Spatial-temporal gait parameters based on a wearable inertial sensor of healthy Brazilian subjects

Authors

  • Artur César Aquino dos Santos Instituto de Medicina Física e Reabilitação do Hospital das Clínicas da Faculdade de Medicina da Universidade de São Paulo
  • Paulo Roberto Fonseca Junior Instituto de Medicina Física e Reabilitação do Hospital das Clínicas da Faculdade de Medicina da Universidade de São Paulo
  • Maria Helena Gomes de Sousa Instituto de Medicina Física e Reabilitação do Hospital das Clínicas da Faculdade de Medicina da Universidade de São Paulo
  • Sabrina Saemy Tome Uchiyama Instituto de Medicina Física e Reabilitação do Hospital das Clínicas da Faculdade de Medicina da Universidade de São Paulo
  • Marcel Simis Instituto de Medicina Física e Reabilitação do Hospital das Clínicas da Faculdade de Medicina da Universidade de São Paulo
  • Linamara Rizzo Battistella Faculdade de Medicina da Universidade de Sao Paulo

DOI:

https://doi.org/10.11606/issn.2317-0190.v30i4a219934

Keywords:

Gait Analysis, Reference Values, Wearable Electronic Devices

Abstract

Gait analysis in a laboratory may be expensive, time-consuming, and restricted to a controlled environment. Validated wearable technology may be an alternative to such analysis. However, wearable technologies should demonstrate reference values of a healthy population. Objective: To establish spatio-temporal gait reference values of an accelerometer (G-Walk) in a healthy Brazilian population. Methods: This is a cross-sectional study with 124 healthy subjects evaluated with G-Walk in the 6-minute and 10-meter walk tests (6MWT and 10MWT). Gait parameters of Velocity, Cadence, Distance, and gait symmetry variables were retrieved for analysis. Clinical and demographical characteristics were also collected and tested with simple linear regression as covariables of the gait characteristics. The bootstrapped 5th percentile of the gait parameter established the reference values. If a covariable influence was found, the reference values were established by subgroup analysis according to the covariable. Results: The study analyzed 114 subjects, mostly women (67.74%), aged 39.36 (SD 12.18). Height was a covariable of cadence for the 10MWT and cadence and stride length for the 6MWT. Age and sex combined were covariables of 6MWT velocity, and sex alone was a covariable of 6MWT. All reference values for symmetry were above 89%, velocity at the 10MWT was above 1.0m/s, and distance at the 6MWT was 354m and 359.5 for females and males, respectively. Conclusions: Our study generated reference values for spatio-temporal gait analysis with G-Walk of a population of a major urban area, considering the covariables of age, height, and sex.

Downloads

Download data is not yet available.

References

Senden R, Grimm B, Heyligers IC, Savelberg HH, Meijer K. Acceleration-based gait test for healthy subjects: reliability and reference data. Gait Posture. 2009;30(2):192-6. Doi: https://doi.org/10.1016/j.gaitpost.2009.04.008

Deligianni F, Guo Y, Yang GZ. From Emotions to Mood Disorders: A Survey on Gait Analysis Methodology. IEEE J Biomed Health Inform. 2019;23(6):2302-2316. Doi: https://doi.org/10.1109/JBHI.2019.2938111

Ridao-Fernández C, Pinero-Pinto E, Chamorro-Moriana G. Observational Gait Assessment Scales in Patients with Walking Disorders: Systematic Review. Biomed Res Int. 2019;2019:2085039. Doi: https://doi.org/10.1155/2019/2085039

Schwesig R, Leuchte S, Fischer D, Ullmann R, Kluttig A. Inertial sensor based reference gait data for healthy subjects. Gait Posture. 2011;33(4):673-8. Doi: https://doi.org/10.1016/j.gaitpost.2011.02.023

Bugané F, Benedetti MG, Casadio G, Attala S, Biagi F, Manca M, et al. Estimation of spatial-temporal gait parameters in level walking based on a single accelerometer: validation on normal subjects by standard gait analysis. Comput Methods Programs Biomed. 2012;108(1):129-37. Doi: https://doi.org/10.1016/j.cmpb.2012.02.003

Fonseca Junior PR, Moura RCF, Oliveira CS, Politti F. Use of wearable inertial sensors for the assessment of spatiotemporal gait variables in children: A systematic review. Mot Rev Educ Fís. 2020;26(3):e10200139. Doi: https://doi.org/10.1590/S1980-6574202000030139

Nasiri S, Khosravani MR. Progress and challenges in fabrication of wearable sensors for health monitoring. Sensors Actuators A Phys. 2020;312:112105. Doi: https://doi.org/10.1016/j.sna.2020.112105

Patel M, Pavic A, Goodwin VA. Wearable inertial sensors to measure gait and posture characteristic differences in older adult fallers and non-fallers: a scoping review. Gait Posture. 2020;76:110-121. Doi: https://doi.org/10.1016/j.gaitpost.2019.10.039

Iijima H, Takahashi M. State of the Field of waist-mounted sensor algorithm for gait events detection: A scoping review. Gait Posture. 2020;79:152-161. Doi: https://doi.org/10.1016/j.gaitpost.2020.03.021

Kirkwood RN, Batista NCL, Marques LBF, Melo Ocarino J, Neves LLA, Souza Moreira B. Cross-cultural adaptation and reliability of the Functional Gait Assessment in older Brazilian adults. Braz J Phys Ther. 2021;25(1):78-85. Doi: https://doi.org/10.1016/j.bjpt.2020.02.004

Simis M, Imamura M, Sampaio de Melo P, Marduy A, Battistella L, Fregni F. Deficit of Inhibition as a Marker of Neuroplasticity (DEFINE Study) in Rehabilitation: A Longitudinal Cohort Study Protocol. Front Neurol. 2021;12:695406. Doi: 10.3389/fneur.2021.695406

Gutierrez RG, Carter S, Drukker D. On boundary-value likeli-hood-ratio tests. Stata Technical Bulletin. 2001;10(60):15-8.

