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. 2022 Apr 29:2022:8997108.
doi: 10.1155/2022/8997108. eCollection 2022.

Enhanced Laterality Index: A Novel Measure for Hemispheric Asymmetry

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Enhanced Laterality Index: A Novel Measure for Hemispheric Asymmetry

Yuwen Li et al. J Healthc Eng. .

Abstract

During sleep, the two hemispheres display asymmetries in their activation pattern. Various hemispheric asymmetry measures have been utilized in existing works. Nevertheless, all these measures have one common problem that they would merely take one representative quantity into account when evaluating the functional asymmetry. However, there is a complex series of information exchanges between the two cerebral hemispheres, and only considering one quantity inevitably leads to one-sided or even incorrect conclusions. Consequently, to address the limitation of conventional laterality indices, we propose the so-called enhanced laterality index (ELI), which considers multiple measures of functional asymmetries. Normal sleep and obstructive sleep apnea electroencephalograms (EEGs) from 21 subjects collected in the clinical acquisition system are applied, and two representative quantities are considered simultaneously in this paper. We measure the signal complexity by using fuzzy entropy, and the signal strength is evaluated by calculating EEG energy. The difference of ELI is demonstrated by the comparison with the traditional laterality index (LI) in evaluating the functional asymmetry during sleep.

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Conflict of interest statement

The authors declare no conflicts of interest.

Figures

Figure 1
Figure 1
Illustration of 20 s epoch C3-A2 and C4-A1 EEG signals for normal sleep and OSA.
Figure 2
Figure 2
PSG signals and event annotations, in which the red box indicates the exact OSA event annotation.
Figure 3
Figure 3
(a) Butterworth filter magnitude response, the cutoff frequency is 50 Hz. (b) The frequency spectrum based on the Fourier transform of the original EEG data and the filtered data.
Figure 4
Figure 4
Typical frequency bands decomposed from original EEG data based on the wavelet transform. (a) δ (1–3 Hz), (b) θ (4–7 Hz), (c) α (8–13 Hz), and (d) β (14–30 Hz).
Figure 5
Figure 5
LI distribution along with FEC3 and FEC4. Total epochs were presented in (a) normal sleep and in (b) obstructive sleep apnea.
Figure 6
Figure 6
LI distribution along with EC3 and EC4. Total epochs were presented in (a) normal sleep and in (b) obstructive sleep apnea.
Figure 7
Figure 7
ELI computed with signal complexity and signal strength in consideration. 4 randomly selected subjects are illustrated in subfigures (a)–(d). λ=0.2 in (a1) ∼ (d1), λ=0.4 in (a2) ∼ (d2), λ=0.6 in (a3) ∼ (d3), and λ=0.8 in (a4) ∼ (d4).
Figure 8
Figure 8
Average ELI from 21 subjects for each of δ, θ, α, and β.
Figure 9
Figure 9
ELI|β+δ when signal strength of δ and signal complexity of β are considered simultaneously.

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