ICPEF · The Interaction between the Central and Peripheral Exercise-Related Fatigue

The Interaction between the Central and Peripheral Exercise-Related Fatigue

The interaction between fatigue and neuromuscular activation has been under intensive research for more than a century. Nevertheless, it remains one of the most challenging research topics in neurophysiology. Many excellent pioneering works have illuminated the interaction between the feedback from the fatiguing muscles and the degree of neuromuscular activation in the working limbs, so called central motor command. The factors influencing the development of fatigue involve both peripheral and central aspects. However, the research investigating the interactions among these factors is still in its infancy, with many concepts yet to be clarified. The first activities in this project focused on the analytical modelling of cortical and muscular electrical signals. A complex and innovative analytical model for studying common inputs sent by cortical areas to the pool of motor neurons has been developed. The model includes the non-linear behaviour of the motor neurons and mathematically describes the spectral characteristics of the cumulative spike train as output of the pool of motor neurons in relation to the strength of the cortical synaptic input. The model has been investigated analytically by providing formulations for the characteristics of the simulated signals as well as for the coherence between the simulated cortical activity and the motor neuron output (muscle part). As an important achievement, this model and its analytical characterization allow the investigation of the factors of influence in the study of corticospinal connectivity by corticomuscular coherence. The next step was the development of novel signal processing techniques for high-density surface EMG and EEG analysis. Three novel methods for processing high-density surface EMG and EEG were developed, each of them with an important impact in our ability to study the neuromuscular system in vivo in humans during natural movements. The first new method developed is an extension of the technique called EMG-EMG coherence, which is usually applied after rectification (absolute value) of the surface EMG. However this pre-processing has been demonstrated to be sensible to filtering and cancellation and these effects can dramatically alter the estimated magnitude of the coherence. Instead of EMG rectification we proposed a novel multichannel approach, based on an Activity Index extracted from high-density surface EMG signals. With this approach we demonstrated that it is possible to detect sources of common synaptic input to motor neurons also in cases when the frequency of input is outside the surface EMG bandwidth. A second method developed during this project relates to the detection of artefacts from EEG recordings. The EEG features of interest are indeed typically embedded within the ongoing EEG activity and various artefacts that hinder their extraction. A method for the automatic detection of artefacts in multichannel electroencephalograms (EEG) was developed. The technique is based on higher-order statistics of acquired EEG and is capable to identify different types of EEG artefacts, such as eye blinking, eye movements, mouth movements, and head movements, etc. Finally, a powerful method for extracting the association between cortical and muscular activity was developed. The method is based on the decomposition of high-density surface EMG on the individual motor units and the EMG-informed identification of cortical oscillations from the concurrently recorded EEG. The method is based on the assumption that oscillatory component in EEG is phase-locked to the discharge patterns of identified motor units. In comparison to corticomuscular coherence which is commonly used to study EMG-EEG connectivity, our novel method provides consistent results on shorter time intervals of analyzed signals and is therefore better suited for on-line applications. Unlike the corticomuscular coherence that analyses global frequency content of EMG and EEG, the method enables us to study relationships between individual motor units and cortical oscillations. Therefore, the main outcome of the project is a set of innovative and advanced methods for the study of muscular and cortical activity, and their interactions, during motor tasks. These methods provide a new way of looking at the neural determinants of movements non-invasively and can thus be important in the areas of neuroscience, motor control, and clinical sciences. With its strong multidisciplinary nature, the project ICPEF promoted the exploitation of the state-of-the-art knowledge in the field of neurophysiology, electronics and signal processing. It aimed to complete and diversify the Fellow’s expertise, which was, before ICPEF, mainly focused on the basic research in biomedical signal processing. Building long-lasting collaborative partnership between the researcher, academic institutions and different SMEs, the project enhanced the researcher’s expertise in research management, communication skills, networking, team working and decision-making, which had been absent in his previous academic training. By introducing the Fellow to many new contacts, the project also significantly contributed to both the professional development of the researcher’s innovativeness as well as his scientific knowledge. Among the various contacts made, the one that directly influenced the researcher’s future career has been the interaction with Tyromotion, a SME producing devices for robotic rehabilitation. This company was interested in the cooperation with the Fellow because of the skills he has shown during ICPEF, especially on the acquisition and analysis of muscular signals that can be used to improve the procedure of robotic rehabilitation. The Fellow is currently an employee of this company. The project ICPEF represents a major breakthrough in the combined analysis of high-density surface EMG and EEG signals, promoting and facilitating the scientific and technological excellence in Europe and significantly contributing to the improvement of European research policy, especially in the health sector. The advanced methods for analysis of muscular and cortical signals developed in the project are having and will have the potential to be exploited in various applications, such as helping patients with tremor, for improving the neurorehabilitation procedures, brain-computer interfaces, and biomedical research in general.

Data: CORDIS, © European Union