Journal of Healthcare Engineering

Journal of Healthcare Engineering / 2015 / Article

Research Article | Open Access

Volume 6 |Article ID 749129 |

Senay Tewolde, Kalarickal Oommen, Donald Y. C. Lie, Yuanlin Zhang, Ming-Chien Chyu, "Epileptic Seizure Detection and Prediction Based on Continuous Cerebral Blood Flow Monitoring – a Review", Journal of Healthcare Engineering, vol. 6, Article ID 749129, 20 pages, 2015.

Epileptic Seizure Detection and Prediction Based on Continuous Cerebral Blood Flow Monitoring – a Review

Received01 Jan 2015
Accepted01 Apr 2015


Epilepsy is the third most common neurological illness, affecting 1% of the world’s population. Despite advances in medicine, about 25 to 30% of the patients do not respond to or cannot tolerate the severe side effects of medical treatment, and surgery is not an option for the majority of patients with epilepsy. The objective of this article is to review the current state of research on seizure detection based on cerebral blood flow (CBF) data acquired by thermal diffusion flowmetry (TDF), and CBF-based seizure prediction. A discussion is provided on the applications, advantages, and disadvantages of TDF in detecting and localizing seizure foci, as well as its role in seizure prediction. Also presented are an overview of the present challenges and possible future research directions (along with methodological guidelines) of the CBF-based seizure detection and prediction methods.


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