EMG patterns during running: Intra- and inter-individual variability

Guidetti, Laura; Rivellini, Gianfranco; Figura, Francesco

doi:10.1016/1050-6411(95)00015-1

Cited by 70 publications

(68 citation statements)

References 13 publications

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“…When applying the current study's results to the elecromyographical investigations in the literature, EMG peaks relative to FS of 6.8 ± 2.8 ms for the rectus femoris, and 9.5 ± 4.7 ms for the tibialis anterior muscles were found [4]. Based on the current study's results, it can be stated that M3 is the only method which can be used to define these EMG peaks accurately relative to FS.…”

Section: Discussionsupporting

confidence: 53%

“…Furthermore, the accuracy of electromyographical (EMG) investigations (EMG onset and EMG peak value) of lower limb muscles is based on an accurately determining FS. Relative to FS, Guidetti et al [4] found EMG peaks of 6.8 ± 2.8 ms for rectus femoris, 11.1 ± 5.3 ms for gastrocnemius, and 9.5 ± 4.7 ms for tibialis anterior muscles when running at 4.2 m/s. The short latency between FS and EMG peak emphasizes the importance of accurate and precise FS detection.…”

Section: Introductionmentioning

confidence: 99%

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Which Method Detects Foot Strike in Rearfoot and Forefoot Runners Accurately when Using an Inertial Measurement Unit?

2017

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Accelerometers and gyroscopes are used to detect foot strike (FS), i.e., the moment when the foot first touches the ground. However, it is unclear whether different conditions (footwear hardness or foot strike pattern) influence the accuracy and precision of different FS detection methods when using such micro-electromechanical sensors (MEMS). This study compared the accuracy of four published MEMS-based FS detection methods with each other and the gold standard (force plate) to establish the most accurate method with regard to different foot strike patterns and footwear conditions. Twenty-three recreational runners (12 rearfoot and 11 forefoot strikers) ran on a 15-m indoor track at their individual running speed in three footwear conditions (low to high hardness). MEMS and a force plate were sampled at a rate of 3750 Hz. Individual accuracy and precision of FS detection methods were found which were dependent on running styles and footwear conditions. Most of the methods were characterized by a delay which generally increased from rearfoot to forefoot strike pattern and from high to low midsole hardness. It can be concluded that only one of the four methods can accurately determine FS in a variety of conditions.

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Section: Discussionsupporting

confidence: 53%

Section: Introductionmentioning

confidence: 99%

Which Method Detects Foot Strike in Rearfoot and Forefoot Runners Accurately when Using an Inertial Measurement Unit?

2017

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“…First, this 5 could be due to the fact that subjects had a different optimal number of spatial modules, 6 thus requiring different muscle groupings. Second, such inter-subject differences in mus-7 cle synergies have been reported in previous studies (Hug et al, 2010;Guidetti et al, 1996;8 Frère and Hug, 2012) and are expected to be more pronounced when more muscles are 9 recorded. Indeed, in complex motor tasks (e.g.…”

Section: Cc-by-nc-nd 40 International License Not Peer-reviewed) Is supporting

confidence: 52%

Space-by-time modular decomposition effectively describes whole-body muscle activity during upright reaching in various directions

Hilt

Delis

Pozzo

et al. 2017

Preprint

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The modular control hypothesis suggests that motor commands are built 1 from precoded modules whose specific combined recruitment can allow the 2 performance of virtually any motor task. Despite considerable experimental 3 support, this hypothesis remains tentative as classical findings of reduced di-4 mensionality in muscle activity may also result from other constraints (biome-5 chanical couplings, data averaging or low dimensionality of motor tasks). 6Here we assessed the effectiveness of modularity in describing muscle activity 7 in a comprehensive experiment comprising 72 distinct point-to-point whole-

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“…Tibialis activity starts at take-off and ends at touchdown, with peak activation before touchdown (Gazendam and Hof, 2007;. On level ground, the movement is periodic and the activity patterns are fairly repetitive (Gazendam and Hof, 2007;Guidetti et al, 1996;Ishikawa et al, 2007;.…”

Section: Introductionmentioning

confidence: 99%

Preparing the leg for ground contact in running: the contribution of feed-forward and visual feedback

Müller

Häufle

Blickhan

2014

Journal of Experimental Biology

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While running on uneven ground, humans are able to negotiate visible but also camouflaged changes in ground level. Previous studies have shown that the leg kinematics before touch down change with ground level. The present study experimentally investigated the contributions of visual perception (visual feedback), proprioceptive feedback and feed-forward patterns to the muscle activity responsible for these adaptations. The activity of three bilateral lower limb muscles (m. gastrocnemius medialis, m. tibialis anterior and m. vastus medialis) of nine healthy subjects was recorded during running across visible (drop of 0, −5 and −10 cm) and camouflaged changes in ground level (drop of 0 and −10 cm). The results reveal that at touchdown with longer flight time, m. tibialis anterior activation decreases and m. vastus medialis activation increases purely by feed-forward driven (flight time-dependent) muscle activation patterns, while m. gastrocnemius medialis activation increase is additionally influenced by visual feedback. Thus, feed-forward driven muscle activation patterns are sufficient to explain the experimentally observed adjustments of the leg at touchdown.

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EMG patterns during running: Intra- and inter-individual variability

Cited by 70 publications

References 13 publications

Which Method Detects Foot Strike in Rearfoot and Forefoot Runners Accurately when Using an Inertial Measurement Unit?

Which Method Detects Foot Strike in Rearfoot and Forefoot Runners Accurately when Using an Inertial Measurement Unit?

Space-by-time modular decomposition effectively describes whole-body muscle activity during upright reaching in various directions

Preparing the leg for ground contact in running: the contribution of feed-forward and visual feedback

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