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In this contribution we present first investigations for the signal processing on Micro Electrode Arrays (MEAs) used to observe the growth of biological neural networks. Neural cells produce ion currents, which can be measured extracellularly as differences in electric potentials. In order to measure these potentials (spikes), neuronal stem cells are cultivated on the surface of MEAs. These stem cells...
Goal of this study was to verify the usability of a novel linear parameter varying (LPV) identification technique for the identification of time-varying joint impedance. Quantification of neuromechanical parameters describing joint impedance improves understanding of human movement control and is of clinical relevance for diagnostics and treatment monitoring of patients suffering from movement disorders...
This paper presents a novel computer-aided system for assisting schizophrenia (SZ) diagnosis. Power Spectral Density Ratios (PSDRs) covering 7 brain regions and 5 frequency sub-bands are extracted as features, from single-trial magnetoencephalography (MEG) recorded while subjects read sentence stimuli silently. A two-stage feature selection algorithm combining F-score and Adaptive Boosting (Adaboost)...
The chemical, mechanical, and electrochemical attributes of the Parylene sheath electrode (PSE) were evaluated following a post-fabrication thermoforming process to determine its impact on both the polymer and thin film platinum materials. The three-dimensional conical shape of the PSE was formed via thermal molding of a surface micromachined Parylene C microchannel using a custom shape-forming microwire...
Brain-Computer Interfaces (BCI) can provide innovative solutions beyond the medical domain. In human research, visuospatial attention is often assessed from shifts in head or gaze orientation. However in some critical situations, these behavioral features can be dissociated from covert attention processes and brain features may indicate more reliably the spatial focus of attention. In this context,...
The robustness of myo-electric prosthesis usage is largely influenced by user performance, where psychological factors (i.e. cognitive-skills, motor-skills and psychological status — such as motivation, will, and stress) play a prominent role. These factors become more important the more degrees of freedom (DOF) a multifunctional prosthesis provides. Despite the large amount of research efforts during...
It has been hypothesized that propriospinal neurons (PNs) in the C3-C4 spinal cord mediates cortical motor commands to the peripheral muscles during tremor in patients with Parkinson's disease (PD). However, there has been no direct evidence so far to support the role of PN in transmitting tremor commands. In this paper, we report the positive correlation of cutaneous afferents with reduction in tremor...
Deep brain stimulation (DBS) of the periaqueductal gray (PAG) has been shown to be an option for chronic pain inhibition. Drawbacks exist due to electrical stimulation doses given in an open-loop and manual fashion based on patients' subjective feedback. In response, we have developed a closed-loop system capable of detecting nociceptive signals from the spinal cord while delivering electrical stimulation...
This paper develops a new closed-loop strategy for deep brain stimulation, derived using a model-based analysis of the basal ganglia. The system is described using a firing-rate model that has been proposed recently in the literature, in order to analyze the generation of beta-band oscillations. On this system, a proportional regulation of the firing-rate compensates the loss of stability of the subthalamo-pallidal...
In this study, modulation index (MI) features derived from local field potential (LFP) recordings in the sub-thalamic nucleus (STN) and electroencephalographic recordings (EEGs) from the primary motor cortex are shown to correlate with both the overall motor impairment and motor subscores in a monkey model of parkinsonism. The MI features used are measures of phase-amplitude cross frequency coupling...
Deep brain stimulation (DBS) effectively suppresses the pathological neural activity associated with Parkinson's disease, with a parallel improvement in motor symptoms of the disease observed. However, its exact mode of action is not fully understood. This study explores a fourth order computational model of neural synchrony and applied stimulation using established nonlinear control systems theory...
We simulate how a two-class brain-computer interface automatically adapts to post-movement imagery bursts of beta band activity (beta rebound) measured in the electroencephalogram at Cz. We used data from 20 healthy, novice volunteers. By combining an adaptive BCI approach with beta rebound features we hypothesize to attain better performance for more users, higher usability and lower setup time than...
Electrocorticography, thanks to its low degree of invasiveness, has received in recent years an increasing attention for chronic brain-machine interface applications. To be up to the task, electrocorticography electrode arrays can benefit from several improvements. Better recording abilities can be obtained through smaller, low impedance and high density electrodes, while conformability can provide...
We present a dual-chamber co-culturing device that permits investigations on network electrophysiology and functional connectivity. In this work, we characterized the dynamics and functional connectivity of interconnected homogeneous and heterogeneous cultures to demonstrate usefulness of this approach. Segregating two neuronal populations while simultaneously guaranteeing certain degree in controlling...
The development of brain computer interfaces (BCIs) for patient rehabilitation is a growing field of research. The BCI experimental paradigms consist mainly of selective attention BCI models and motor imagery (MI) BCIs. Selective attention models require an external stimulus (screen) but achieve high rates of classification accuracy fairly quickly. MI systems do not require external stimuli but require...
It is hypothesized that a dysfunction of the supplementary motor area (SMA), secondary to a deficit of the nigrostriatal dopamine system, partially contributes to the symptomatology of Parkinson's disease (PD), i.e., akinesia. In this pilot study we investigated the effect of real-time fMRI neurofeedback based volitional up-regulation of the SMA on hand motor performance of one PD patient and 3 healthy...
A process is presented for analyzing electrocor-ticographic (ECoG) recordings and prototyping brain computer interfaces in which complex signal processing chains are able to be rapidly developed and iterated in digital audio workstation (DAW) software. DAW software includes many built-in “drag and drop” blocks that perform common, low-level signal processing algorithms such as filtering and envelope...
The P300 speller is a brain-computer interface (BCI) system designed to communicate language by presenting language stimuli and detecting event related potentials in a subject's electroencephalogram (EEG) signal. The target patient population is prone to fatigue, so reducing or removing this training step could increase the amount of time available to the subject for actual BCI use. We present an...
It is widely accepted that the common spatial pattern (CSP) analysis method, albeit being very popular in brain-computer interface (BCI) applications as a feature extraction method for binary classification, is vulnerable to artifact. It could underperform when it is exposed to an input whose frequency band is too broad that many interfering frequency components are contained. These drawbacks are...
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