EEG spectro-temporal modulation energy: A new feature for automated diagnosis of Alzheimer's disease

Abstract

Abstract-There is recent indication that Alzheimer's disease (AD) can be characterized by atypical modulation of electrophysiological brain activity caused by fibrillar amyloid deposition in specific regions of the brain, such as those related to cognition and memory. In this paper, we propose to objectively characterize EEG sub-band modulation in an attempt to develop an automated noninvasive AD diagnostics tool. First, multi-channel full-band EEG signals are decomposed into five well-known frequency sub-bands: delta, theta, alpha, beta, and gamma. The temporal amplitude envelope of each sub-band is then computed via a Hilbert transformation. The proposed 'spectro-temporal modulation energy' feature measures the rate with which each sub-band is modulated. Modulation energy features are computed for 19 referential EEG signals and seven bipolar signals. Salient features are then selected and used to train four different classifiers, namely, support vector machines, logistic regression, classification and regression trees, and neural networks. Experiments with a database of 34 participants, 22 of which have been clinically diagnosed with probable-AD, show a neural network classifier achieving over 91% accuracy, thus significantly outperforming a classifier trained with conventional spectral-based features.

EEG amplitude modulation analysis for semi-automated diagnosis of Alzheimer’s disease

“…In this article, we propose an alternate nonstationary EEG analysis method for (semi-)automated AD diagnosis, based on extending earlier study reported in [29]. More specifically, we measure the rate at which subband EEG amplitude modulations change over short periods of time (circa 5 s) and compare such "spectro-temporal" signal representations between healthy controls and patients with varying AD severity levels (ranging from mild to severe).…”

“…Biauricular referential electrodes were attached, as recommended by the Brazilian Society of Clinical Neurophysiology and the American EEG Society. Motivated by our recent findings [35,36], from the referential montage we derived a virtual interhemispheric bipolar montage, as there is evidence of an interhemispheric disconnection in AD [27]. The so-called "bipolar signal" was obtained by simply subtracting the two bi-auricular referenced signals involved [37].…”

“…are the impulse responses of elliptic bandpass filters used to separate delta (0.1-4 Hz), theta (4-8 Hz), alpha (8-12 Hz), beta (12)(13)(14)(15)(16)(17)(18)(19)(20)(21)(22)(23)(24)(25)(26)(27)(28)(29)(30), and gamma (30-100 Hz) bands [44]. The temporal amplitude envelope of each of the five subband EEG signals is then computed by means of a Hilbert transform H{·} (the interested reader is referred to [45] and references therein for more details).…”

“…For the purpose of AD diagnosis, two branches of EEG signal analysis have emerged: spectral and nonlinear dynamics [5]. Pioneering spectral analysis studies showed that AD patients presented increased activity in the delta (0.1-4 Hz) and theta (4-8 Hz) frequency bands, as well as decreased activity in the alpha (8)(9)(10)(11)(12) and beta (12)(13)(14)(15)(16)(17)(18)(19)(20)(21)(22)(23)(24)(25)(26)(27)(28)(29)(30) Hz) bands [6][7][8][9][10][11], thus suggesting a slowing of the EEG signal. Moreover, reduced spectral coherence between the two hemispheres was shown between the alpha and beta frequency bands [12][13][14][15][16].…”

Towards automated EEG-Based Alzheimer's disease diagnosis using relevance vector machines

“…These features have been used as indicators of cortical connectivity [31]. As we are interested inter-hemispheric connectivity, coherence features (both magnitude and phase) were computed only for the 8 Lastly, amplitude modulation features have been recently proposed and shown to reliably detect AD, as well as monitor disease progression [5], [32], [33]. To compute the features, the EEG full-band signal is first decomposed into the five conventional sub-bands: delta, theta, alpha, beta, and gamma.…”