ORCID Profile
0000-0002-3760-7784
Current Organisations
Nanyang Technological University
,
Singapore Institute of Technology
,
Singapore Polytechnic
,
DSO National Laboratories
,
Institute for Infocomm Research
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Publisher: Springer Science and Business Media LLC
Date: 24-06-2009
DOI: 10.1007/S10439-009-9744-8
Abstract: Acoustic studies on snoring sounds have recently drawn attention as a potential alternative to polysomnography in the diagnosis of obstructive sleep apnea (OSA). This paper investigates the feasibility of using nonlinear coupling between frequency modes in snore signals via wavelet bicoherence (WBC) analysis for screening of OSA. Two novel markers (PF1 and PSF), which are frequency modes with high nonlinear coupling strength in their respective WBC spectrum, are proposed to differentiate between apneic and benign snores in same- or both-gender snorers. Snoring sounds were recorded from 40 subjects (30 apneic and 10 benign) by a hanging microphone, and subsequently preprocessed within a wavelet transform domain. Forty inspiratory snores (30 as training and 10 as test data) from each subject were examined. Results demonstrate that nonlinear mode interactions in apneic snores are less self-coupled and usually occupy higher and wider frequency ranges than that of benign snores. PF1 and PSF are indicative of apneic and benign snores (p < 0.0001), with optimal thresholds of PF1 = 285 Hz and PSF = 492 Hz (for both genders combined), as well as sensitivity and specificity values between 85.0 and 90.7%, respectively, outperforming the conventional diagnostic indicator (spectral peak frequency, PF = 243-275 Hz, sensitivity = 77.7-79.7%, specificity = 72.0-78.0%, p < 0.0001). Relationships between apnea-hypopnea index and the proposed markers could likely take the functional form of exponential or power. Perspectives on nonlinear dynamics analysis of snore signals are promising for further research and development of a reliable and inexpensive diagnostic tool for OSA.
Publisher: Royal Society of Chemistry (RSC)
Date: 2015
DOI: 10.1039/C5MH00108K
Abstract: A wearable wristband from knittable two-ply yarn supercapacitors with high specific length capacitance.
Publisher: Elsevier BV
Date: 04-2016
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 10-2008
Publisher: Elsevier BV
Date: 03-2018
Publisher: Elsevier BV
Date: 03-2016
Publisher: Royal Society of Chemistry (RSC)
Date: 2010
DOI: 10.1039/C0NR00441C
Abstract: Single-walled carbon nanotubes (SWCNTs) exhibit strong antibacterial activities. Direct contact between bacterial cells and SWCNTs may likely induce cell damages. Therefore, the understanding of SWCNT-bacteria interactions is essential in order to develop novel SWCNT-based materials for their potential environmental, imaging, therapeutic, and military applications. In this preliminary study, we utilized atomic force microscopy (AFM) to monitor dynamic changes in cell morphology and mechanical properties of two typical bacterial models (gram-negative Escherichia coli and gram-positive Bacillus subtilis) upon incubation with SWCNTs. The results demonstrated that in idually dispersed SWCNTs in solution develop nanotube networks on the cell surface, and then destroy the bacterial envelopes with leakage of the intracellular contents. The cell morphology changes observed on air dried s les are accompanied by an increase in cell surface roughness and a decrease in surface spring constant. To mimic the collision between SWCNTs and cells, a sharp AFM tip of 2 nm was chosen to introduce piercings on the cell surface. No clear physical damages were observed if the applied force was below 10 nN. Further analysis also indicates that a single collision between one nanotube and a bacterial cell is unlikely to introduce direct physical damage. Hence, the antibacterial activity of SWCNTs is the accumulation effect of large amount of nanotubes through interactions between SWCNT networks and bacterial cells.
Publisher: Royal Society of Chemistry (RSC)
Date: 2016
DOI: 10.1039/C5EE02703A
Abstract: Customized hybrid carbon fiber supercapacitors with energy across two orders and power across four orders of magnitude.
Publisher: Elsevier BV
Date: 12-2008
DOI: 10.1016/J.SLEEP.2007.07.010
Abstract: To study the feasibility of using acoustic signatures in snore signals for the diagnosis of obstructive sleep apnea (OSA). Snoring sounds of 30 apneic snorers (24 males 6 females apnea-hypopnea index, AHI=46.9+/-25.7events/h) and 10 benign snorers (6 males 4 females AHI=4.6+/-3.4events/h) were captured in a sleep laboratory. The recorded snore signals were preprocessed to remove noise, and subsequently, modeled using a linear predictive coding (LPC) technique. Formant frequencies (F1, F2, and F3) were extracted from the LPC spectrum for analysis. The accuracy of this approach was assessed using receiver operating characteristic curves and notched box plots. The relationship between AHI and F1 was further explored via regression analysis. Quantitative differences in formant frequencies between apneic and benign snores are found in same- or both-gender snorers. Apneic snores exhibit higher formant frequencies than benign snores, especially F1, which can be related to the pathology of OSA. This study yields a sensitivity of 88%, a specificity of 82%, and a threshold value of F1=470Hz that best differentiate apneic snorers from benign snorers (both gender combined). Acoustic signatures in snore signals carry information for OSA diagnosis, and snore-based analysis might potentially be a non-invasive and inexpensive diagnostic approach for mass screening of OSA.
Publisher: Wiley
Date: 15-10-2015
No related grants have been discovered for Andrew Keong Ng.