Abstract

Dynamic knee joint function requires coordinated multi-muscle activation patterns (MMP) that may be adversely affected by total knee arthroplasty (TKA). This study identified MMP changes in post-operative female TKA patients using a Support Vector Machine (SVM). It was hypothesised that TKA patients can successfully be classified and display significant alterations in temporal and spectral muscle activation characteristics. 19 female subjects (10 unilateral gender-specific TKA, 62.2±8.6yrs, BMI 28.2±5.4; and 9 healthy controls, 61.4±7.4yrs, BMI 25.6±2.4) were recruited. Surface electromyograms (EMG) were obtained for 7 lower limb muscles during walking. Stance phase (±30%) EMG data were processed using a wavelet transform and normalized to total power. Data across all muscles were combined to form MMPs and analyzed using a SVM. Recognition rates for all subjects were computed for MMPs and individual muscles. A binomial test was used to establish statistical significance (p<0.05). The results supported the hypothesis indicating significantly altered muscle activations for vastus medialis (recognition rate ∼68.4%) and biceps femoris (recognition rate ∼73.7%). Further analysis identified distinct between group differences across temporal, spectral and intensity domains. Application of a combined SVM and MMP approach may be beneficial for the future assessment of post-surgical dynamic muscle function.

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