Tom Zurales
Current Organizations / Institutes
The organizations/institutes from the scholar's latest article
Research Subjects
Research Interests
Tom Zurales has a total of 4 co-authors. Here are the top co-authors by number of shared publications:
- Anna Martin
Department of Computer Science University of Minnesota rd Minneapolis MN USA
1 shared publication - Arshia Khan
University of Minnesota Duluth
1 shared publication - Dale Dowling
Department of Computer Science University of Minnesota Duluth Duluth USA
1 shared publication - Rupak Kumar Das
College of IST Pennsylvania State University 16801 PA USA
1 shared publication
Latest Publications
- Open Access
A Survey on EEG Data Analysis Software
Electroencephalography (EEG) is a mechanism to understand the brain’s functioning by analyzing brain electrical signals. More recently, it has been more commonly used in studies that are focused on the causation and effect of dementia. More tools are now available to gather EEG data. This brings about the challenge of understanding brain signals, which involves signal processing. Professionals with an electrical engineering background are very comfortable analyzing EEG data. Still, scientists in computer science and related fields need a source that can identify all the tools available and the process of analyzing the data. This paper deals specifically with the existing EEG data analysis tools and the processes involved in analyzing the EEG data using these tools. Furthermore, the paper goes in-depth into identifying the tools and the mechanisms of data processing techniques. In addition, it lists a set of definitions required for a better understanding of EEG data analysis, which can be challenging. The purpose of this paper is to serve as a reference for not only scientists that are new to EEG data analysis but also seasoned scientists that are looking for a specific data component in EEG and can go straight to the section of the paper that deals with the tool that they are using.
Open AccessA Survey on EEG Data Analysis Software
Electroencephalography (EEG) is a mechanism to understand the brain’s functioning by analyzing brain electrical signals. More recently, it has been more commonly used in studies that are focused on the causation and effect of dementia. More tools are now available to gather EEG data. This brings about the challenge of understanding brain signals, which involves signal processing. Professionals with an electrical engineering background are very comfortable analyzing EEG data. Still, scientists in computer science and related fields need a source that can identify all the tools available and the process of analyzing the data. This paper deals specifically with the existing EEG data analysis tools and the processes involved in analyzing the EEG data using these tools. Furthermore, the paper goes in-depth into identifying the tools and the mechanisms of data processing techniques. In addition, it lists a set of definitions required for a better understanding of EEG data analysis, which can be challenging. The purpose of this paper is to serve as a reference for not only scientists that are new to EEG data analysis but also seasoned scientists that are looking for a specific data component in EEG and can go straight to the section of the paper that deals with the tool that they are using.