Seizure Forecasting Using a Novel Sub-Scalp Ultra-Long Term EEG Monitoring System.

Accurate identification of seizure activity, both clinical and subclinical, has important implications in the management of epilepsy. Accurate recognition of seizure activity is essential for diagnostic, management and forecasting purposes, but patient-reported seizures have been shown to be unreliable. Earlier work has revealed accurate capture of electrographic seizures and forecasting is possible with an implantable intracranial device, but less invasive electroencephalography (EEG) recording systems would be optimal. Here, we present preliminary results of seizure detection and forecasting with a minimally invasive sub-scalp device that continuously records EEG. Five participants with refractory epilepsy who experience at least two clinically identifiable seizures monthly have been implanted with sub-scalp devices (Minder®), providing two channels of data from both hemispheres of the brain. Data is continuously captured via a behind-the-ear system, which also powers the device, and transferred wirelessly to a mobile phone, from where it is accessible remotely via cloud storage. EEG recordings from the sub-scalp device were compared to data recorded from a conventional system during a 1-week ambulatory video-EEG monitoring session. Suspect epileptiform activity (EA) was detected using machine learning algorithms and reviewed by trained neurophysiologists. Seizure forecasting was demonstrated retrospectively by utilizing cycles in EA and previous seizure times. The procedures and devices were well-tolerated and no significant complications have been reported. Seizures were accurately identified on the sub-scalp system, as visually confirmed by periods of concurrent conventional scalp EEG recordings. The data acquired also allowed seizure forecasting to be successfully undertaken. The area under the receiver operating characteristic curve (AUC score) achieved (0.88), which is comparable to the best score in recent, state-of-the-art forecasting work using intracranial EEG.

A new era in electroencephalographic monitoring? Subscalp devices for ultra-long-term recordings.

Inaccurate subjective seizure counting poses treatment and diagnostic challenges and thus suboptimal quality in epilepsy management. The limitations of existing hospital- and home-based monitoring solutions are motivating the development of minimally invasive, subscalp, implantable electroencephalography (EEG) systems with accompanying cloud-based software. This new generation of ultra-long-term brain monitoring systems is setting expectations for a sea change in the field of clinical epilepsy. From definitive diagnoses and reliable seizure logs to treatment optimization and presurgical seizure foci localization, the clinical need for continuous monitoring of brain electrophysiological activity in epilepsy patients is evident. This paper presents the converging solutions developed independently by researchers and organizations working at the forefront of next generation EEG monitoring. The immediate value of these devices is discussed as well as the potential drivers and hurdles to adoption. Additionally, this paper discusses what the expected value of ultra-long-term EEG data might be in the future with respect to alarms for especially focal seizures, seizure forecasting, and treatment personalization.

A wavelet-based noise reduction algorithm and its clinical evaluation in cochlear implants.

Noise reduction is often essential for cochlear implant (CI) recipients to achieve acceptable speech perception in noisy environments. Most noise reduction algorithms applied to audio signals are based on time-frequency representations of the input, such as the Fourier transform. Algorithms based on other representations may also be able to provide comparable or improved speech perception and listening quality improvements. In this paper, a noise reduction algorithm for CI sound processing is proposed based on the wavelet transform. The algorithm uses a dual-tree complex discrete wavelet transform followed by shrinkage of the wavelet coefficients based on a statistical estimation of the variance of the noise. The proposed noise reduction algorithm was evaluated by comparing its performance to those of many existing wavelet-based algorithms. The speech transmission index (STI) of the proposed algorithm is significantly better than other tested algorithms for the speech-weighted noise of different levels of signal to noise ratio. The effectiveness of the proposed system was clinically evaluated with CI recipients. A significant improvement in speech perception of 1.9 dB was found on average in speech weighted noise.

Effect of interphase gap and pulse duration on electrically evoked potentials is correlated with auditory nerve survival.

We investigated the effect of pulse duration (PD) and interphase-gap (IPG) on the electrically-evoked auditory brain stem response (EABR) and viiith nerve compound action potential (ECAP) of deafened guinea pigs in order to test the hypothesis that the extent of change in these neural responses is affected by the histological status of the auditory nerve. Fifteen guinea pigs were deafened by co-administration of kanamycin and furosemide. Animals were acutely implanted with an 8-band electrode array at 1, 4 or 12 weeks following deafening. EABR and ECAP input/output functions were recorded in response to charge balanced biphasic current pulses. We determined the change in current required to equalize; (i) the EABR amplitude when the duration of the current pulse was doubled (104-208 micros/phase); and (ii) the EABR and ECAP amplitudes when the IPG was increased from 8 to 58 micros using a 104 micros/phase current pulse. Following the completion of each experiment the cochleae were examined quantitatively for spiral ganglion neuron survival. As expected, the current level required to evoke an EABR with equal amplitude was lower when the animal was stimulated with current pulses of 208 compared with 104 micros/phase. Moreover, the current level required to evoke EABR/ECAPs with equal amplitude was lower when current pulses had an IPG of 58 versus 8 micros. Importantly, there was a reduction in the magnitude of this effect with greater neural loss; the reduced efficacy of changing both PD and IPG on these electrically-evoked potentials was statistically correlated with neural survival. These results may provide a tool for investigating the contribution of auditory nerve survival to clinical performance among cochlear implant subjects.