The design and hardware implementation of a low-power real-time seizure detection algorithm.

Shriram Raghunathan, Sumeet K. Gupta, Matthew P. Ward, Robert M. Worth, Kaushik Roy, Pedro P. Irazoqui

Research output: Contribution to journalArticle

54 Citations (Scopus)

Abstract

Epilepsy affects more than 1% of the world's population. Responsive neurostimulation is emerging as an alternative therapy for the 30% of the epileptic patient population that does not benefit from pharmacological treatment. Efficient seizure detection algorithms will enable closed-loop epilepsy prostheses by stimulating the epileptogenic focus within an early onset window. Critically, this is expected to reduce neuronal desensitization over time and lead to longer-term device efficacy. This work presents a novel event-based seizure detection algorithm along with a low-power digital circuit implementation. Hippocampal depth-electrode recordings from six kainate-treated rats are used to validate the algorithm and hardware performance in this preliminary study. The design process illustrates crucial trade-offs in translating mathematical models into hardware implementations and validates statistical optimizations made with empirical data analyses on results obtained using a real-time functioning hardware prototype. Using quantitatively predicted thresholds from the depth-electrode recordings, the auto-updating algorithm performs with an average sensitivity and selectivity of 95.3 +/- 0.02% and 88.9 +/- 0.01% (mean +/- SE(alpha = 0.05)), respectively, on untrained data with a detection delay of 8.5 s [5.97, 11.04] from electrographic onset. The hardware implementation is shown feasible using CMOS circuits consuming under 350 nW of power from a 250 mV supply voltage from simulations on the MIT 180 nm SOI process.

Original languageEnglish (US)
Number of pages1
JournalJournal of neural engineering
Volume6
Issue number5
DOIs
StatePublished - Oct 2009

Fingerprint

Seizures
Hardware
Epilepsy
Electrodes
Kainic Acid
Digital circuits
Complementary Therapies
Prosthetics
Population
Prostheses and Implants
Rats
Theoretical Models
Pharmacology
Mathematical models
Equipment and Supplies
Networks (circuits)
Electric potential
Therapeutics

All Science Journal Classification (ASJC) codes

  • Biomedical Engineering
  • Cellular and Molecular Neuroscience

Cite this

Raghunathan, Shriram ; Gupta, Sumeet K. ; Ward, Matthew P. ; Worth, Robert M. ; Roy, Kaushik ; Irazoqui, Pedro P. / The design and hardware implementation of a low-power real-time seizure detection algorithm. In: Journal of neural engineering. 2009 ; Vol. 6, No. 5.
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The design and hardware implementation of a low-power real-time seizure detection algorithm. / Raghunathan, Shriram; Gupta, Sumeet K.; Ward, Matthew P.; Worth, Robert M.; Roy, Kaushik; Irazoqui, Pedro P.

In: Journal of neural engineering, Vol. 6, No. 5, 10.2009.

Research output: Contribution to journalArticle

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