Abstract
Recently, the statistical analysis of muscle activation patterns highlighted that not only one, but several activation patterns can be identified in the gait of healthy adults, with different occurrence. Although its potential, the application of this approach in pathological populations is still limited and specific implementation issues need to be addressed. This study aims at applying a statistical approach to analyze muscle activation patterns of gait in Parkinson’s Disease, integrating gait symmetry and co-activation. Surface electromyographic signal of tibialis anterior and gastrocnemius medialis were recorded during a 6-min walking test in 20 patients. Symmetry between right and left stride time series was verified, different activation patterns identified, and their occurrence (number and timing) quantified, as well as the co-activation of antagonist muscles. Gastrocnemius medialis presented five activation patterns (mean occurrence ranging from 2% to 43%) showing, with respect to healthy adults, the presence of a first shorted and delayed activation (between flat foot contact and push off, and in the final swing) and highlighting a new second region of anticipated activation (during early/mid swing). Tibialis anterior presented five activation patterns (mean occurrence ranging from 3% to 40%) highlighting absent or delayed activity at the beginning of the gait cycle, and generally shorter and anticipated activations during the swing phase with respect to healthy adults. Three regions of co-contraction were identified: from heel strike to mid-stance, from the pre- to initial swing, and during late swing. This study provided a novel insight in the analysis of muscle activation patterns in Parkinson’s Disease patients with respect to the literature, where unique, at times conflicting, average patterns were reported. The proposed integrated methodology is meant to be generalized for the analysis of muscle activation patterns in pathologic subjects.
Highlights
Surface electromyography is widely used in clinical gait analysis [1,2]: amplitude, time, frequency-based parameters, and conduction velocity of muscle fibers can be investigatedElectronics 2020, 9, 1641; doi:10.3390/electronics9101641 www.mdpi.com/journal/electronicsElectronics 2020, 9, 1641 to characterize muscle activity from sEMG [3,4]
The statistical analysis of muscle activity over multiple decades of consecutive strides in ecological conditions highlighted that one, but several activation patterns can be identified with different statistical occurrence in the same walking trial, usually one prevalent pattern accompanied by few less frequent, but still statistically significant ones [4,12,13,14,15,16]
The aim of the present study was to apply a statistical approach to the analysis of sEMG to identify gastrocnemius medialis (GM) and tibialis anterior (TA) activation patterns in the gait of Parkinson’s Disease (PD) patients, taking potential stride asymmetries into account
Summary
Surface electromyography (sEMG) is widely used in clinical gait analysis [1,2]: amplitude-, time-, frequency-based parameters, and conduction velocity of muscle fibers can be investigatedElectronics 2020, 9, 1641; doi:10.3390/electronics9101641 www.mdpi.com/journal/electronicsElectronics 2020, 9, 1641 to characterize muscle activity from sEMG [3,4]. Temporal parameters, i.e., the on/off timing of muscle activation, have become a de-facto standard for the clinical assessment of gait [5,6,7]. A single reference activation pattern is considered, resulting from the analysis of a limited number of strides (i.e., usually few units over a limited number of trials) acquired in laboratory conditions [11]. The statistical analysis of muscle activity over multiple decades of consecutive strides in ecological conditions highlighted that one, but several activation patterns can be identified with different statistical occurrence in the same walking trial, usually one prevalent pattern accompanied by few less frequent, but still statistically significant ones [4,12,13,14,15,16]
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