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• W2890956351 abstract "Closed-loop stimulation of many neurological disorders, such as epilepsy, is an emerging technology and regarded as a promising alternative for surgical and drug treatment. In this paper, a real-time seizure detection algorithm based on STFT and support vector machine (SVM) and its field-programmable gate array (FPGA) implementation are proposed. With a two-stage patient-specific channel selection and feature selection mechanism, those redundant and uncorrelated spectral features are removed from the entire feature set. The evaluation results on CHB-MIT epilepsy database show that the mean detection latency of the proposed algorithm is 6 s, the sensitivity is 98.4%, and the false detection rate is 0.356/h. The performance of our proposed algorithm is comparable to other existing seizure detection algorithms. Moreover, we implement the proposed seizure detection algorithm on Xilinx Zynq-7000 XC7Z020 with high level synthesis. Each classification of the input electroencephalography signal can be finished within 313 <inline-formula xmlns:mml=http://www.w3.org/1998/Math/MathML xmlns:xlink=http://www.w3.org/1999/xlink> <tex-math notation=LaTeX>$mu text{s}$ </tex-math></inline-formula> , and the power consumption of the programmable logic is only 380 mW at 100 MHz. In hardware implementation, an optimization strategy for the nested-loop structure within nonlinear SVM is proposed to improve pipeline efficiency. Compared with existing method, the experimental result shows that our method can speed up the nonlinear SVM by <inline-formula xmlns:mml=http://www.w3.org/1998/Math/MathML xmlns:xlink=http://www.w3.org/1999/xlink> <tex-math notation=LaTeX>$1.70times $ </tex-math></inline-formula> , <inline-formula xmlns:mml=http://www.w3.org/1998/Math/MathML xmlns:xlink=http://www.w3.org/1999/xlink> <tex-math notation=LaTeX>$1.53times $ </tex-math></inline-formula> , <inline-formula xmlns:mml=http://www.w3.org/1998/Math/MathML xmlns:xlink=http://www.w3.org/1999/xlink> <tex-math notation=LaTeX>$1.37times $ </tex-math></inline-formula> , and <inline-formula xmlns:mml=http://www.w3.org/1998/Math/MathML xmlns:xlink=http://www.w3.org/1999/xlink> <tex-math notation=LaTeX>$1.26times $ </tex-math></inline-formula> with the unroll factor equal to 1–4 at the same DSP utilization rate. The evaluation results affirm the possibility of integrating the proposed algorithm and FPGA implementation into a wearable seizure control device." @default.
• W2890956351 created "2018-09-27" @default.
• W2890956351 creator A5020902784 @default.
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• W2890956351 date "2018-01-01" @default.
• W2890956351 modified "2023-10-02" @default.
• W2890956351 title "Hardware Design of Real Time Epileptic Seizure Detection Based on STFT and SVM" @default.
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• W2890956351 doi "https://doi.org/10.1109/access.2018.2870883" @default.
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