Brain-Computer Interface Signal Processing Algorithms: A Computational Cost vs. Accuracy Analysis for Wearable Computers

2012 ◽  
Author(s):  
Ali Ahmadi ◽  
Omid Dehzangi ◽  
Roozbeh Jafari
Keyword(s):  
Signal Processing ◽  
Brain Computer Interface ◽  
Computational Cost ◽  
Computer Interface ◽  
Accuracy Analysis ◽  
Wearable Computers ◽  
Signal Processing Algorithms ◽  
Processing Algorithms

Signal processing algorithms for SSVEP-based brain computer interface: State-of-the-art and recent developments

2021 ◽  
pp. 1-15
Author(s):  
Jie Hong ◽  
Xiansheng Qin
Keyword(s):  
Signal Processing ◽  
Feature Extraction ◽  
State Of The Art ◽  
Brain Computer Interface ◽  
Interface State ◽  
Computer Interface ◽  
Comprehensive Review ◽  
Recent Developments ◽  
Signal Processing Algorithms ◽  
Processing Algorithms

Over past two decades, steady-state evoked potentials (SSVEP)-based brain computer interface (BCI) systems have been extensively developed. As we all know, signal processing algorithms play an important role in this BCI. However, there is no comprehensive review of the latest development of signal processing algorithms for SSVEP-based BCI. By analyzing the papers published in authoritative journals in nearly five years, signal processing algorithms of preprocessing, feature extraction and classification modules are discussed in detail. In addition, other aspects existed in this BCI are mentioned. The following key problems are solved. (1) In recent years, which signal processing algorithms are frequently used in each module? (2) Which signal processing algorithms attract more attention in recent years? (3) Which modules are the key to signal processing in BCI field? This information is very important for choosing the appropriate algorithms, and can also be considered as a reference for further research. Simultaneously, we hope that this work can provide relevant BCI researchers with valuable information about the latest trends of signal processing algorithms for SSVEP-based BCI systems.

scholarly journals A magnetoencephalography dataset for motor and cognitive imagery-based brain-computer interface

2021 ◽  
Vol 8 (1) ◽  
Author(s):  
Dheeraj Rathee ◽  
Haider Raza ◽  
Sujit Roy ◽  
Girijesh Prasad
Keyword(s):  
Scientific Community ◽  
Brain Computer Interface ◽  
Sampling Frequency ◽  
Computer Interface ◽  
Word Generation ◽  
Machine Learning Methods ◽  
Computer Interfaces ◽  
Signal Processing Algorithms ◽  
Processing Algorithms ◽  
Healthy Participants

AbstractRecent advancements in magnetoencephalography (MEG)-based brain-computer interfaces (BCIs) have shown great potential. However, the performance of current MEG-BCI systems is still inadequate and one of the main reasons for this is the unavailability of open-source MEG-BCI datasets. MEG systems are expensive and hence MEG datasets are not readily available for researchers to develop effective and efficient BCI-related signal processing algorithms. In this work, we release a 306-channel MEG-BCI data recorded at 1KHz sampling frequency during four mental imagery tasks (i.e. hand imagery, feet imagery, subtraction imagery, and word generation imagery). The dataset contains two sessions of MEG recordings performed on separate days from 17 healthy participants using a typical BCI imagery paradigm. The current dataset will be the only publicly available MEG imagery BCI dataset as per our knowledge. The dataset can be used by the scientific community towards the development of novel pattern recognition machine learning methods to detect brain activities related to motor imagery and cognitive imagery tasks using MEG signals.

scholarly journals A Compact UWB Indoor and Through-Wall Radar with Precise Ranging and Tracking

2012 ◽  
Vol 2012 ◽  
pp. 1-11 ◽  
Author(s):  
Yinan Yu ◽  
Jian Yang ◽  
Tomas McKelvey ◽  
Borys Stoew
Keyword(s):  
Signal Processing ◽  
Theoretical Analysis ◽  
Short Range ◽  
Indoor Environment ◽  
Low Cost ◽  
Moving Target ◽  
Radiation Characteristics ◽  
Uwb Radar ◽  
Signal Processing Algorithms ◽  
Processing Algorithms

Ultrawideband (UWB) technology has many advantages compared to its narrowband counterpart in many applications. We present a new compact low-cost UWB radar for indoor and through-wall scenario. The focus of the paper is on the development of the signal processing algorithms for ranging and tracking, taking into account the particular properties of the UWB CMOS transceiver and the radiation characteristics of the antennas. Theoretical analysis for the algorithms and their evaluations by measurements are presented in the paper. The ranging resolution of this UWB radar has achieved 1-2 mm RMS accuracy for a moving target in indoor environment over a short range, and Kalman tracking algorithm functions well for the through-wall detection.

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