Detection of Alzheimer’s Disease Using Optimized EEG Data Acquisition and its Effect on Reaction Time
| Autor: | Nisma Amjad, Mashal Fatima, Muhammad Shafique |
|---|---|
| Rok vydání: | 2018 |
| Předmět: |
medicine.medical_specialty
medicine.diagnostic_test business.industry Headset Healthy subjects Sensory system Disease Audiology Electroencephalography Approximate entropy 030218 nuclear medicine & medical imaging 03 medical and health sciences 0302 clinical medicine Eeg data Medicine Random interval business 030217 neurology & neurosurgery |
| Zdroj: | 2018 IEEE-EMBS Conference on Biomedical Engineering and Sciences (IECBES). |
| DOI: | 10.1109/iecbes.2018.8626696 |
| Popis: | In the elderly population Alzheimer’s disease is a emergent health issue which seeks efficient early detection, that is still a challenge for scientist. This study focuses at establishing a low cost EEG based Alzheimer’s disease detection system. This proposes EEG based wireless headset system, EMOTIV EPOC, for the detection of Alzheimer’s disease and investigating its effect on reaction time. AD effect on EEG was investigated along with the cross check on response time. Approximate Entropy (ApEn) method was used to calculate reduced complexity of EEG signals to detect Alzheimer’s disease. AD patients had significantly lower ApEn values than control subjects at electrodes F8, P7, P8 and T8 (p |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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