scholarly journals Development of the Electroencephalograph-based Brain Computer Interface System

2021 ◽  
Vol 2078 (1) ◽  
pp. 012079
Author(s):  
Xiang Gao ◽  
Gesangzeren Fnu ◽  
Xianshu Wan
Keyword(s):  
Signal Classification ◽  
Computer Interface ◽  
Signal Acquisition ◽  
Processing Unit ◽  
Overall Design ◽  
Accurate Performance ◽  
Three Stages ◽  
And Performance ◽  
Design Challenges ◽  
Application Design

Abstract A practical BCI-based application design contains a variety of design stages are needed to be considered. The design challenges are majorly present in 3 major stages: brain signal acquisition, signal processing unit, and signal classification. Combinations of different approaches have to be employed to achieve the functional and accurate performance of the overall design. Those design choices, algorithms, and methodologies that are meant to solve design challenges presented in the previously mentioned three stages have become a hot subject of a number of studies. This paper aims at providing a thorough overview of existing methodologies for BCI-based application design, comparing their principles and performance and recommending suitable design choices that would yield an objective result for the application.

An FPGA-Based Brain-Computer Interface for Wireless Electric Wheelchairs

2013 ◽  
Vol 284-287 ◽  
pp. 1616-1621 ◽  
Author(s):  
Jzau Sgeng Lin ◽  
Sun Ming Huang
Keyword(s):  
Signal Processing ◽  
Brain Computer Interface ◽  
Computer Interface ◽  
Signal Acquisition ◽  
Processing Unit ◽  
Electric Wheelchair ◽  
Brain Waves ◽  
Compact Size ◽  
Bci System ◽  
Signal Processing Unit

A wireless EEG-based brain-computer interface (BCI) and an FPGA-based system to control electric wheelchairs through a Bluetooth interface was proposed in this paper for paralyzed patients. Paralytic patients can not move freely and only use wheelchairs in their daily life. Especially, people getting motor neuron disease (MND) can only use their eyes and brain to exercise their willpower. Therefore, real-time EEG and winking signals can help these patients effectively. However, current BCI systems are usually complex and have to send the brain waves to a personal computer or a single-chip microcontroller to process the EEG signals. In this paper, a simple BCI system with two channels and an FPGA-based circuit for controlling DC motor can help paralytic patients easily to drive the electric wheelchair. The proposed BCI system consists of a wireless physiological with two-channel acquisition module and an FPGA-based signal processing unit. Here, the physiological signal acquisition module and signal processing unit were designed for extracting EEG and winking signals from brain waves which can directly transformed into control signals to drive the electric wheelchairs. The advantages of the proposed BCI system are low power consumption and compact size so that the system can be suitable for the paralytic patients. The experimental results showed feasible action for the proposed BCI system and drive circuit with a practical operating in electric wheelchair applications.

scholarly journals Indices of Heart Rate Variability and Performance During a Response-Conflict Task Are Differently Associated With ADHD and Autism

2021 ◽  
pp. 108705472097279
Author(s):  
Alessio Bellato ◽  
Iti Arora ◽  
Puja Kochhar ◽  
Chris Hollis ◽  
Madeleine J. Groom
Keyword(s):  
Heart Rate ◽  
Heart Rate Variability ◽  
Sensory Information ◽  
Response Conflict ◽  
Mediation Model ◽  
Conflict Task ◽  
Accurate Performance ◽  
And Performance ◽  
Comorbid Adhd ◽  
The Relationship

We investigated autonomic arousal, attention and response conflict, in ADHD and autism. Heart rate variability (HRV), and behavioral/electrophysiological indices of performance, were recorded during a task with low and high levels of response conflict in 78 children/adolescents (7–15 years old) with ADHD, autism, comorbid ADHD+autism, or neurotypical. ANOVA models were used to investigate effects of ADHD and autism, while a mediation model was tested to clarify the relationship between ADHD and slower performance. Slower and less accurate performance characterized ADHD and autism; however, atypical electrophysiological indices differently characterized these conditions. The relationship between ADHD and slower task performance was mediated by reduced HRV in response to the cue stimulus. Autonomic hypo-arousal and difficulties in mobilizing energetic resources in response to sensory information (associated with ADHD), and atypical electrophysiological indices of information processing (associated with autism), might negatively affect cognitive performance in those with ADHD+autism.

scholarly journals Independent home use of a brain-computer interface by people with amyotrophic lateral sclerosis

Neurology ◽  
2018 ◽  
Vol 91 (3) ◽  
pp. e258-e267 ◽  
Author(s):  
Jonathan R. Wolpaw ◽  
Richard S. Bedlack ◽  
Domenic J. Reda ◽  
Robert J. Ringer ◽  
Patricia G. Banks ◽  
...  
Keyword(s):  
Quality Of Life ◽  
Amyotrophic Lateral Sclerosis ◽  
Brain Computer Interface ◽  
Computer Interface ◽  
It Use ◽  
Technical Problems ◽  
Rapid Disease Progression ◽  
And Performance ◽  
Lateral Sclerosis

ObjectiveTo assess the reliability and usefulness of an EEG-based brain-computer interface (BCI) for patients with advanced amyotrophic lateral sclerosis (ALS) who used it independently at home for up to 18 months.MethodsOf 42 patients consented, 39 (93%) met the study criteria, and 37 (88%) were assessed for use of the Wadsworth BCI. Nine (21%) could not use the BCI. Of the other 28, 27 (men, age 28–79 years) (64%) had the BCI placed in their homes, and they and their caregivers were trained to use it. Use data were collected by Internet. Periodic visits evaluated BCI benefit and burden and quality of life.ResultsOver subsequent months, 12 (29% of the original 42) left the study because of death or rapid disease progression and 6 (14%) left because of decreased interest. Fourteen (33%) completed training and used the BCI independently, mainly for communication. Technical problems were rare. Patient and caregiver ratings indicated that BCI benefit exceeded burden. Quality of life remained stable. Of those not lost to the disease, half completed the study; all but 1 patient kept the BCI for further use.ConclusionThe Wadsworth BCI home system can function reliably and usefully when operated by patients in their homes. BCIs that support communication are at present most suitable for people who are severely disabled but are otherwise in stable health. Improvements in BCI convenience and performance, including some now underway, should increase the number of people who find them useful and the extent to which they are used.

