Henrik Baare Olsen

Evaluation of intra-muscular EMG signal decomposition algorithms

We propose and test a tool to evaluate and compare EMG signal decomposition algorithms. A model for the generation of synthetic intra-muscular EMG signals, previously described, has been used to obtain reference decomposition results. In order to evaluate the performance of decomposition algorithms it is necessary to define indexes which give a compact but complete indication about the quality of the decomposition. The indexes given by traditional detection theory are in this paper adapted to the multi-class EMG problem. Moreover, indexes related to model parameters are also introduced. It is possible in this way to compare the sensitivity of an algorithm to different signal features. An example application of the technique is presented by comparing the results obtained from a set of synthetic signals decomposed by expert operators having no information about the signal features using two different algorithms. The technique seems to be appropriate for evaluating decomposition performance and constitutes a useful tool for EMG signal researchers to identify the algorithm most appropriate for their needs.

Motor unit activity during stereotyped finger tasks and computer mouse work

Motor unit (MU) activity pattern was examined in the right-hand extensor digitorum communis muscle (EDC) during standardised finger movements simulating actual computer mouse tasks. Intramuscular recordings were performed with a quadripolar needle electrode. Nine women performed four lifts of their right-hand index finger, middle finger or both as well as a number of double clicks. Additionally, the subjects performed contra lateral activity with their left-hand fingers and for three subjects recordings were also obtained during an interview with no physical activity. Besides the expected close coupling of MU activity with finger movement, activity was observed in three different situations with no physical requirements. Attention related activity was found before or after performance of the finger movement task, contra lateral activity in right EDC during left-hand finger tasks, and activity during mental activity without any finger movements involved. A relatively large number of doublet occurrences suggest they are a natural part of the activation pattern during performance of the rapid finger movement required to perform an efficient double click on the computer mouse.

The use of EMG biofeedback for learning of selective activation of intra-muscular parts within the serratus anterior muscle: a novel approach for rehabilitation of scapular muscle imbalance.

Motor control and learning possibilities of scapular muscles are of clinical interest for restoring scapular muscle balance in patients with neck and shoulder disorders. The aim of the study was to investigate whether selective voluntary activation of intra-muscular parts within the serratus anterior can be learned with electromyographical (EMG) biofeedback, and whether the lower serratus anterior and the lower trapezius muscle comprise the lower scapula rotation force couple by synergistic activation. Nine healthy males practiced selective activation of intra-muscular parts within the serratus anterior with visual EMG biofeedback, while the activity of four parts of the serratus anterior and four parts of the trapezius muscle was recorded. One subject was able to selectively activate both the upper and the lower serratus anterior respectively. Moreover, three subjects managed to selectively activate the lower serratus anterior, and two subjects learned to selectively activate the upper serratus anterior. During selective activation of the lower serratus anterior, the activity of this muscle part was 14.4+/-10.3 times higher than the upper serratus anterior activity (P<0.05). The corresponding ratio for selective upper serratus vs. lower serratus anterior activity was 6.4+/-1.7 (P<0.05). Moreover, selective activation of the lower parts of the serratus anterior evoked 7.7+/-8.5 times higher synergistic activity of the lower trapezius compared with the upper trapezius (P<0.05). The learning of complete selective activation of both the lower and the upper serratus anterior of one subject, and selective activation of either the upper or lower serratus anterior by five subjects designates the promising clinical application of EMG biofeedback for restoring scapular muscle balance. The synergistic activation between the lower serratus anterior and the lower trapezius muscle was observed in only a few subjects, and future studies including more subjects are required before conclusions of a lower scapula rotation couple can be drawn.

The importance of the work/rest pattern as a risk factor in repetitive monotonous work.

Abstract The work cycle time is an important parameter in assessing the risk for development of musculoskeletal disorders caused by repetitive monotonous work. The work/rest pattern in the work cycle time may be an even more important factor. Based on the normalized work cycle time for 48 meat cutters, a “slow” group (121.0–138.9% of the mean work time) and a “fast” group (68.4–85.5% of the mean work time) were defined. During work, the mean muscle activity level for the wrist extensor was 20% of the reference value, and the flexor muscles were 40% of the reference value. No differences were observed between the “slow” and the “fast” group of meat cutters. Electrophysiological signs of muscle fatigue in the power spectrum analysis from the EMG signals registered during meat cutting showed no differences between the groups. Meat cutting work seems to be performed with a stereotyped muscle activity pattern with only small variations for the forearm muscles. Regardless of a rather large difference in the work/rest pattern between the two groups of meat cutters, no differences were found in any of the measured acute physiological responses. To evaluate the risk of the workload, more comprehensive variables must be included in addition to the work cycle time and the work/rest pattern. Relevance to industry One explanation for the high frequencies of musculoskeletal disorders has been suggested to be the speed of work. A way to estimate the speed of work is to measure the work cycle time and the work/rest pattern. The purpose of this study is to evaluate the work/rest pattern as a risk factor.