Preben Kidmose

The In-the-Ear Recording Concept: User-Centered and Wearable Brain Monitoring

The integration of brain monitoring based on electroencephalography (EEG) into everyday life has been hindered by the limited portability and long setup time of current wearable systems as well as by the invasiveness of implanted systems (e.g. intracranial EEG). We explore the potential to record EEG in the ear canal, leading to a discreet, unobtrusive, and user-centered approach to brain monitoring. The in-the-ear EEG (Ear-EEG) recording concept is tested using several standard EEG paradigms, benchmarked against standard onscalp EEG, and its feasibility proven. Such a system promises a number of advantages, including fixed electrode positions, user comfort, robustness to electromagnetic interference, feedback to the user, and ease of use. The Ear-EEG platform could also support additional biosensors, extending its reach beyond EEG to provide a powerful health-monitoring system for those applications that require long recording periods in a natural environment.

Time-Frequency Analysis of EEG Asymmetry Using Bivariate Empirical Mode Decomposition

A novel method is introduced to determine asymmetry, the lateralization of brain activity, using extension of the algorithm empirical mode decomposition (EMD). The localized and adaptive nature of EMD make it highly suitable for estimating amplitude information across frequency for nonlinear and nonstationary data. Analysis illustrates how bivariate extension of EMD (BEMD) facilitates enhanced spectrum estimation for multichannel recordings that contain similar signal components, a realistic assumption in electroencephalography (EEG). It is shown how this property can be used to obtain a more accurate estimate of the marginalized spectrum, critical for the localized calculation of amplitude asymmetry in frequency. Simulations on synthetic data sets and feature estimation for a brain-computer interface (BCI) application are used to validate the proposed asymmetry estimation methodology.

A Study of Evoked Potentials From Ear-EEG

A method for brain monitoring based on measuring the electroencephalogram (EEG) from electrodes placed in-the-ear (ear-EEG) was recently proposed. The objective of this study is to further characterize the ear-EEG and perform a rigorous comparison against conventional on-scalp EEG. This is achieved for both auditory and visual evoked responses, over steady-state and transient paradigms, and across a population of subjects. The respective steady-state responses are evaluated in terms of signal-to-noise ratio and statistical significance, while the qualitative analysis of the transient responses is performed by considering grand averaged event-related potential (ERP) waveforms. The outcomes of this study demonstrate conclusively that the ear-EEG signals, in terms of the signal-to-noise ratio, are on par with conventional EEG recorded from electrodes placed over the temporal region.

In-Ear EEG From Viscoelastic Generic Earpieces: Robust and Unobtrusive 24/7 Monitoring

We introduce a novel in-ear sensor which satisfies key design requirements for wearable electroencephalography (EEG)-it is discreet, unobtrusive, and capable of capturing high-quality brain activity from the ear canal. Unlike our initial designs, which utilize custom earpieces and require a costly and time-consuming manufacturing process, we here introduce the generic earpieces to make ear-EEG suitable for immediate and widespread use. Our approach represents a departure from silicone earmoulds to provide a sensor based on a viscoelastic substrate and conductive cloth electrodes, both of which are shown to possess a number of desirable mechanical and electrical properties. Owing to its viscoelastic nature, such an earpiece exhibits good conformance to the shape of the ear canal, thus providing stable electrode-skin interface, while cloth electrodes require only saline solution to establish low impedance contact. The analysis highlights the distinguishing advantages compared with the current state-of-the-art in ear-EEG. We demonstrate that such a device can be readily used for the measurement of various EEG responses.

Measuring phase synchrony using complex extensions of EMD

A framework for the robust assessment of phase synchrony between multichannel observations is introduced. This is achieved by using Empirical Mode Decomposition (EMD), a data driven technique which decomposes nonlinear and nonstationary data into their oscillatory components (scales). In general, it is rarely possible to jointly process two or more channels due to the non-uniqueness of the decompositions. To guarantee the same decomposition levels for every pair of channels analysed, we consider phase synchrony within the recently introduced framework of complex extensions of EMD. Simulation results on brain signals support the analysis.

EEG Recorded from the Ear: Characterizing the Ear-EEG Method.