SeisNoise.jl: Ambient Seismic Noise Cross Correlation on the CPU and GPU in Julia

2020 ◽  
Vol 92 (1) ◽  
pp. 517-527
Author(s):  
Timothy Clements ◽  
Marine A. Denolle
Keyword(s):  
Seismic Noise ◽  
High Performance ◽  
Cross Correlation ◽  
Graphic Processing Unit ◽  
Ambient Seismic Noise ◽  
Processing Unit ◽  
Central Processing ◽  
And Performance ◽  
Noise Cross Correlation ◽  
Performance Computing

Abstract We introduce SeisNoise.jl, a library for high-performance ambient seismic noise cross correlation, written entirely in the computing language Julia. Julia is a new language, with syntax and a learning curve similar to MATLAB (see Data and Resources), R, or Python and performance close to Fortran or C. SeisNoise.jl is compatible with high-performance computing resources, using both the central processing unit and the graphic processing unit. SeisNoise.jl is a modular toolbox, giving researchers common tools and data structures to design custom ambient seismic cross-correlation workflows in Julia.

scholarly journals Design and Verification of a Dry Sensor-Based Multi-Channel Digital Active Circuit for Human Brain Electroencephalography Signal Acquisition Systems

Micromachines ◽  
2019 ◽  
Vol 10 (11) ◽  
pp. 720
Author(s):  
Chin-Teng Lin ◽  
Chi-Hsien Liu ◽  
Po-Sheng Wang ◽  
Jung-Tai King ◽  
Lun-De Liao
Keyword(s):  
Daily Life ◽  
Event Related Potentials ◽  
Computer Interface ◽  
Signal Acquisition ◽  
Eeg Signal ◽  
Eeg Signals ◽  
Preparation Time ◽  
Active Circuit ◽  
Related Potentials ◽  
Common Application

A brain–computer interface (BCI) is a type of interface/communication system that can help users interact with their environments. Electroencephalography (EEG) has become the most common application of BCIs and provides a way for disabled individuals to communicate. While wet sensors are the most commonly used sensors for traditional EEG measurements, they require considerable preparation time, including the time needed to prepare the skin and to use the conductive gel. Additionally, the conductive gel dries over time, leading to degraded performance. Furthermore, requiring patients to wear wet sensors to record EEG signals is considered highly inconvenient. Here, we report a wireless 8-channel digital active-circuit EEG signal acquisition system that uses dry sensors. Active-circuit systems for EEG measurement allow people to engage in daily life while using these systems, and the advantages of these systems can be further improved by utilizing dry sensors. Moreover, the use of dry sensors can help both disabled and healthy people enjoy the convenience of BCIs in daily life. To verify the reliability of the proposed system, we designed three experiments in which we evaluated eye blinking and teeth gritting, measured alpha waves, and recorded event-related potentials (ERPs) to compare our developed system with a standard Neuroscan EEG system.

scholarly journals Early Feasibility Study of a Neurostimulator to Create Artificial Vision

Neurosurgery ◽  
2019 ◽  
Vol 66 (Supplement_1) ◽  
Author(s):  
Nader Pouratian ◽  
Daniel Yoshor ◽  
Soroush Niketeghad ◽  
Jessy Dornm ◽  
Robert Greenberg
Keyword(s):  
Video Processing ◽  
Visual Information ◽  
Electrode Array ◽  
Video Camera ◽  
Artificial Vision ◽  
Processing Unit ◽  
New Device ◽  
Pediatric Glaucoma ◽  
Functional Vision ◽  
And Performance

Abstract INTRODUCTION Stimulation of human visual cortex is known to elicit visual perceptions that could potentially be used for creating artificial vision. The Orion Visual Cortical Prosthesis is a new device that is intended to restore some functional vision to blind patients. METHODS The device comprises an implant (consisting of an electronics package, receiving antenna, and an electrode array with 60 electrodes); glasses with a video camera; and a video processing unit (VPU). The camera collects real-time visual information, which is then processed by the VPU and converted to stimulation patterns sent to electrode array. The electronics are skull mounted with the subdural array implanted through a posterior interhemispheric approach. This is a 5-yr study of subjects who are bilaterally blind with bare light or no light perception due to non-cortical etiology. RESULTS A total of 6 subjects have been implanted in 2 centers. As of May 1, 2019, average implant duration was 11.1 mo (range 3.4-15.0 mo). Average age at time of implant was 50.3 yr. Cause of blindness included trauma (2), pediatric glaucoma (2), optic neuropathy (1), and endophthalmitis (1). One serious adverse device event (seizure) has been reported. Average thresholds ranged from 1.6 to 3.7 mA across the 6 subjects. At 6 mo postimplant, 3 of 5 subjects performed significantly better with the system on than off on a light localization task; 2 subjects performed better on a direction of motion task, and no subjects had measurable visual acuity. All 5 subjects were rated as receiving “positive” or “mild positive” benefit on a functional vision assessment. One-year adverse event and visual performance data for the first 5 subjects will be presented and compared to results from a commercially-available retinal prosthesis. CONCLUSION Safety and performance results of the first 5 subjects as of 6 mo postimplantation appear encouraging.

Sign in / Sign up

Export Citation Format

Share Document