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Effect of EMG normalisation method on calculation of co-activation of lower limb muscles during walking and running Clare Scoot, Omar Mian

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Presentation on theme: "Effect of EMG normalisation method on calculation of co-activation of lower limb muscles during walking and running Clare Scoot, Omar Mian"— Presentation transcript:

1 Effect of EMG normalisation method on calculation of co-activation of lower limb muscles during walking and running Clare Scoot, Omar Mian (scootc@lsbu.ac.uk) Sport and Exercise Science Research Centre, School of Applied Sciences References 1.Falconer & Winter (1985) Electromyogr Clin Neurophysiol. 25: 135-49. 2.Nagai et al (2011). Arch Gerontol Geriatr 53, 338–343. 3.Ortega & Farley (2015). J Electromyogr Kinesiol 25, 193–198. Introduction The degree to which muscles co-activate during movement provides insight into movement coordination. One method of expressing co-activation between antagonistic muscle pairs is as a ratio of common muscle activity to total muscle activity recorded by electromyography (EMG) (1). The EMG data that is input into this ratio is normalised using different methods by different researchers. Some normalise EMG to its value during maximum voluntary contractions (MVC) (2), whereas others normalise to its peak or average values during the gait cycle (3). This potentially makes comparison across studies difficult. The purpose of this study is to compare the effect of different methods of EMG normalisation on the level of co-activation calculated during walking and running. Methods Participants: Six healthy, young adults (5 males, 1 female; Mean ± SD age = 26 ± 7 years). Isometric MVCs: Performed on a KinCom dynamometer (Figure 1) at controlled joint angles:  Ankle plantar flexion and dorsi-flexion at 10° plantar flexion.  Knee extension and flexion at 110° knee angle (full extension = 180°) Walking & Running: On a treadmill at 4.5 km/hr and 10.5 km/hr.  Motion data: reflective markers placed on anatomical landmarks captured at 100Hz (Qualysis) (Figure 1).  Motion data and EMG recorded synchronously to estimate timing of foot contact and split data into gait cycles EMG Recording: 2000 Hz using surface electrodes:  Vastus medialis (VM), Semitendinosus (ST), Gastrocnemius Lateralis (GL), Tibialis anterior (TA)  Example in Figure 2 EMG Normalisation: EMG signals were:  Rectified and 10 Hz low pass filtered (creating EMG linear envelopes).  Then normalised to a) the level recorded during MVC and b) peak level during walking at 4.5 km/hr Co-activation between antagonist muscle pairs: Calculated by the following equation (1), Where  EMG 1 and EMG 2 are normalised EMG linear envelopes for muscles 1 and 2.  EMG min is the minimum of the two envelopes at any given moment in time, and represents the common activity. An example is given in Figure 3. Differences in co-activation calculated using EMG envelopes normalised using different methods were tested using T-tests (significance level =.05). Figure (3): Example of co-activation calculation during walking (4.5 km/hr) using data normalised to maximal voluntary contraction. Left panel: EMG linear envelopes for VM-ST muscle pair, averaged over several gait cycles. Right panel: Illustration of co-activation equation applied to this data. Vertical line denotes time of foot off within the gait cycle. Results Co-activation calculated using the different methods of EMG normalisation were numerically different, however differences were small and not statistically significant (Figure 4; blue vs red bars, P >.05). Figure (4): Group mean co-activation values (± standard deviation) for shank (GL_TA) and thigh (VM_ST) antagonist muscle pairs during walking at 4.5km/hr (left panel) and running at 10.5km/hr (right panel) using EMG linear envelopes normalised by different methods. Discussion It is concluded that the MVC and peak gait EMG normalisation methods do not produce significant differences in Falconer & Winter’s (1) co-activation index during gait. Therefore substantial differences between studies using these different normalisation methods are unlikely to be due to normalisation method. Figure (1): Left: KinCom dynamometer set up for knee extension and flexion MVCs. Right: Example stick figure representation of motion data captured during walking using Qualysis software. Figure (2): Raw EMG (mV) for the vastus medialis and semitendinosus during walking. Black vertical line denotes timing of foot strikes and blue vertical line indicates timing of foot off. VM ST Seconds (s )


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