Averaged EMG profiles in jogging and running at different speeds

Gazendam, Marnix G.J.; Hof, At L.

doi:10.1016/j.gaitpost.2006.06.013

Cited by 139 publications

(130 citation statements)

References 22 publications

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“…It can be seen that there were different increases of activity of the muscles belonging to the same muscular group. This finding is in line with Gazendam & Hof (2007), who found that the relationship between speed and muscular effort was generally different between muscles of the same group. The activity peak of muscles belonging to the same group could be very different (RF and VM) or quite similar (BF and ST).…”

Section: Peak Amplitude Of Myoelectric Activity and Relative Incrementsupporting

confidence: 92%

“…Figure 1 shows that the muscular activity profiles of five out of the six studied muscles for each leg were similar in walking and in jogging, although there were differences in the sequence of movement arches of hip and knee corresponding to the phases of support and non-support, and also in the direction of the movement arches of the ankle. The above-mentioned findings support other studies, such as those of Gazendam & Hof (2007); Mann & Hagy (1980);Mann (1982);and Ounpuu (1994). Figure 1 also shows that there was a similar pattern (nearly identical) between the grand ensemble averages of muscular activity in both legs.…”

Section: Reliability Of the S-emg Signalsupporting

confidence: 91%

“…For the muscles studied, the obtained functional patterns for walking and for jogging were similar to those already published (Gazendam & Hof, 2007;Mann & Hagy, 1980;Mann, 1982;and Ounpuu, 1994). Inter-subject variability was determined by averaging the un-normalized and normalized EAV of the 10 subjects (GEAV).…”

Section: Reliability Of the S-emg Signalsupporting

confidence: 84%

“…In all the above-mentioned papers the muscle activity was recorded from only one leg, and the muscular activity was qualitatively described rather than quantified. Nilsson et al (1985) and Gazendam and Hof (2007) quantified the profiles of averaged rectified EMGs at different speeds of locomotion and mode of progression in humans on motor-driven treadmill.…”

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Walking and Jogging: Quantification of Muscle Activity of the Lower Extremities

Gavilanes-Miranda¹,

Gandarias²,

García³

2011

Advances in Applied Electromyography

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Section: Peak Amplitude Of Myoelectric Activity and Relative Incrementsupporting

confidence: 92%

Section: Reliability Of the S-emg Signalsupporting

confidence: 91%

Section: Reliability Of the S-emg Signalsupporting

confidence: 84%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Walking and Jogging: Quantification of Muscle Activity of the Lower Extremities

Gavilanes-Miranda¹,

Gandarias²,

García³

2011

Advances in Applied Electromyography

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“…Threshold calculation is applied as follows: Video sequences from the KTH and Weizmann datasets are normalized on the basis of number of frames and the time of a particular sequence for an activity. The threshold is calculated on the basis of a case study given in [29]. To recognize the actions, we establish the features of each action from the parameters of human model as follows: Walking feature: In case of walking action, every part of human move generally and approximately in the same direction and speed.…”

Section: Feature Extractionmentioning

confidence: 99%

Analysis of Gait Pattern to Recognize the Human Activities

Gupta¹,

Dixit²,

Semwal³

2014

IJIMAI

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-Human activity recognition based on the computer vision is the process of labelling image sequences with action labels. Accurate systems for this problem are applied in areas such as visual surveillance, human computer interaction and video retrieval. The challenges are due to variations in motion, recording settings and gait differences. Here we propose an approach to recognize the human activities through gait. Activity recognition through Gait is the process of identifying an activity by the manner in which they walk. The identification of human activities in a video, such as a person is walking, running, jumping, jogging etc are important activities in video surveillance. We contribute the use of Model based approach for activity recognition with the help of movement of legs only. Experimental results suggest that our method are able to recognize the human activities with a good accuracy rate and robust to shadows present in the videos.

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Electromyography activity across gait and incline: The impact of muscular activity on human morphology

Wall-Scheffler

Chumanov

Steudel-Numbers

et al. 2010

American J Phys Anthropol

100

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The study of human evolution depends upon a fair assessment of the ability of hominin individuals to gain access to necessary resources. We expect that the morphology of extant and extinct populations represents a successful locomotory system that allowed individuals to move across the environment gaining access to food, water and mates while still maintaining excess energy to allocate to reproduction. Our assessment of locomotor morphology must then incorporate tests of fitness within realistic environments-environments that themselves vary in terrain and whose negotiation requires a variety of gait and speeds. This study assesses muscular activity (measured as the integrated signal from surface electromyography) of seven thigh and hip muscle groups during walking and running across a wide range of speeds and inclines, in order to systematically assess the role that morphology can play in minimizing muscular activity and thus energy expenditure. Our data suggest that humans are better adapted to walking than running at any slope, as evidenced by small confidence intervals and even trends across speed and incline. We find that while increasing task intensity unsurprisingly increases muscular activity in the lower limb, individuals with longer limbs show significantly reduced activity during both walking and running, especially in the hip adductors, gluteus maximus and hamstring muscles. People with a broader pelvis show significantly reduced activity while walking in the hip adductor and hamstring muscles. Keywords human locomotion; EMG; incline; gluteus maximusIn the study of human locomotion, it has been generally suggested that muscle activity, as measured using electromyography (EMG), will offer important clues to selective pressures shaping the locomotor elements of human form (Basmajian, 1972;Zihlman, 1978;Tuttle et al., 1979;Stern and Susman, 1981;Marzke et al., 1988;Lieberman et al., 2006). Despite that humans perform a relatively small array of gaits [e.g. walking and running, though for (Srinivasan, 2006)], they perform them over a wide variety of terrain and with varying speed combinations. Consequently, effectively filtering through possible selection pressures on locomotor morphology requires a systematic comparison of morphology (lower limb length and pelvis breadth being a reasonable place to begin), in addition to the systematic comparison of the activity of human locomotor musculature across gait, speed and incline [for lower limb muscle activity during other activities-throwing, digging, gathering, etc.-see (Marzke et al., 1988)]. Building ecological models of mobility [e.g. (Foley, 1992;Foley and Elton, 1998;Kramer, 2004)] depends upon accurate assessments of the benefits of bipedalism, and the benefits of bipedalism cannot be understood without better modelling of the influence of variable terrain and non-level surfaces. To this end integrating the interactions between speed and incline is vital for understanding selection on hominin locomotor morphology, such as lower limb length a...

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Averaged EMG profiles in jogging and running at different speeds

Cited by 139 publications

References 22 publications

Walking and Jogging: Quantification of Muscle Activity of the Lower Extremities

Walking and Jogging: Quantification of Muscle Activity of the Lower Extremities

Analysis of Gait Pattern to Recognize the Human Activities

Electromyography activity across gait and incline: The impact of muscular activity on human morphology

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