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The linear-envelope peak (LEP) of surface EMG signal is widely used in gait analysis to characterize muscular activity, especially in clinics. This study is designed to evaluate LEP accuracy in identifying muscular activation and assessing activation timing during walking. Surface EMG signals from gastrocnemius lateralis (GL) and tibialis anterior (TA) were analyzed in 100 strides per subject (31 healthy subjects) during ground walking. Signals were full-wave rectified and low-pass filtered (cut-off frequency=5 Hz) to extract the linear envelope. LEP accuracy in identifying muscle activations and the associated error in peak detection were assessed by direct comparison with a reference method based on wavelet transform. LEP accuracy in identifying the timing of higher signalenergy levels was also assessed, increasing the reference-algorithm selectivity. The detection error (percentage number of times when LEP falls outside the correspondent reference activation interval) is close to zero. Detection error increases up to 70% for intervals including only signal energy higher than 90% of energy peak. Mean absolute error (MAE, the absolute value of the distance between LEP timing and the correspondent actual timing of the sEMG-signal peak computed by reference algorithm) is 54.1±20.0 ms. Detection error and MAE are significantly higher (p<0.05) in TA data compared to GL signals. Differences among MAE values detected adopting different values for LE cut-off frequency are not statistically significant. LEP was found to be accurate in identifying the number of muscle activations during walking. However, the use of LEP to assess the timing of highest sEMG-signal energy (signal peak) should be considered carefully. Indeed, it could introduce a relevant inaccuracy in muscle-activation identification and peak-timing quantification. The type of muscle to analyze could also influence LEP performances, while the cut-off frequency chosen for envelope extraction appears to have a limited impact. • Linear envelope peak (LEP) is widely used to identify muscle activation during gait. • LEP accuracy is tested in 3100 strides of 31 subjects vs. a wavelet-based algorithm. • LEP provides an accurate identification of the number of activations in a stride. • The use of LEP introduces a relevant error in the quantification of EMG-peak timing. • LEP performances are also influenced by the type of muscle being analyzed. [ABSTRACT FROM AUTHOR]

Abstract: Aim of the study was to identify the different modalities of activation of gastrocnemius lateralis (GL) and tibialis anterior (TA) during gait at self-selected speed, by a statistical analysis of surface electromyographic signal from a large number (hundreds) of strides per subject. The analysis on fourteen healthy adults showed a large variability in the number of activation intervals, in their occurrence rate, and in the on-off instants, within different strides of the same walk. For each muscle, the assessment of the different modalities of activation (five for muscle) allowed to identify a single pattern, common for all the modalities and able to characterize the behavior of muscles during normal gait. The pattern of GL activity centered in two regions of the gait cycle: the transition between flat foot contact and push-off (observed in 100% of total strides) and the final swing (67.1±15.9%). Two regions characterized also the pattern of TA activity: from pre-swing to following loading response (100%), and the mid-stance (30.5±15.0%). This “normality” pattern represents the first attempt for the development in healthy young adults of a reference for dynamic EMG activity of GL and TA, in terms of variability of on-off muscular activity and occurrence rate during gait. [Copyright &y& Elsevier]

Abstract: Aim of the present study was to identify the different modalities of activation of rectus femoris (RF) during gait at self-selected speed, by a statistical analysis of surface electromyographic signal from a large number (hundreds) of strides per subject. The analysis of ten healthy adults showed that RF is characterized by different activation modalities within different strides of the same walk. RF most recurrent modality (observed in 53±6% of total strides) consists of three activations, at the beginning of gait cycle, around foot-off and in the terminal swing. Further two modalities of RF activation differ from the most recurrent one because of the lack of activity around foot-off (26±6%) or the splitting into two (or three) small activations around stance-to-swing transition (17±2%). Despite the large variability, our statistical analysis allowed to identify two patterns of activation that characterize completely the behavior of rectus femoris during gait. The first pattern, around stance-to-swing transition, can be monophasic, biphasic or triphasic and is necessary to control knee extension and hip flexion from pre-swing to initial swing. The second pattern, from terminal swing to following mid-stance, is likely due to the contribution of low-level RF activity and cross-talk from surrounding vastii. [Copyright &y& Elsevier]