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Previous research has shown that neuronal activity can be used to continuously decode the kinematics of gross movements involving arm and hand trajectory. However, decoding the kinematics of fine motor movements, such as the manipulation of individual fingers, has not been demonstrated. In this study, single unit activities were recorded from task-related neurons in M1 of two trained rhesus monkey...
Simultaneously recorded electroencephalogram (EEG) and functional magnetic resonance imaging (fMRI) is rapidly emerging as a powerful neurophysiological research and clinical tool. However, the quality of the EEG, recorded in the MRI scanner, is affected by the ballistocardiogram (BCG), which is an artifact related to the cardiac cycle. The BCG has a complete spectral overlap with the EEG and is nonstationary...
The fast pace of development of upper-limb prostheses requires a paradigm shift in EMG-based controls. Traditional control schemes are only capable of providing 2 degrees of freedom, which is insufficient for dexterous control of individual fingers. We present a framework where myoelectric signals from natural hand and finger movements can be decoded with a high accuracy. 32 surface-EMG electrodes...
Advances in brain-computer interfaces (BCI) have enabled direct neural control of robotic and prosthetic devices. However, it remains unknown whether cortical signals can be decoded in real-time to replicate dexterous movements of individual fingers and the wrist. In this study, single unit activity from 115 task-related neurons in the primary motor cortex (Ml) of a trained rhesus monkey were recorded,...
Non invasive brain-computer interfaces (BCI) allow people to communicate by modulating features of their electroencephalogram (EEG). Spatiotemporal filtering has a vital role in multi-class, EEG based BCI. In this study, we used a novel combination of principle component analysis, independent component analysis and dipole source localization to design a spatiotemporal multiple source tuning (SPAMSORT)...
Dynamic synchronization between different brain regions has long been considered as the underlying neural mechanism of sensory, motor and cognitive functions. Practical methods of accurately quantifying this kind of dynamics by using scalp EEG are plagued by volume conduction effects and background noise. We propose a new method of measuring transient phase locking between independent components underlying...
A novel scheme for real time detection of ischemic features from long term electrocardiograms (ECG), based on the dilated discrete Hermite expansion is proposed. The discrete Hermite functions used for the expansion are eigenvectors of a symmetric tridiagonal matrix that commutes with the centered Fourier matrix. The ECG signals were expanded in terms of Hermite functions using a simple dot product...
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