Highlights Auditory middle and late latency responses can be recorded reliably from ear-EEG. For sources close to the ear, ear-EEG has the same signal-to-noise-ratio as scalp. Ear-EEG is an excellent match for power spectrum-based analysis. A method for measuring electroencephalograms (EEG) from the outer ear, so-called ear-EEG, has recently been proposed. The method could potentially enable robust recording of EEG in natural environments. The objective of this study was to substantiate the ear-EEG method by using a larger population of subjects and several paradigms. For rigor, we considered simultaneous scalp and ear-EEG recordings with common reference. More precisely, 32 conventional scalp electrodes and 12 ear electrodes allowed a thorough comparison between conventional and ear electrodes, testing several different placements of references. The paradigms probed auditory onset response, mismatch negativity, auditory steady-state response and alpha power attenuation. By comparing event related potential (ERP) waveforms from the mismatch response paradigm, the signal measured from the ear electrodes was found to reflect the same cortical activity as that from nearby scalp electrodes. It was also found that referencing the ear-EEG electrodes to another within-ear electrode affects the time-domain recorded waveform (relative to scalp recordings), but not the timing of individual components. It was furthermore found that auditory steady-state responses and alpha-band modulation were measured reliably with the ear-EEG modality. Finally, our findings showed that the auditory mismatch response was difficult to monitor with the ear-EEG. We conclude that ear-EEG yields similar performance as conventional EEG for spectrogram-based analysis, similar timing of ERP components, and equal signal strength for sources close to the ear. Ear-EEG can reliably measure activity from regions of the cortex which are located close to the ears, especially in paradigms employing frequency-domain analyses.

Auditory evoked responses from Ear-EEG recordings

A method for brain monitoring based on measuring electroencephalographic (EEG) signals from electrodes placed in-the-ear (Ear-EEG) was recently proposed. The Ear-EEG recording methodology provides a non-invasive, discreet and unobtrusive way of measuring electrical brain signals and has great potential as an enabling method for brain monitoring in everyday life. This work aims at further establishing the Ear-EEG recording methodology by considering auditory evoked potentials, and by comparing Ear-EEG responses with conventional on-scalp recordings and with well established results from the literature. It is shown that both steady state and transient responses can be obtained from Ear-EEG, and that these responses have similar characteristics and quality compared to EEG obtained from conventional on-scalp recordings.

Velocity and Directionality of the Electrohysterographic Signal Propagation

Objective The initiation of treatment for women with threatening preterm labor requires effective distinction between true and false labor. The electrohysterogram (EHG) has shown great promise in estimating and classifying uterine activity. However, key issues remain unresolved and no clinically usable method has yet been presented using EHG. Recent studies have focused on the propagation velocity of the EHG signals as a potential discriminator between true and false labor. These studies have estimated the propagation velocity of individual spikes of the EHG signals. We therefore focus on estimating the propagation velocity of the entire EHG burst recorded during a contraction in two dimensions. Study Design EHG measurements were performed on six women in active labor at term, and a total of 35 contractions were used for the estimation of propagation velocity. The measurements were performed using a 16-channel two-dimensional electrode grid. The estimates were calculated with a maximum-likelihood approach. Results The estimated average propagation velocity was 2.18 (±0.68) cm/s. No single preferred direction of propagation was found. Conclusion The propagation velocities estimated in this study are similar to those reported in other studies but with a smaller intra- and inter-patient variation. Thus a potential tool has been established for further studies on true and false labor contractions.

Co-Located Multimodal Sensing: A Next Generation Solution for Wearable Health

A novel physiological sensor which combines electrical and mechanical modalities is introduced. The electrical component behaves as a standard electrode and detects changes in bioelectrical potential, whereas the mechanical component comprises an electret condenser microphone with a thin and light diaphragm, making it sensitive to local mechanical activity but immune to global body movements. A key feature of the proposed sensor is that the microphone is positioned directly on top of the electrode component (co-location). In conjunction with co-located electromechanical sensing, the ability of the electrode to flex allows for motion to be detected at the same location where it corrupts the electrical physiological response. Thus, the output of the mechanical sensor can be used to reject motion-induced artifacts in physiological signals, offering improved recording quality in wearable health applications. We also show that the co-located electrical and mechanical modalities provide derived information beyond unimodal sensing, such as pulse arrival time and breathing, thus enhancing the utility of the proposed device and highlighting its potential as a diagnostic tool.

Ear-EEG: User-Centered and Wearable BCI

We present a radically new solution for EEG-based brain computer interface (BCI) where electrodes are embedded on a customized earpiece, as typically used in hearing aids (Ear-EEG). This provides a noninvasive, minimally intrusive and user-friendly EEG platform suitable for long-term use (days) in natural environments. The operation of Ear-EEG is illustrated for alpha-attenuation and responses to auditory stimuli, and its potential in BCI is evaluated on an SSVEP study. We show that Ear-EEG bitrate performances are comparable with those of on-scalp electrodes, thus promising a quantum step forward for wearable BCI.