Electrical and Electronic Engineering - Research Publications
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ItemA comparative study on approximate entropy measure and poincare plot indexes of minimum foot clearance variability in the elderly during walking(BMC, 2008-02-02)BACKGROUND: Trip-related falls which is a major problem in the elderly population, might be linked to declines in the balance control function due to ageing. Minimum foot clearance (MFC) which provides a more sensitive measure of the motor function of the locomotor system, has been identified as a potential gait parameter associated with trip-related falls in older population. This paper proposes nonlinear indexes (approximate entropy (ApEn) and Poincaré plot indexes) of MFC variability and investigates the relationship of MFC with derived indexes of elderly gait patterns. The main aim is to find MFC variability indexes that well correlate with balance impairments. METHODS: MFC data during treadmill walking for 14 healthy elderly and 10 elderly participants with balance problems and a history of falls (falls risk) were analysed using a PEAK-2D motion analysis system. ApEn and Poincaré plot indexes of all MFC data sets were calculated and compared. RESULTS: Significant relationships of mean MFC with Poincaré plot indexes (SD1, SD2) and ApEn (r = 0.70, p < 0.05; r = 0.86, p < 0.01; r = 0.74, p < 0.05) were found in the falls-risk elderly group. On the other hand, such relationships were absent in the healthy elderly group. In contrast, the ApEn values of MFC data series were significantly (p < 0.05) correlated with Poincaré plot indexes of MFC in the healthy elderly group, whereas correlations were absent in the falls-risk group. The ApEn values in the falls-risk group (mean ApEn = 0.18 +/- 0.03) was significantly (p < 0.05) higher than that in the healthy group (mean ApEn = 0.13 +/- 0.13). The higher ApEn values in the falls-risk group might indicate increased irregularities and randomness in their gait patterns and an indication of loss of gait control mechanism. ApEn values of randomly shuffled MFC data of falls risk subjects did not show any significant relationship with mean MFC. CONCLUSION: Results have implication for quantifying gait dynamics in normal and pathological conditions, thus could be useful for the early diagnosis of at-risk gait. Further research should provide important information on whether falls prevention intervention can improve the gait performance of falls risk elderly by monitoring the change in MFC variability indexes.
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ItemJeeva: Enterprise Grid Enabled Web Portal for Protein Secondary Structure Prediction(IEEE, 2008)This paper presents a Grid portal for protein secondary structure prediction developed by using services of Aneka, a .NET-based enterprise Grid technology. The portal is used by research scientists to discover new prediction structures in a parallel manner. An SVM (Support Vector Machine)-based prediction algorithm is used with 64 sample protein sequences as a case study to demonstrate the potential of enterprise Grids.
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ItemInteraction between sleep EEG and ECG signals during and after obstructive sleep apnea events with or without arousals(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 recordings(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 events(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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ItemInvestigating scale invariant dynamics in minimum toe clearance variability of the young and elderly during treadmill walking(IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC, 2008-08)Current research applying variability measures of gait parameters has demonstrated promise for helping to solve one of the "holy grails" of geriatric research by defining markers that can be used to prospectively identify persons at risk of falling . The minimum toe clearance (MTC) event occurs during the leg swing phase of the gait cycle and is a task highly sensitive to the spatial and balance control properties of the locomotor system. The aim of this study is to build upon the current state of research by investigating the magnitude and dynamic structure from the MTC time series fluctuations due to aging and locomotor disorder. Thirty healthy young (HY), 27 healthy elderly (HE), and 10 falls risk (FR) elderly individuals (who presented a prior history of trip-related falls) participated in treadmill walking for at least 10 min at their preferred speed. Continuous MTC data were collected and the first 512 data points were analyzed. The following variability indices were quantified: 1) MTC mean and standard deviation (SD), 2) PoincarE plot indices of MTC variability (SD1, SD2, SD1/SD2), 3) a wavelet based multiscale exponent beta to describe the dynamic structure of MTC fluctuations, and 4) detrended fluctuation analysis exponent alpha to investigate the presence of long-range correlations in MTC time series data. Results showed that stride-to-stride MTC time series has a nonlinear structure in all three groups when compared against randomly shuffled surrogate MTC data. Test on aging effects showed the MTC central tendency was significantly lower (p < 0.01) and the magnitude of the MTC variability significantly higher (p < 0.01). This trend changed when comparing FR subjects against age-matched HE as both the central tendency (p < 0.01) and magnitude of the variability (p < 0.01) increased significantly in FR. Although the magnitude of MTC variability increased with age, the nonlinear indices represented by alpha, beta, and SD1/SD2 demonstrated that the nonlinear structure of MTC does not change significantly due to aging (p > 0.05). There were, however, significant differences between HY and FR for beta (between scale 1 and 2; p < 0.01) and alpha (p < 0.05). Out of all the variability measures applied, beta(Wv2-4), SD1/SD2, SD2 of critical MTC parameter were found to be potential markers to be able to reliably identify FR from HE subjects. Further research is required to understand the mechanisms underlying the cause of MTC variability.
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ItemAn Adaptive REM for Improving AQM Performance(IEEE - Institute of Electrical and Electronic Engineers, 2008)