Research Article
A Prototype System of Acute Stroke Type Discrimination and Monitoring Based on a Annulus Antenna Array: A Pilot Study
@INPROCEEDINGS{10.1007/978-3-030-49289-2_13, author={Mingsheng Chen and Jia Xu and Jingbo Chen and Haisheng Zhang and Mingxin Qin}, title={A Prototype System of Acute Stroke Type Discrimination and Monitoring Based on a Annulus Antenna Array: A Pilot Study}, proceedings={Wireless Mobile Communication and Healthcare. 8th EAI International Conference, MobiHealth 2019, Dublin, Ireland, November 14-15, 2019, Proceedings}, proceedings_a={MOBIHEALTH}, year={2020}, month={6}, keywords={Stroke type discrimination Cerebral hemorrhage Cerebral ischemia Microwave detection Support Vector Machine}, doi={10.1007/978-3-030-49289-2_13} }- Mingsheng Chen
Jia Xu
Jingbo Chen
Haisheng Zhang
Mingxin Qin
Year: 2020
A Prototype System of Acute Stroke Type Discrimination and Monitoring Based on a Annulus Antenna Array: A Pilot Study
MOBIHEALTH
Springer
DOI: 10.1007/978-3-030-49289-2_13
Abstract
Objective: Timely and effective discrimination of hemorrhagic stroke and ischemic stroke can significantly improve the prognosis. Current discrimination is expensive and has the disadvantage of having to be in contact with the patient. Based on animal experiments, in this paper, microwave measurement technique is used to study the discrimination of two stroke types. Method: In the experiments, 10 rabbits (5 cerebral hemorrhage and 5 cerebral ischemia) are selected. Cerebral hemorrhage is induced by injecting autologous blood (1 to 4 mL) into the brain of rabbits, and the cerebral ischemia is induced by bilateral common carotid artery ligation and femoral artery blood extraction. The two groups are monitored by a 16-channel microwave detection system to obtain the reflection parameter caused by pathological changes in the brain. After redundancy removed from original data, support vector machine (SVM) is used to identify the type and severity of two types of stroke. Findings: The study shows that the microwave-based stroke identification system can effectively distinguish the cerebral hemorrhage model and the cerebral ischemia model. The experimental system is very promising in pre-hospital stroke type identification because of low cost, non-invasive, simple operation and rapid measurement.