Asymmetry Index in Muscle Activations.

Gait asymmetry is typically evaluated using spatio-temporal or joint kinematics parameters. Only a few studies addressed the problem of defining an asymmetry index directly based on muscle activity, extracting parameters from surface electromyography (sEMG) signals. Moreover, no studies used the extraction of the muscle principal activations (activations that are necessary for accomplishing a specific motor task) as the base to construct an asymmetry index, less affected by the variability of sEMG patterns. The aim of this paper is to define a robust index to quantitatively assess the asymmetry of muscle activations during locomotion, based on the extraction of the principal activations. SEMG signals were analyzed combining statistical gait analysis (SGA) and a clustering algorithm that allows for obtaining the muscle principal activations. We evaluated the asymmetry levels of four lower limb muscles in: (1) healthy subjects of different ages (children, adults, and elderly); (2) different populations of orthopedic patients (adults with megaprosthesis of the knee after bone tumor resection, elderly subjects after total knee arthroplasty, and elderly subjects after total hip arthroplasty); and (3) neurological patients (children with hemiplegic cerebral palsy and elderly subjects affected by idiopathic normal pressure hydrocephalus). The asymmetry index obtained for each pathological population was then compared to that of age-matched controls. We found asymmetry levels consistent with the expected impact of the different pathologies on muscle activation during gait. This suggests that the proposed index can be successfully used in clinics for an objective assessment of the muscle activation asymmetry during locomotion.

Influence of pre-processing in the extraction of muscle synergies during human locomotion.

The extraction of muscle synergies in human locomotion may be biased by the kind of pre-processing applied to electromyographic (EMG) data. The aim of this contribution is to analyze the differences in the muscle synergies extracted using a standard pre-processing procedure and a new procedure. The new procedure is based on the selection of the muscle's principal activations (necessary actuations of the muscle to accomplish its specific biomechanical task during gait), discarding secondary activations (with an auxiliary function in motor control). EMG signals were recorded from 12 muscles of a healthy volunteer who was asked to walk, at self-selected pace, for 5 minutes. A dataset of 193 gait cycles was collected and divided into 19 epochs of 10 concatenated gait cycles. The application of the new pre-processing procedure provided 5 instead of 6 muscle synergies accurately reconstructing the original EMG data matrix, and clearer and more stable neural activation commands. The new preprocessing procedure may be easily extended to the extraction of muscle synergies in other cyclic movements, such as running, stair climbing, cyclo-ergometer exercising, and swimming.