Challenges and Future Trends of EEG as a Frontier of Clinical Applications

Abstract

The non-invasive techniques for diagnosis are rapidly increasing due to technological advancement in medicine. The analysis of physiological signals reveals information about the state of human health. Among these, electroencephalography (EEG) is commonly used in neuroscience for a wide range of operations that acquire electrical activities of brain. Human behavior during different psycho-physiological states can be studied using EEG. In fact, EEG has been found to be useful in a number of clinical applications. This review mainly presents various clinical prospects of EEG. The genesis of EEG is discussed along with its spectral behavior. In addition, various preprocessing approaches for artifacts removal are briefly discussed. The common features such as time, frequency, and non-linear parameters are also stated that reveal underlying information in EEG which is useful for both supervised and unsupervised classification problems. The processed EEG can be useful for the following clinical applications: seizure detection, psychological assessment, cognitive development, anesthesia monitoring, polysomnography, drowsiness detection, and brain computer interface. Although the non-invasive approach is highly beneficial in medicine, accuracy and reliability of such system is always an issue. To overcome these challenges, sophisticated and highly intelligent instrumentation techniques with convenient experimental setup needs to be developed which can attract consumers with broad spectrum usage of EEG.