Performance Estimation of an Implantable Epileptic Seizure Detector with a Low-power On-chip Oscillator
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Implantable closed-loop epilepsy controllers require ideally both accurate epileptic seizure detection and low power consumption. On-chip oscillators can be used in implantable devices because they consume less power than other oscillators such as crystal oscillators. In this study, we investigated the tolerable error range of a lower power on-chip oscillator without losing the accuracy of seizure detection. We used 24 ictal and 14 interictal intracranial electroencephalographic segments recorded from epilepsy surgery patients. The performance variations with respect to oscillator frequency errors were estimated in terms of specificity, modified sensitivity, and detection timing difference of seizure onset using Generic Osorio Frei Algorithm. The frequency errors of on-chip oscillators were set at ± 10% as the worst case. Our results showed that an oscillator error of ± 10% affected both specificity and modified sensitivity by less than 3%. In addition, seizure onsets were detected with errors earlier or later than without errors and the average detection timing difference varied within less than 0.5 s range. The results suggest that on-chip oscillators could be useful for low-power implantable devices without error compensation circuitry requiring significant additional power. These findings could help the design of closed-loop systems with a seizure detector and automated stimulators for intractable epilepsy patients
Abstract
Implantable closed-loop epilepsy controllers require ideally both accurate epileptic seizure detection and low power consumption. On-chip oscillators can be used in implantable devices because they consume less power than other oscillators such as crystal oscillators. In this study, we investigated the tolerable error range of a lower power on-chip oscillator without losing the accuracy of seizure detection. We used 24 ictal and 14 interictal intracranial electroencephalographic segments recorded from epilepsy surgery patients. The performance variations with respect to oscillator frequency errors were estimated in terms of specificity, modified sensitivity, and detection timing difference of seizure onset using Generic Osorio Frei Algorithm. The frequency errors of on-chip oscillators were set at ± 10% as the worst case. Our results showed that an oscillator error of ± 10% affected both specificity and modified sensitivity by less than 3%. In addition, seizure onsets were detected with errors earlier or later than without errors and the average detection timing difference varied within less than 0.5 s range. The results suggest that on-chip oscillators could be useful for low-power implantable devices without error compensation circuitry requiring significant additional power. These findings could help the design of closed-loop systems with a seizure detector and automated stimulators for intractable epilepsy patients
참고문헌 (22)
- C. P. Young, "A Portable Wireless Online Closed-Loop Seizure Controller in Freely Moving Rats", IEEE Trans. Instrum. Meas., 60, pp.513~521 (2011)
- "Brain Facts: A Primer on the Brain and Nervous System" (2012)[URL]
- N.C. Bhavaraju, "Analog seizure detection and performance evaluation", IEEE Trans. Biomed. Eng., 53, pp.238~245 (2006)
- E. Beghi, "Epilepsy, a comprehensive textbook", pp.65~70 (2008), Williams &Wilkins
- H.W. Lee, "Epilepsy Topics", pp.161~172 (2014), InTech
- S. Raghunathan, "A hardware-algorithm co-design approach to optimize seizure detection algorithms for implantable applications", J Neurosci Methods, 193, pp.106~117 (2010)
- C. C. Jouny, "Characterization of early partial seizure onset: Frequency, complexity and entropy", Clin Neurophysiol, 123, pp.658~669 (2012)
- I. Osorio, "Real-time automated detection and quantitative analysis of seizures and short-term prediction of clinical onset", Epilepsia, 39, pp.615~627 (1998)
- A.H. Shoeb, "Application of machine learning to epileptic seizure detection", Proc. 27th International Conference on Machine Learning, pp.975~982 (2010)
- F. Mormann, "Seizure prediction: the long and winding road", Brain, 130, pp.314~333 (2007)
- S. Narasimhan, "Ultra-low-power and robust digital-signal-processing hardware for implantable neural interface microsystems", IEEE Trans. Biomed. Circuits Syst., 5, pp.169~178 (2011)
- J. Kwong, "A 65 nm sub-microcontroller with integrated SRAM and switched capacitor DC-DC converter", IEEE J. Solid-State Circuits, 44, pp.115~126 (2009)
- 김승욱, "Adaptive Online Voltage Scaling Scheme Based on the Nash Bargaining Solution", ETRI Journal, 33(3), pp.407~414 (2011), 한국전자통신연구원
- J. Bae, "A lowenergy crystal-Less double-FSK sensor node transceiver for wireless body-area network", IEEE J. Solid-State Circuits, 47, pp.2678~2692 (2012)
- J.D. Soldera, "A temperature compensated CMOS relaxation oscillator for low power applications", Proc. 25th Symposium on Integrated Circuits and Systems Design, pp.1~4 (2012)
- K. Choe, "A precision relaxation oscillator with a self-clocked offset-cancellation scheme for implantable biomedical SoCs", IEEE International Solid-State Circuits Conference-Digest of Technical Papers, pp.402~403 (2009)
- F. Sebastiano, "A low-voltage mobility-based frequency reference for crystal-less ULP radios", IEEE J. Solid-State Circuits, 44, pp.2002~2009 (2009)
- L. Xiaoyin, "Epileptic seizure detection with the local field potential of anterior thalamic of rats aiming at real time application", Engineering in Medicine and Biology Society, EMBC, 2011 Annual International Conference of the IEEE, pp.6781~6784 (2011)
- S. Ravindran, "Low complexity algorithms for heart rate and epileptic seizure detection", ISABEL 2009 2nd International Symposium on Applied Sciences in Biomedical and Communication Technologies, pp.1~5 (2009)
- H. W. Lee, "Seizure localization using three-dimensional surface projections of intracranial EEG power", NeuroImage, 83, pp.616~626 (2013)
- H. W. Lee, "Altered functional connectivity in seizure onset zones revealed by fMRI intrinsic connectivity", Neurology, 83, pp.2269~2277 (2014)
- M. T. Salam, "A novel lowpower-implantable epileptic seizure-onset detector", IEEE Trans. Biomed. Circuits Syst, 5, pp.568~578 (2011)