of other parameters varied between 0.26 (double support duration in PD) and 1.74 (duration of single support for HC). The mean square error confirmed the best fit of the regression line for speed, stride duration and stride length. The y-intercepts showed higher systematic error in PD than HC for speed, stance, swing, and single support phases.

Conclusions: The final results of this study indicate that the G-Walk system can be used for evaluating the gait characteristics of the healthy subjects as well as the PD patients. However, the duration of the gait cycle phases should be used with caution due to the presence of a systematic error.

Keywords: Biomechanics; Gait analysis; Parkinson’s disease; Wearable sensors.

Conflict of interest statement

The authors declare there are no competing interests.

©2020 Vítečková et al.

Figures

Figure 1. Scatter plots with Passing-Bablok regression…
Figure 1. Scatter plots with Passing-Bablok regression lines and identity lines (y = x) for control group.
(A) Cadence (step/min), (B) Speed (m/s), (C) Stride duration (s), (D) Stride lenght (m), (E) Stance (%), (F) Swing (%), (G) Double support (%), (H) Single support (%); x-axis: GAITRite, y-axis: G-Walk.
Figure 2. Scatter plots with Passing-Bablok regression…
Figure 2. Scatter plots with Passing-Bablok regression lines and identity lines (y = x) for Parkinson’s disease patients.
(A) Cadence (step/min), (B) Speed (m/s), (C) Stride duration (s), (D) Stride lenght (m), (E) Stance (%), (F) Swing (%), (G) Double support (%), (H) Single support (%); x-axis: GAITRite, y-axis: G-Walk.

