A wavelet analysis was developed to measure the timing of multiunit bursts in surface electromyograms (EMGs) from single trials. EMG data were taken from eleven elbow and/or shoulder muscles during reaching movements in six different directions, at a range of speeds. A relatively simple wavelet (db2) was chosen, and the analysis focused on wavelet coefficients at an intermediate scale (D3), where the wavelet length approximately matched the wavelengths present in EMG bursts. Burst times were identified from the peaks of the coefficient traces and were plotted as a function of movement time. Linear regression revealed significant relations in most cases, and thus served to validate the wavelet burst identification. With a few exceptions, burst timing scaled in a manner approximately similar to the scaling of movement time. As shown previously with different analytical methods, both within and across joints, EMG bursts were not confined to distinct 'agonist' and 'antagonist' time frames, but instead showed a variety of phases relative to speed or joint torque.
Bibliographical noteFunding Information:
I thank Drs Sara T. Murray, John F. Soechting, and Gilbert Strang for help and support. This work was supported by a grant from the National Institute of Neurological Disorders and Stroke, R01 NS27484.
- Event detection
- Motor pattern generation
- Triphasic pattern