Discrete-Time Fractional-Order Dynamical Networks Minimum-Energy State Estimation

Fractional-order dynamical networks are increasingly being used to model and describe processes demonstrating long-term memory or complex interlaced dependencies among the spatial and temporal components of a wide variety of dynamical networks. Notable examples include networked control systems or neurophysiological networks which are created...

Detecting moments of distraction during meditation practice based on changes in the EEG signal

Electroencephalography (EEG) enables online monitoring brain activity, which can be used for neurofeedback. One of the growing applications of EEG neurofeedback is to facilitate meditation practice. Specifically, EEG neurofeedback can be used to alert participants whenever they get distracted during meditation practice based on changes in their...

On Learning Discrete-Time Fractional-Order Dynamical Systems

Discrete-time fractional-order dynamical systems (DT-FODS) have found innumerable applications in the context of modeling spatiotemporal behaviors associated with long-term memory. Applications include neurophysiological signals such as electroencephalogram (EEG) and electrocorticogram (ECoG). Although learning the spatiotemporal parameters of...

Early detection of exposure to toxic chemicals using continuously recorded multi-sensor physiology

Early detection of exposure to a toxic chemical, e.g., in a military context, can be life-saving. We propose to use machine learning techniques and multiple continuously measured physiological signals to detect exposure, and to identify the chemical agent. Such detection and identification could be used to alert individuals to take...

Multisine frequency modulation of intra-epidermal electric pulse sequences: A novel tool to study nociceptive processing

A sustained sensory stimulus with a periodic variation of intensity creates an electrophysiological brain response at associated frequencies, referred to as the steady-state evoked potential (SSEP). The SSEPs elicited by the periodic stimulation of nociceptors in the skin may represent activity of a brain network that is primarily involved in...

Modeling the nonlinear cortical response in EEG evoked by wrist joint manipulation

Joint manipulation elicits a response from the sensors in the periphery which, via the spinal cord, arrives in the cortex. The average evoked cortical response recorded using electroencephalography was shown to be highly nonlinear; a linear model can only explain 10% of the variance of the evoked response, and over 80% of the response is...

Smart reading aid for detecting problems with reading fluency and comprehension

Brain signal and eye tracking technology have been intensively applied in cognitive science in order to study reading, listening and learning processes. Though promising results have been found in laboratory experiments, there are no smart reading aids that are capable to estimate difficulty during normal reading. This paper presents a new...