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المؤلفHussein R.
المؤلفMohamed A.
المؤلفAlghoniemy M.
تاريخ الإتاحة2022-04-21T08:58:31Z
تاريخ النشر2015
اسم المنشور2015 International Conference on Computing, Networking and Communications, ICNC 2015
المصدرScopus
المعرّفhttp://dx.doi.org/10.1109/ICCNC.2015.7069506
معرّف المصادر الموحدhttp://hdl.handle.net/10576/30139
الملخصThe growth of wireless body area sensor networks (WBASNs) has led the way to advancements In healthcare applications and patient monitoring systems; epileptic seizure lies at the heart of these promising technologies. For real-time epileptic seizure detection, wireless EEG sensors have been utilized for the purpose of data acquisition, pre-processing and transmission to the server side. The dilemma of excessive power consumption of both data processing and transmission imposes strict constraints on battery-powered sensor nodes. The conventional streaming approach transmits raw EEG data as is, while consumes excessive transmission power. Other modalities consider lossy compression paradigms in order to reduce the transmitted data. This paper proposes on-board data reduction technique, which extracts low-complexity and high level, application-based, features at the sensor side. In particular, EEG spectrum is segmented to five frequency sub-bands; numerous combinations of these sub-bands are selected as feature vectors, and classification using k-nearest neighbor. Simulations have revealed that alpha and delta rhythms yield feature vectors for the EEG signals in the context of epileptic seizure detection. Satisfactory results have been obtained (around 92.47% accuracy). Moreover, the proposed approach outperforms both data streaming and compression techniques in terms of total power consumption and seizure detection performance. 2015 IEEE.
اللغةen
الناشرInstitute of Electrical and Electronics Engineers Inc.
الموضوعClassification (of information)
Data acquisition
Data reduction
Electric power utilization
Energy efficiency
Nearest neighbor search
Neurodegenerative diseases
Patient monitoring
Sensor networks
Sensor nodes
Compressive sensing
Data processing and transmission
Epileptic seizure detection
Health care application
Patient monitoring systems
Wavelet compression
Wireless body area sensor network
Wireless transmissions
Neurophysiology
العنوانEnergy-efficient on-board processing technique for wireless epileptic seizure detection systems
النوعConference Paper
الصفحات1116-1121
dc.accessType Abstract Only


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