References

    1. Bilić-Zulle L. Comparison of methods: passing and Bablok regression. Biochemia Medica. 2011;21:49–52. doi: 10.11613/bm.2011.010.
    1. Bilney B, Morris M, Webster K. Concurrent related validity of the GAITRite walkway system for quantification of the spatial and temporal parameters of gait. Gait & Posture. 2003;17:68–74. doi: 10.1016/s0966-6362(02)00053-x.
    1. Bland JM, Altman DG. A note on the use of the intraclass correlation coefficient in the evaluation of agreement between two methods of measurement. Computers in Biology and Medicine. 1990;20:337–340. doi: 10.1016/0010-4825(90)90013-F.
    1. Bravi M, Gallotta E, Morrone M, Maselli M, Santacaterina F, Toglia R, Foti C, Sterzi S, Bressi F, Miccinilli S. Concurrent validity and inter trial reliability of a single inertial measurement unit for spatial–temporal gait parameter analysis in patients with recent total hip or total knee arthroplasty. Gait Posture. 2020;76:175–181. doi: 10.1016/j.gaitpost.2019.12.014.
    1. Cimolin V, Capodaglio P, Cau N, Galli M, Santovito C, Patrizi A, Tringali G, Sartorio A. Computation of spatio-temporal parameters in level walking using a single inertial system in lean and obese adolescents. Biomedizinische Technik. Biomedical Engineering. 2017;62:505–511. doi: 10.1515/bmt-2015-0180.
    1. De Ridder R, Lebleu J, Willems T, De Blaiser C, Detrembleu C, Roosen P. Concurrent validity of a commercial wireless trunk tri-axial accelerometer system for gait analysis. Journal of Sport Rehabilitation. 2019;28(6):1–13. doi: 10.1123/jsr.2018-0295.
    1. DesJardins AM, Schiller M, Eraqi E, Samuels AN, Galen SS. Validity of a wireless gait analysis tool (Wi-GAT) in assessing spatio-temporal gait parameters at slow, preferred and fast walking speeds. Technology and Health Care. 2016;24:843–852. doi: 10.3233/THC-161232.
    1. Dodson JA, Reid KJ, Gill TM, Krumholz HM, Forman DE, Spertus JA, Rich MW, Arnold SV, Alexander KP. Slow gait among older adults post-ami and risk for hospital readmission. Journal of the American College of Cardiology. 2012;59:E1914. doi: 10.1016/S0735-1097(12)61915-9.
    1. Fleiss JL, Levin B, Paik MC. Statistical methods for rates and proportions. 3rd ed. John Wiley & Sons; New Jersey: 2013.
    1. Godfrey A, Del Din S, Barry G, Mathers JC, Rochester L. Instrumenting gait with an accelerometer: a system and algorithm examination. Medical Engineering & Physics. 2015;37:400–407. doi: 10.1016/j.medengphy.2015.02.003.
    1. Greene BR, Foran TG, McGrath D, Doheny EP, Burns A, Caulfield B. A comparison of algorithms for body-worn sensor-based spatiotemporal gait parameters to the GAITRite electronic walkway. Journal of Applied Biomechanics. 2012;28(3):349–355. doi: 10.1123/jab.28.3.349.
    1. Heikkilä A, Sevander-Kreus N, Häkkinen A, Vuorenmaa M, Salo P, Konsta P, Ylinen J. Effect of total knee replacement surgery and postoperative 12 month home exercise program on gait parameters. Gait & Posture. 2017;53:92–97. doi: 10.1016/j.gaitpost.2017.01.004.
    1. Muro-de-la Herran A, Garcia-Zapirain B, Mendez-Zorrilla A. Gait analysis methods: an overview of wearable and non-wearable systems, highlighting clinical applications. Sensors. 2014;14:3362–3394. doi: 10.3390/s140203362.
    1. Jagos H, Pils K, Haller M, Wassermann C, Chhatwal C, Rafolt D, Rattay F. Mobile gait analysis via eSHOEs instrumented shoe insoles: a pilot study for validation against the gold standard GAITRite®. Journal of Medical Engineering & Technology. 2017;41:375–386. doi: 10.1080/03091902.2017.1320434.
    1. Leonardi L, Aceto MG, Marcotulli C, Arcuria G, Serrao M, Pierelli F, Paone P, Filla A, Roca A, Casali C. A wearable proprioceptive stabilizer for rehabilitation of limb and gait ataxia in hereditary cerebellar ataxias: a pilot open-labeled study. Neurological Sciences. 2017;38:459–463. doi: 10.1007/s10072-016-2800-x.
    1. McGee SR. Evidence-based physical diagnosis. Elsevier/Saunders; Philadelphia: 2012. p. 54.
    1. Menz HB, Latt MD, Tiedemann A, San Kwan MM, Lord SR. Reliability of the GAITRite® walkway system for the quantification of temporo-spatial parameters of gait in young and older people. Gait & posture. 2004;20(1):20–25. doi: 10.1016/S0966-6362(03)00068-7.
    1. Nonnekes J, Goselink RJM, Růžička E, Fasano A, Nutt JG, Bloem BR. Neurological disorders of gait, balance and posture: a sign-based approach. Nature Reviews. Neurology. 2018;14:183–189. doi: 10.1038/nrneurol.2017.178.
    1. Panebianco GP, Bisi MC, Stagni R, Fantozzi S. Analysis of the performance of 17 algorithms from a systematic review: influence of sensor position, analysed variable and computational approach in gait timing estimation from IMU measurements. Gait Posture. 2018;66:76–82. doi: 10.1016/j.gaitpost.2018.08.025.
    1. Park G, Woo Y. Comparison between a center of mass and a foot pressure sensor system for measuring gait parameters in healthy adults. Journal of Physical Therapy Science. 2015;27(10):3199–3202. doi: 10.1589/jpts.27.3199.
    1. Passing H, Bablok W. A new biometrical procedure for testing the equality of measurements from two different analytical methods. Application of linear regression procedures for method comparison studies in clinical chemistry, Part I. Journal of Clinical Chemistry and Clinical Biochemistry. 1983;21:709–720.
    1. Pau M, Leban B, Collu G, Migliaccio GM. Effect of light and vigorous physical activity on balance and gait of older adults. Archives of Gerontology and Geriatrics. 2014;59:568–573. doi: 10.1016/j.archger.2014.07.008.
    1. Petraglia F, Scarcella L, Pedrazzi G, Brancato L, Puers R, Costantino C. Inertial sensors versus standard systems in gait analysis: a systematic review and meta-analysis. European Journal of Physical and Rehabilitation Medicine. 2019;55(2):265–280. doi: 10.23736/S1973-9087.18.05306-6.
    1. Prescott RJ. Avoid being tripped up by statistics: Statistical guidance for a successful research paper. Gait & Posture. 2019;72:240–249. doi: 10.1016/j.gaitpost.2018.06.172.
    1. Rennie L, Dietrichs E, Moe-Nilssen R, Opheim A, Franzén E. The validity of the Gait Variability Index for individuals with mild to moderate Parkinson’s disease. Gait & Posture. 2017;54:311–317. doi: 10.1016/j.gaitpost.2017.03.023.
    1. Sloman L, Berridge M, Homatidis S, Hunter D, Duck T. Gait patterns of depressed patients and normal subjects. The American journal of psychiatry. 1982;139(1):94–97. doi: 10.1176/ajp.139.1.94.
    1. Tao W, Liu T, Zheng R, Feng H. Gait analysis using wearable sensors. Sensors. 2012;12:2255–2283. doi: 10.3390/s120202255.
    1. Tomlinson CL, Stowe R, Patel S, Rick C, Gray R, Clarke CE. Systematic review of levodopa dose equivalency reporting in Parkinson’s disease. Movement Disorders. 2010;25(15):2649–2653. doi: 10.1002/mds.23429.
    1. Van Uden CJT, Besser MP. Test-retest reliability of temporal and spatial gait characteristics measured with an instrumented walkway system (GAITRite) BMC Musculoskeletal Disorders. 2004;5:5–13. doi: 10.1186/1471-2474-5-13.
    1. Vaz S, Falkmer T, Passmore AE, Parsons R, Andreou P. The case for using the repeatability coefficient when calculating test–retest reliability. PLOS ONE. 2013;8(9):e73990. doi: 10.1371/journal.pone.0073990.
    1. Webster KE, Wittwer JE, Feller JA. Validity of the GAITRite® walkway system for the measurement of averaged and individual step parameters of gait. Gait & Posture. 2005;22(4):317–321. doi: 10.1016/j.gaitpost.2004.10.005.
    1. Wolak ME, Fairbairn DJ, Paulsen YR. Guidelines for estimating repeatability. Methods in Ecology and Evolution. 2012;3:129–137. doi: 10.1111/j.2041-210X.2011.00125.x.
    1. Zago M, Sforza C, Pacifici I, Cimolin V, Camerota F, Celletti C, Condoluci C, De Pandis MF, Galli M. Gait evaluation using inertial measurement units in subjects with Parkinson’s disease. Journal of Electromyography and Kinesiology. 2018;42:44–48. doi: 10.1016/j.jelekin.2018.06.009.
    1. Zaki R, Bulgiba A, Ismail R, Ismail NA. Statistical methods used to test for agreement of medical instruments measuring continuous variables in method comparison studies: a systematic review. PLOS ONE. 2012;7:e37908. doi: 10.1371/journal.pone.0037908.
    1. Zijlstra W, Hof AL. Assessment of spatio-temporal gait parameters from trunk accelerations during human walking. Gait & Posture. 2003;18:1–10. doi: 10.1016/S0966-6362(02)00190-X.

Source: PubMed

Sponsors en medewerkers

Medische omstandigheden

Geneesmiddelinterventies

3
Abonneren