Abstract:
Motor units are the smallest functional units of our movements. The study of their activation provides a window into the mechanisms of neural control of movement in human...Show MoreMetadata
Abstract:
Motor units are the smallest functional units of our movements. The study of their activation provides a window into the mechanisms of neural control of movement in humans. The classic methods for motor unit investigations date to several decades ago. They are based on invasive recordings with selective needle or wire electrodes. Conversely, the noninvasive (surface) EMG has been commonly processed as an interference signal, with the extraction of its global characteristics, e.g., amplitude. These characteristics, however, are only crudely associated to the underlying motor unit activities. In the last decade, methods have been proposed for reliably extracting individual motor unit activities from the interference surface EMG signal. We describe these methods in this review, with a focus on blind source separation (BSS) and techniques used on decomposed EMG signals. For example, from the motor unit discharge timings, information can be extracted regarding the synaptic input received by the corresponding motor neurons. In reviewing these methods, we also provide examples of applications in representative conditions, such as pathological tremor. In conclusion, we provide an overview of processing methods of the surface EMG signal that allow a reliable characterization of individual motor units in vivo in humans.
Published in: Proceedings of the IEEE ( Volume: 104, Issue: 2, February 2016)
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- IEEE Keywords
- Index Terms
- Human Movement ,
- Motor Unit ,
- Electrode ,
- Motor Neurons ,
- Unit Of Activity ,
- Global Features ,
- Time Of Discharge ,
- Source Separation ,
- Blind Source Separation ,
- Motor Unit Action ,
- Electromyogram Signals ,
- General Condition ,
- Probability Density Function ,
- Phase Velocity ,
- Independent Component Analysis ,
- Autocorrelation Function ,
- Spatial Filter ,
- Joint Capsule ,
- Conduction Velocity ,
- Spike Trains ,
- Common Input ,
- Number Of Motor Units ,
- Volume Conductor ,
- Action Potential Duration ,
- Number Of Motor Neurons ,
- Separate Vectors ,
- Essential Tremor ,
- Neural Drive ,
- Motoneuron Pool ,
- Muscle Unit
- Author Keywords
Keywords assist with retrieval of results and provide a means to discovering other relevant content. Learn more.
- IEEE Keywords
- Index Terms
- Human Movement ,
- Motor Unit ,
- Electrode ,
- Motor Neurons ,
- Unit Of Activity ,
- Global Features ,
- Time Of Discharge ,
- Source Separation ,
- Blind Source Separation ,
- Motor Unit Action ,
- Electromyogram Signals ,
- General Condition ,
- Probability Density Function ,
- Phase Velocity ,
- Independent Component Analysis ,
- Autocorrelation Function ,
- Spatial Filter ,
- Joint Capsule ,
- Conduction Velocity ,
- Spike Trains ,
- Common Input ,
- Number Of Motor Units ,
- Volume Conductor ,
- Action Potential Duration ,
- Number Of Motor Neurons ,
- Separate Vectors ,
- Essential Tremor ,
- Neural Drive ,
- Motoneuron Pool ,
- Muscle Unit
- Author Keywords