Automatic determination of EMG-contaminated components and validation of independent component analysis using EEG during pharmacologic paralysis.

OBJECTIVE: Validate independent component analysis (ICA) for removal of EMG contamination from EEG, and demonstrate a heuristic, based on the gradient of EEG spectra (slope of graph of log EEG power vs log frequency, 7-70 Hz) from paralysed awake humans, to automatically identify and remove components that are predominantly EMG. METHODS: We studied the gradient of EMG-free EEG spectra to quantitatively inform the choice of threshold. Then, pre-existing EEG from 3 disparate experimental groups was examined before and after applying the heuristic to validate that the heuristic preserved neurogenic activity (Berger effect, auditory odd ball, visual and auditory steady state responses). RESULTS: (1) ICA-based EMG removal diminished EMG contamination up to approximately 50 Hz, (2) residual EMG contamination using automatic selection was similar to manual selection, and (3) task-induced cortical activity remained, was enhanced, or was revealed using the ICA-based methodology. CONCLUSION: This study further validates ICA as a powerful technique for separating and removing myogenic signals from EEG. Automatic processing based on spectral gradients to exclude EMG-containing components is a conceptually simple and valid technique. SIGNIFICANCE: This study strengthens ICA as a technique to remove EMG contamination from EEG whilst preserving neurogenic activity to 50 Hz.

Measurement of neural signals from inexpensive, wireless and dry EEG systems.

Electroencephalography (EEG) is challenged by high cost, immobility of equipment and the use of inconvenient conductive gels. We compared EEG recordings obtained from three systems that are inexpensive, wireless, and/or dry (no gel), against recordings made with a traditional, research-grade EEG system, in order to investigate the ability of these 'non-traditional' systems to produce recordings of comparable quality to a research-grade system. The systems compared were: Emotiv EPOC (inexpensive and wireless), B-Alert (wireless), g.Sahara (dry) and g.HIamp (research-grade). We compared the ability of the systems to demonstrate five well-studied neural phenomena: (1) enhanced alpha activity with eyes closed versus open; (2) visual steady-state response (VSSR); (3) mismatch negativity; (4) P300; and (5) event-related desynchronization/synchronization. All systems measured significant alpha augmentation with eye closure, and were able to measure VSSRs (although these were smaller with g.Sahara). The B-Alert and g.Sahara were able to measure the three time-locked phenomena equivalently to the g.HIamp. The Emotiv EPOC did not have suitably located electrodes for two of the tasks and synchronization considerations meant that data from the time-locked tasks were not assessed. The results show that inexpensive, wireless, or dry systems may be suitable for experimental studies using EEG, depending on the research paradigm, and within the constraints imposed by their limited electrode placement and number.