Atkinson G, Nevill AM. Statistical methods for assessing measurement error (reliability) in variables relevant to sports medicine. Sports Med. 1998;26(4):217-38. Doi: https://doi.org/10.2165/00007256-199826040-00002

Cook R, Weisberg S. Diagnostics for Heteroscedasticity in Regression. Biometrika.1983;70(1):1-10. Doi: https://doi.org/10.2307/2335938

Royston P. Model selection for univariable fractional polynomials. Stata J. 2017;17(3):619-29.

Burritt MF, Slockbower JM, Forsman RW, Offord KP, Berg-stralh EJ, Smithson WA. Pediatric reference intervals for 19 biologic variables in healthy children. Mayo Clin Proc. 1990;65(3):329-36. Doi: https://doi.org/10.1016/s0025-6196(12)62533-6

Linnet K. Nonparametric estimation of reference intervals by simple and bootstrap-based procedures. Clin Chem. 2000;46(6 Pt 1):867-9.

Ceriotti F, Hinzmann R, Panteghini M. Reference intervals: the way forward. Ann Clin Biochem. 2009;46(Pt 1):8-17. Doi: https://doi.org/10.1258/acb.2008.008170

SIDRA: Sistema IBGE de Recuperação Automática [databe on the Internet]. Rio de Janeiro: IBGE; c2023 [cited 2023 Sep 17]. Available from: https://sidra.ibge.gov.br/home/pms/brasil

Negrini S, Serpelloni M, Amici C, Gobbo M, Silvestro C, Buraschi R, et al. Use of wearable inertial sensor in the assessment of timed-up-and-go test: influence of device placement on temporal variable estimation. In: Perego P, Andreoni G, Rizzo G. Wireless Mobile Communication and Healthcare. MobiHealth 2016. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommu-nications Engineering. Berlin: Springer; 2017. p. 310-7. Doi: https://doi.org/10.1007/978-3-319-58877-3_40

Storm FA, Cesareo A, Reni G, Biffi E. Wearable Inertial Sensors to Assess Gait during the 6-Minute Walk Test: A Systematic Review. Sensors (Basel). 2020;20(9):2660. Doi: https://doi.org/10.3390/s20092660

Bohannon RW. Population representative gait speed and its determinants. J Geriatr Phys Ther. 2008;31(2):49-52. Doi: https://doi.org/10.1519/00139143-200831020-00002

Oberg T, Karsznia A, Oberg K. Basic gait parameters: reference data for normal subjects, 10-79 years of age. J Rehabil Res Dev. 1993;30(2):210-23.

Murray MP, Drought AB, Kory RC. Walking patterns of normal men. J Bone Joint Surg Am. 1964;46:335-60.

Murray MP, Kory RC, Sepic SB. Walking patterns of normal women. Arch Phys Med Rehabil. 1970;51(11):637-50.

Kirtley C, Whittle MW, Jefferson RJ. Influence of walking speed on gait parameters. J Biomed Eng. 1985;7(4):282-8. Doi: https://doi.org/10.1016/0141-5425(85)90055-x

Macellari V, Giacomozzi C, Saggini R. Spatial-temporal parameters of gait: reference data and a statistical method for normality assessment. Gait Posture. 1999;10(2):171-81. Doi: https://doi.org/10.1016/s0966-6362(99)00021-1

Geffré A, Friedrichs K, Harr K, Concordet D, Trumel C, Braun JP. Reference values: a review. Vet Clin Pathol. 2009;38(3):288-98. Doi: https://doi.org/10.1111/j.1939-165X.2009.00179.x

Concordet D, Geffré A, Braun JP, Trumel C. A new approach for the determination of reference intervals from hospital-based data. Clin Chim Acta. 2009;405(1-2):43-8. Doi: https://doi.org/10.1016/j.cca.2009.03.057

Gräsbeck R. Reference values, why and how. Scand J Clin Lab Invest Suppl. 1990;201:45-53.

Virtanen A, Kairisto V, Irjala K, Rajamäki A, Uusipaikka E. Regression-based reference limits and their reliability: example on hemoglobin during the first year of life. Clin Chem. 1998;44(2):327-35.

Virtanen A, Kairisto V, Uusipaikka E. Parametric methods for estimating covariate-dependent reference limits. Clin Chem Lab Med. 2004;42(7):734-8. Doi: https://doi.org/10.1515/CCLM.2004.124

Horn PS, Pesce AJ, Copeland BE. A robust approach to reference interval estimation and evaluation. Clin Chem. 1998;44(3):622-31.

Horn PS, Pesce AJ. Reference intervals: an update. Clin Chim Acta. 2003;334(1-2):5-23. Doi: https://doi.org/10.1016/s0009-8981(03)00133-5

Downloads

Published

2023-12-31

Issue

Section

Original Article

How to Cite

1.
Santos ACA dos, Fonseca Junior PR, Sousa MHG de, Uchiyama SST, Simis M, Battistella LR. Spatial-temporal gait parameters based on a wearable inertial sensor of healthy Brazilian subjects. Acta Fisiátr. [Internet]. 2023 Dec. 31 [cited 2024 May 19];30(4):245-50. Available from: https://periodicos.usp.br/actafisiatrica/article/view/219934