Biomedical Signal Processing and Control Automated Detection and Classification of High Frequency Oscillations (hfos) in Human Intracereberal Eeg

Abstract Discrete high-frequency oscillations (HFOs) in the range of 80–500 Hz have previously been recorded from human epileptic brains using intracereberal EEG and seem to be a reliable biomarker of seizure onset zone in patients with intractable epilepsy. Visual marking of HFOs bursts is tedious, highly time-consuming particularly for analyzing long-term multichannel EEG recordings, inevitably subjective and can be error prone. Thus, the development of automatic, fast and robust detectors is necessary and crucial for HFOs investigation and for propelling their eventual clinical applications. This paper presents a proposed algorithm for detection and classification of HFOs, which is a combination of both smoothed Hilbert Huang Transform (HHT) and root mean square (RMS) feature. Performance evaluation in terms of sensitivity and false discovery rate (FDR) were respectively 90.72% and 8.23% related to process validation. Indeed, the proposed method was efficient in terms of high sensitivity in which the majority of HFOs visually identified by experienced reviewers was correctly detected, and had a lower FDR. This would mean that only a low rate of detected events was misclassified as candidate HFOs events. The presented software is extremely fast, suitable and can be considered a valuable clinical tool for HFOs investigation.

[1]  Andrea Pigorini,et al.  Time–frequency spectral analysis of TMS-evoked EEG oscillations by means of Hilbert–Huang transform , 2011, Journal of Neuroscience Methods.

[2]  Jean Gotman,et al.  Interictal high-frequency oscillations (100-500 Hz) in the intracerebral EEG of epileptic patients. , 2007, Brain : a journal of neurology.

[3]  J. M. Lina,et al.  Recording and analysis techniques for high-frequency oscillations , 2012, Progress in Neurobiology.

[4]  Norra MacReady,et al.  Radiotherapy and Localization of Seizures Cited as Promising Therapies for Epilepsy , 2008 .

[5]  J. Gotman,et al.  High frequency oscillations (80–500 Hz) in the preictal period in patients with focal seizures , 2009, Epilepsia.

[6]  J. Gotman,et al.  A comparison between detectors of high frequency oscillations , 2012, Clinical Neurophysiology.

[7]  Charles L. Wilson,et al.  Hippocampal and Entorhinal Cortex High‐Frequency Oscillations (100–500 Hz) in Human Epileptic Brain and in Kainic Acid‐Treated Rats with Chronic Seizures , 1999, Epilepsia.

[8]  Charles L. Wilson,et al.  Quantitative analysis of high-frequency oscillations (80-500 Hz) recorded in human epileptic hippocampus and entorhinal cortex. , 2002, Journal of neurophysiology.

[9]  Michel Le Van Quyen,et al.  Epileptogenic Actions of GABA and Fast Oscillations in the Developing Hippocampus , 2005, Neuron.

[10]  C. Bénar,et al.  Pitfalls of high-pass filtering for detecting epileptic oscillations: A technical note on “false” ripples , 2010, Clinical Neurophysiology.

[11]  R. P. Gregory,et al.  Electroencephalogram epileptiform abnormalities in candidates for aircrew training. , 1993, Electroencephalography and clinical neurophysiology.

[12]  Sandipan Pati,et al.  Pharmacoresistant epilepsy: From pathogenesis to current and emerging therapies , 2010, Cleveland Clinic Journal of Medicine.

[13]  Sheng-Fu Liang,et al.  A hierarchical approach for online temporal lobe seizure detection in long-term intracranial EEG recordings , 2013, Journal of neural engineering.

[14]  Eivind Kvedalen Signal processing using the Teager Energy Operator and other nonlinear operators , 2003 .

[15]  Itzhak Fried,et al.  Interictal high‐frequency oscillations (80–500Hz) in the human epileptic brain: Entorhinal cortex , 2002, Annals of neurology.

[16]  C. Doshi,et al.  Methods for detecting high-frequency oscillations in ongoing brain signals: Application to the determination of epileptic seizure onset zones , 2011 .

[17]  Bernardino Castillo-Toledo,et al.  An algorithm for on-line detection of high frequency oscillations related to epilepsy , 2013, Comput. Methods Programs Biomed..

[18]  Jean Gotman,et al.  Ictal and interictal high frequency oscillations in patients with focal epilepsy , 2011, Clinical Neurophysiology.

[19]  J. Martinerie,et al.  Mapping interictal oscillations greater than 200 Hz recorded with intracranial macroelectrodes in human epilepsy. , 2010, Brain : a journal of neurology.

[20]  Jeffery A. Hall,et al.  Interictal high‐frequency oscillations (80–500 Hz) are an indicator of seizure onset areas independent of spikes in the human epileptic brain , 2008, Epilepsia.

[21]  G. Mathern,et al.  Removing interictal fast ripples on electrocorticography linked with seizure freedom in children , 2010, Neurology.

[22]  Steve M. Potter,et al.  Spontaneous and evoked high‐frequency oscillations in the tetanus toxin model of epilepsy , 2010, Epilepsia.

[23]  K Vijayalakshmi,et al.  Spike Detection in Epileptic Patients EEG Data using Template Matching Technique , 2010 .

[24]  J. Artieda,et al.  High frequency oscillations in the somatosensory evoked potentials (SSEP's) are mainly due to phase-resetting phenomena , 2006, Journal of Neuroscience Methods.

[25]  J. Gotman,et al.  High-frequency oscillations during human focal seizures. , 2006, Brain : a journal of neurology.

[26]  K. P. Indiradevi,et al.  A multi-level wavelet approach for automatic detection of epileptic spikes in the electroencephalogram , 2008, Comput. Biol. Medicine.

[27]  B. Litt,et al.  High-frequency oscillations in human temporal lobe: simultaneous microwire and clinical macroelectrode recordings. , 2008, Brain : a journal of neurology.

[28]  N. Huang,et al.  The empirical mode decomposition and the Hilbert spectrum for nonlinear and non-stationary time series analysis , 1998, Proceedings of the Royal Society of London. Series A: Mathematical, Physical and Engineering Sciences.

[29]  Abdennaceur Kachouri,et al.  A Comparaison of Methods for Detection of High Frequency Oscillations (HFOs) in Human Intacerberal EEG Recordings , 2013 .

[30]  Chin-Feng Lin,et al.  HHT-based time-frequency analysis method for biomedical signal applications , 2011 .

[31]  Damien Garcia,et al.  Robust smoothing of gridded data in one and higher dimensions with missing values , 2010, Comput. Stat. Data Anal..

[32]  J. Gotman,et al.  High‐frequency electroencephalographic oscillations correlate with outcome of epilepsy surgery , 2010, Annals of neurology.

[33]  Roshanak Yazdanpour-Naeini,et al.  Automatic Detection of High Frequency Oscillations of Neural Signals in Epileptic Patients , 2012 .

[34]  Abdennaceur Kachouri,et al.  A comparison of methods for separation of transient and oscillatory signals in EEG , 2011, Journal of Neuroscience Methods.

[35]  Brian Litt,et al.  Human and automated detection of high-frequency oscillations in clinical intracranial EEG recordings , 2007, Clinical Neurophysiology.