- Electrical and Electronic Engineering - Research Publications
Electrical and Electronic Engineering - Research Publications
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ItemSensitivity of temporal heart rate variability in Poincare plot to changes in parasympathetic nervous system activityKarmakar, CK ; Khandoker, AH ; Voss, A ; Palaniswami, M (BMC, 2011-03-03)BACKGROUND: A novel descriptor (Complex Correlation Measure (CCM)) for measuring the variability in the temporal structure of Poincaré plot has been developed to characterize or distinguish between Poincaré plots with similar shapes. METHODS: This study was designed to assess the changes in temporal structure of the Poincaré plot using CCM during atropine infusion, 70° head-up tilt and scopolamine administration in healthy human subjects. CCM quantifies the point-to-point variation of the signal rather than gross description of the Poincaré plot. The physiological relevance of CCM was demonstrated by comparing the changes in CCM values with autonomic perturbation during all phases of the experiment. The sensitivities of short term variability (SD1), long term variability (SD2) and variability in temporal structure (CCM) were analyzed by changing the temporal structure by shuffling the sequences of points of the Poincaré plot. Surrogate analysis was used to show CCM as a measure of changes in temporal structure rather than random noise and sensitivity of CCM with changes in parasympathetic activity. RESULTS: CCM was found to be most sensitive to changes in temporal structure of the Poincaré plot as compared to SD1 and SD2. The values of all descriptors decreased with decrease in parasympathetic activity during atropine infusion and 70° head-up tilt phase. In contrast, values of all descriptors increased with increase in parasympathetic activity during scopolamine administration. CONCLUSIONS: The concordant reduction and enhancement in CCM values with parasympathetic activity indicates that the temporal variability of Poincaré plot is modulated by the parasympathetic activity which correlates with changes in CCM values. CCM is more sensitive than SD1 and SD2 to changes of parasympathetic activity.
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ItemPower spectral analysis for identifying the onset and termination of obstructive sleep apnoea events in ECG recordingsKhandoker, AH ; Karmakar, CK ; Palaniswami, M (IEEE, 2008)
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ItemCharacterization Of Chimeric Surface Submentalis EMG Activity During Hypopneas In Obstructive Sleep Apnea PatientsDaulatzai, MA ; Khandoker, AH ; Karmakar, CK ; Palaniswami, M ; Khan, N (IEEE, 2009)
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ItemUnravelling unique qualitative and quantitative characteristics of the surface submentalis EMG in OSA polysomnogramsDaulatzai, M ; Karmakar, C ; Khan, N ; Khandoker, A ; Palaniswami, M (IEEE, 2010-12-01)
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ItemCross Power Spectral Density between Two-Lead ECG Signals at the Termination of Obstructive Sleep Apnea with or without ArousalsKhandoker, AH ; Karmakar, CK ; Palaniswami, M (IEEE, 2008)
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ItemInteraction between sleep EEG and ECG signals during and after obstructive sleep apnea events with or without arousalsKHANDOKER, AHSAN ; KARMAKAR, CHANDAN ; PALANISWAMI, MARIMUTHU (IEEE - Institute of Electrical and Electronic Engineers, 2008)
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ItemIdentification of onset, maximum and termination of obstructive sleep apnoea events in single lead ECG recordingsKarmakar, CK ; Khandoker, AH ; Palaniswami, M (IEEE, 2008)Measuring the Apnoea Hypopnoea Index (AHI) is important for determining the severity of any apnoea patient. This study presents a method of screening each apnoea event separately based on the single lead Electrocardiogram (EGG) signal. The whole ECG of a subject was divided into Normal, Onset, OSA-maximum and Termination epochs with length of 5 seconds. PSD analysis was used for determining the features directly from the ECG. ROC area was calculated to determine the discrimination capability of each feature (or power in each frequency bin) found by PSD analysis. The maximum ROC area found between Normal vs. OSA-maximum was 0.81 in the frequency range of 52-72 Hz. The ROC area and significant frequency band for Normal vs. Onset and Normal vs. Termination were 0.78, 0.78 and 57-65 Hz, 52-66 Hz respectively.
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ItemAnalysis of coherence between sleep EEG and ECG signals during and after obstructive sleep apnea eventsKhandoker, AH ; Karmakar, CK ; Palaniswami, M (IEEE, 2008)This study presents the first successful preliminary attempt to directly investigate the interactions of power spectra of sleep EEG and ECG signals of patients with obstructive sleep apnea syndrome (OSAS) by coherence analysis. ECG and EEG signals were collected from 8 OSAS patients and 3 healthy subjects. Coherence between two signals over different frequency bands(0-128 Hz) were calculated for normal breathing events, obstructive sleep apnea (OSA) events and events following OSA terminations (with/without arousals) in non-REM as well as REM sleep. Overall coherence of ECG and EEG in REM sleep is higher than that in non-REM sleep. A significant (p=0.0164) difference of coherence in the range of 10-5 Hz was found among normal, OSA and termination events in REM sleep. The results could be useful in detecting OSA events or OSA related arousals to characterize sleep fragmentation from ECG and EEG signals.
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ItemAutomatic recognition of obstructive sleep apnoea syndrome using power spectral analysis of electrocardiogram and hidden markov modelsAl-Ani, T ; Karmakar, CK ; Khandoker, AH ; Palaniswami, M (IEEE, 2008-12-01)
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ItemLateral Decubitus Posture during Sleep: Sub-Groups of Obstructive Sleep Apnea Patients - Therapeutic Value of Vertical Position in OSADaulatzai, MA ; Khan, N ; Karmakar, C ; Khandoker, A ; Palaniswami, M ; Marusic, S ; Palaniswami, M ; Gubbi, J ; Law, YW (IEEE, 2009)