Use Cases and Designs for a Brain-Computer Interface using EEG Wireless Sensors
| Autor: | Ana-Maria Ghimes, Valentin-Alexandru Vladuta, Constantin Grumazescu |
|---|---|
| Rok vydání: | 2018 |
| Předmět: |
business.industry
Computer science 020208 electrical & electronic engineering 05 social sciences Real-time computing Medical equipment 050801 communication & media studies 02 engineering and technology 0508 media and communications Software 0202 electrical engineering electronic engineering information engineering Wireless Time management Use case business Wireless sensor network Pace Brain–computer interface |
| Zdroj: | 2018 International Symposium on Fundamentals of Electrical Engineering (ISFEE). |
| DOI: | 10.1109/isfee.2018.8742434 |
| Popis: | Wireless sensors have developed greatly in the recent years and their applicability spreads to various fields. One that benefited greatly from this development is healthcare. Due to the independence from wires and other specific hardware equipment, these small devices were included in medical equipment with the end goal of aiding specialists in obtaining complete information in a shorter period of time. This led to a decrease in diagnosis time and in an improved success rate for different operations. Desired continuous mobility and poor time management are key factors that led to various brain diseases and not only. To keep pace with this trend, many solutions have been developed over time to counteract this trend and improve the quality of life. Electroencephalography (EEG) sensors have the role to study the activity of the brain in various states and provide measurements that can aid patients and specialists in dealing with certain issues. This paper has the objective to present different use cases in which EEG sensors can be used to detect, diagnose or treat different disorders. Moreover, we have conducted a survey of existing hardware and software solutions that can be integrated with medical sensing hardware. All of these components are meant to be intelligently combined, experimented with and tested for complex healthcare related applications. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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