A Strathclyde cluster model for gait kinematic measurement using functional methods : a study of inter-assessor reliability analysis with comparison to anatomical models

Meng, Lin and Millar, Lindsay and Childs, Craig and Buis, Arjan (2020) A Strathclyde cluster model for gait kinematic measurement using functional methods : a study of inter-assessor reliability analysis with comparison to anatomical models. Computer Methods in Biomechanics and Biomedical Engineering, 23 (12). pp. 844-853. ISSN 1025-5842

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    Abstract

    A major source of error in reliability of gait analysis arises from the palpation of anatomical landmarks (ALs). The purpose of this study was to investigate whether less reliance on manually identifying ALs could improve inter-assessor reliability of joint kinematics compared to two anatomical models. It was hypothesised that the Strathclyde Functional Cluster Model (SFCM), in which the hip, knee and ankle joint centres and knee and ankle flexion axes were determined by functional methods, would obtain greater inter-assessor reliability. Ten able-bodied participants and seven assessors were recruited. Each participant completed three trials conducted by different assessors on non-consecutive days. Agreement and inter-assessor reliability between the models were compared and analysed, whilst factor effects of assessor experience and body mass index (BMI) were investigated. The SFCM obtained excellent agreement with anatomical models for all sagittal angles and hip ab/adduction angle, and it showed slightly higher inter-assessor reliability with smaller variations in the knee and ankle. The assessor experience was not a significant factor, but the BMI had a significant effect on the inter-assessor reliability. The results demonstrate that the SFCM may be more beneficial for less experienced assessors.

    ORCID iDs

    Meng, Lin ORCID logoORCID: https://orcid.org/0000-0001-9787-9936, Millar, Lindsay ORCID logoORCID: https://orcid.org/0000-0001-7600-9907, Childs, Craig ORCID logoORCID: https://orcid.org/0000-0003-1318-0007 and Buis, Arjan ORCID logoORCID: https://orcid.org/0000-0003-3947-293X;