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Human gait patterns differ considerably between the sexes. Therefore sex specific trunk muscle activation patterns can be expected. Healthy volunteers of both sexes (51 women, 55 men) walked on a treadmill at speeds from 2 to 6 km/h. Surface electormyography was recorded from five pairs of trunk muscles. Grand averaged root mean square (rms) curves and amplitude normalised curves were calculated. Mean amplitudes and relative amplitudes were calculated as well. Mean amplitudes as well as relative amplitude levels were not generally sex specific, but differed for single muscles. Grand averaged rms curves of all investigated muscles differed between sexes. At low walking speeds, differences mostly originated from mean amplitude level differences, alternating between sexes. At higher walking speeds, amplitude curves became more phasic, differences again alternated between sexes. Therefore, trunk muscle co-ordination during gait is sex-specific. Any interpretation of trunk muscle co-ordination patterns during gait requires sex specific normatives.

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ObjectivesSurface electromyography (sEMG) is a standard tool in clinical routine and clinical or psychosocial experiments also including speech research and orthodontics to measure the activity of selected facial muscles to objectify facial movements during specific facial exercises or experiments with emotional expressions. Such muscle-specific approaches neglect that facial muscles act more as an interconnected network than as single facial muscles for specific movements. What is missing is an optimal sEMG setting allowing a synchronous measurement of the activity of all facial muscles as a whole.MethodsA total of 36 healthy adult participants (53% women, 18–67 years) were included. Electromyograms were recorded from both sides of the face using an arrangement of electrodes oriented by the underlying topography of the facial muscles (Fridlund scheme) and simultaneously by a geometric and symmetrical arrangement on the face (Kuramoto scheme). The participants performed a standard set of different facial movement tasks. Linear mixed-effects models and adjustment for multiple comparisons were used to evaluate differences between the facial movement tasks, separately for both applied schemes. Data analysis utilized sEMG amplitudes and also their maximum-normalized values to account for amplitude differences between the different facial movements.ResultsSurface electromyography activation characteristics showed systematic regional distribution patterns of facial muscle activation for both schemes with very low interindividual variability. The statistical significance to discriminate between the different sEMG patterns was good for both schemes (significant comparisons for sEMG amplitudes: 87.3%, both schemes, normalized values: 90.9%, Fridlund scheme, 94.5% Kuramoto scheme), but the Kuramoto scheme performed considerably superior.ConclusionFacial movement tasks evoke specific patterns in the complex network of facial muscles rather than activating single muscles. A geometric and symmetrical sEMG recording from the entire face seems to allow more specific detection of facial muscle activity patterns during facial movement tasks. Such sEMG patterns should be explored in more clinical and psychological experiments in the future.