A novel technique for Electroencephalogram (EEG) compression is proposed in this article. This technique models the intrinsic dependency inherent between the different EEG channels. It is based on dipole fitting that is usually used in order to find a solution to the classic problems in EEG analysis: inverse and forward problems. The suggested compression system uses dipole fitting as a first building block to provide an approximation of the recorded signals. Then, (based on a smoothness factor,) appropriate coding techniques are suggested to compress the residuals of the fitting process. Results show that this technique works well for different types of recordings and is even able to provide near-lossless compression for event-related pote...
Modem applications of EEG require acquisition, storage and transmission of large amount of EEG data....
Abstract—Nearby scalp channels in multi-channel EEG data exhibit high correlation. A question that n...
Stroke is a critical event that causes the disruption of neural connections. There is increasing evi...
Electroencephalogram (EEG) signal has been widely used to analyze brain activities so as to diagnose...
Electroencephalography (EEG) is the technique of measuring electrical signals generated within the b...
In this paper, we study various lossless compression techniques for electroencephalograph (EEG) sign...
Compressive sensing is a new data compression paradigm that has shown significant promise in fields ...
The amount of data contained in electroencephalogram (EEG) recordings is quite massive and this plac...
This paper analyzes lossy data compression in the specific context of event-related potential (ERP) ...
In this paper EEG and Holter EEG data compression techniques which allow perfect reconstruction of t...
In this paper, lossless and near-lossless compression algorithms for multichannel electroencephalogr...
Objectives: We developed a method with the aim of decorrelating scalp EEG based on a set of spatial ...
A novel near-lossless compression algorithm for multichannel electroencephalogram (MC-EEG) is propos...
In this paper we present an experiment utilizing the JPEG-2000 image compression standard to compres...
In this paper a lossless and lossy Neural Compressor for electroencephalographic (EEG) signals is pr...
Modem applications of EEG require acquisition, storage and transmission of large amount of EEG data....
Abstract—Nearby scalp channels in multi-channel EEG data exhibit high correlation. A question that n...
Stroke is a critical event that causes the disruption of neural connections. There is increasing evi...
Electroencephalogram (EEG) signal has been widely used to analyze brain activities so as to diagnose...
Electroencephalography (EEG) is the technique of measuring electrical signals generated within the b...
In this paper, we study various lossless compression techniques for electroencephalograph (EEG) sign...
Compressive sensing is a new data compression paradigm that has shown significant promise in fields ...
The amount of data contained in electroencephalogram (EEG) recordings is quite massive and this plac...
This paper analyzes lossy data compression in the specific context of event-related potential (ERP) ...
In this paper EEG and Holter EEG data compression techniques which allow perfect reconstruction of t...
In this paper, lossless and near-lossless compression algorithms for multichannel electroencephalogr...
Objectives: We developed a method with the aim of decorrelating scalp EEG based on a set of spatial ...
A novel near-lossless compression algorithm for multichannel electroencephalogram (MC-EEG) is propos...
In this paper we present an experiment utilizing the JPEG-2000 image compression standard to compres...
In this paper a lossless and lossy Neural Compressor for electroencephalographic (EEG) signals is pr...
Modem applications of EEG require acquisition, storage and transmission of large amount of EEG data....
Abstract—Nearby scalp channels in multi-channel EEG data exhibit high correlation. A question that n...
Stroke is a critical event that causes the disruption of neural connections. There is increasing evi...