Opportunities for Electroceuticals in Epilepsy. (October 2019)

• Record Type: Journal Article
• Authors: Kavehei, Omid; Hamilton, Tara Julia; Truong, Nhan Duy; Nikpour, Armin
• Is Part Of: Trends in pharmacological sciences. Volume 40:Number 10(2019)
• Page Start: 735
• Page End: 746
• Publication Date: 2019-10
• Subjects: epilepsy -- electroceuticals -- artificial intelligence -- microelectronics; Pharmacology -- Periodicals; Pharmacology -- trends -- Periodicals; Pharmacologie -- Périodiques; Pharmacology; Electronic journals; Periodicals; 615.1
• DOI: 10.1016/j.tips.2019.08.001
• Languages: English
• ISSNs: 0165-6147

Abstract

Abstract : Epilepsy is a neurological disorder that affects ∼1% of the world population. Nearly 30% of epilepsy patients suffer from pharmacoresistant epilepsy that cannot be treated with antiepileptic drugs. Depending on seizure type, a diverse range of therapies are available, including surgery, vagus nerve stimulation, and deep brain stimulation. We review the sensing and stimulation technologies most used in neurological disorders, and provide a vision of minimally invasive electroceuticals to enable accurate forecasting of epileptic seizures and therapy. The use of such systems could potentially help patients to prevent injuries and, in combination with an intervention mechanism, could provide a method of suppressing seizures in epileptic patients. Highlights: Electroceuticals can help to treat diseases that do not respond to conventional medication, such as arrhythmia, epilepsy, depression, impaired hearing, or vision. Artificial intelligence (AI) solutions open doors to a more productive brain signal processing that results in better patient specificity and reduced sensitivity to noise and artifacts. Preliminary results of neural stimulation in epilepsy promises an improved quality of life for patients. In some cases, these treatments can be noninvasive and wearable. A subscalp brain–machine interfacing system is one of the most promising options for long-term, reliable, ambulatory, and minimally invasive brain signal monitoring. AI-based biomedical signal processing holds the potential to provide insights into more effective hardware sensory implementation and to improve the design of brain–machine interfacing electronics.