Simultaneous estimation of muscle fibre conduction velocity and muscle fibre orientation using 2D multichannel surface electromyogram

Abstract

The paper presents a new approach for simultaneous estimation of muscle fibre conduction velocity (MFCV) and muscle fibre orientation (MFO) for motor units (MUs) in two-dimensional (2D) multichannel surface electromyography recordings. This is an important tool for detecting changes and abnormalities in muscle function and structure. In addition, simultaneous estimation of MFO and MFCV avoids the necessity of manual electrode alignment. The proposed method detected propagating MU action potentials (MUAPs) in a running time window as moving components in amplitude maps. Thereafter, estimations were obtained by fitting a three-dimensional function to these maps. The performance was evaluated using synthetic MU signals at 10 dB SNR and authentic biceps brachii measurements. Results demonstrated MFCV and MFO estimates with standard deviations of less than 0.05 m s(-1) and 1 degrees for simulated signals, and less than 0.2 m s(-1) and 4 degrees for experimental data. However, standard deviations as low as 0.12 m s(-1) and 1.6 degrees from real signals were demonstrated. It was concluded that the method performs as well as, or better than, linear array multichannel methods when individual propagating MUAPs can be identified, even if electrodes are not aligned with fibre direction.

Automatic segmentation of surface EMG images: Improving the estimation of neuromuscular activity

“…Multi-channel EMG recordings allow for the estimation of muscle fibers direction (Grönlund et al, 2005) and the centroid of EMG amplitude , for the identification of motor unit action potentials (Holobar et al, 2009), and for the robust estimation of EMG descriptors (Farina and Falla, 2008). Insights into the localized activity within and between muscles is often obtained by visual inspection of multi-channel EMGs (Troiano et al, 2008), which is time consuming and subjective.…”

Spatial distribution of active muscle fibre characteristics in the upper trapezius muscle and its dependency on contraction level and duration

“…MFCV and MFO values were calculated using the algorithm developed by Grö nlund et al (2005a). The method utilizes the 2-D electromyograms to estimate MFCV and MFO of propagating MU action potentials (MUAPs).…”

Spatio-temporal processing of surface EMG signals from the sternocleidomastoideus muscle to assess effects of radiotherapy on motor unit conduction velocity and firing rate—A pilot study

“…The method is based on three steps: (1) detection of trajectories of individual MUAPs propagating along the muscle fibres, as recorded on the skin's surface [14], (2) estimation of their corresponding CVs [14], and (3) separation of CV estimates recorded at different locations on the skins surface [12,13]. The method is here briefly described.…”