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Fulltext The assessment of finger photoplethysmography fitness index (PPGF) among young men with cardiovascular disease risk factors: a cross sectional study

Aminuddin, A., Zaiton, Z., Azizah, U., Norizam, S., Nor Anita, M.M.N., Chellappan, K.

Medicine & Health, 2016;11(2):218-231.
MyJurnal

Two new vascular health markers which are derived from finger
photoplethysmography (PPG) waveform have been introduced based on Malaysian
population, namely PPG fitness index (PPGF) and vascular risk prediction index
(VRPI). The objectives of this study were to investigate the associations between
PPGF and other cardiovascular disease (CVD) markers such as carotid femoral pulse
wave velocity (PWVCF), to compare PPGF between those with and without CVD risk
factors and to determine the sensitivity of VRPI in identifying young subjects with
CVD risk factors. A total of 114 men age 20 to 40 yrs with and without CVD risk
factors were recruited. Risk factors included hypertension, smoking, dyslipidemia,
abdominal obesity and family history of premature CVD. Subjects were divided
into healthy, those with one risk factor and those with at least two risk factors. Their
weight, height, peripheral and central blood pressure (BP), PWVCF and PPGF were
measured and the sensitivity of VRPI in predicting subjects with CVD risk factor was
calculated. Data was analyzed via SPSS version 15 and p < 0.05 was considered
significant. The mean age of the subjects was 28.94 ± 4.86 yrs. No differences in
PPGF was observed between groups (p > 0.05). The independent variables for
PPGF were forward pressure (Beta = 0.35, p < 0.01), PWVCF (Beta = -0.26, p < 0.01),
systolic BP (Beta = -0.26, p = 0.04) and height (Beta = 0.24, p < 0.01). The sensitivity
of VRPI was 82.02%. In conclusion, PPGF was correlated to PWVCF and may be a
potential marker of arterial stiffness. In addition, VRPI is sensitive to be used as an
early screening of CVD risk factors.
Fulltext Image Processing for mHealth-Based Approach to Detect the Local Tissue Inflammation in Cutaneous Leishmaniasis: A Proof of Concept Study

Silva H, Chellappan K, Karunaweera N

Comput Math Methods Med, 2021;2021:4208254.
PMID: 34873414 DOI: 10.1155/2021/4208254

Skin lesions are a feature of many diseases including cutaneous leishmaniasis (CL). Ulcerative lesions are a common manifestation of CL. Response to treatment in such lesions is judged through the assessment of the healing process by regular clinical observations, which remains a challenge for the clinician, health system, and the patient in leishmaniasis endemic countries. In this study, image processing was initially done using 40 CL lesion color images that were captured using a mobile phone camera, to establish a technique to extract features from the image which could be related to the clinical status of the lesion. The identified techniques were further developed, and ten ulcer images were analyzed to detect the extent of inflammatory response and/or signs of healing using pattern recognition of inflammatory tissue captured in the image. The images were preprocessed at the outset, and the quality was improved using the CIE L∗a∗b color space technique. Furthermore, features were extracted using the principal component analysis and profiled using the signal spectrogram technique. This study has established an adaptive thresholding technique ranging between 35 and 200 to profile the skin lesion images using signal spectrogram plotted using Signal Analyzer in MATLAB. The outcome indicates its potential utility in visualizing and assessing inflammatory tissue response in a CL ulcer. This approach is expected to be developed further to a mHealth-based prediction algorithm to enable remote monitoring of treatment response of cutaneous leishmaniasis.
Fulltext Variable-Length Multiobjective Social Class Optimization for Trust-Aware Data Gathering in Wireless Sensor Networks

Saad MA, Jaafar R, Chellappan K

Sensors (Basel), 2023 Jun 12;23(12).
PMID: 37420692 DOI: 10.3390/s23125526

Data gathering in wireless sensor networks (WSNs) is vital for deploying and enabling WSNs with the Internet of Things (IoTs). In various applications, the network is deployed in a large-scale area, which affects the efficiency of the data collection, and the network is subject to multiple attacks that impact the reliability of the collected data. Hence, data collection should consider trust in sources and routing nodes. This makes trust an additional optimization objective of the data gathering in addition to energy consumption, traveling time, and cost. Joint optimization of the goals requires conducting multiobjective optimization. This article proposes a modified social class multiobjective particle swarm optimization (SC-MOPSO) method. The modified SC-MOPSO method is featured by application-dependent operators named interclass operators. In addition, it includes solution generation, adding and deleting rendezvous points, and moving to the upper and lower class. Considering that SC-MOPSO provides a set of nondominated solutions as a Pareto front, we employed one of the multicriteria decision-making (MCDM) methods, i.e., simple additive sum (SAW), for selecting one of the solutions from the Pareto front. The results show that both SC-MOPSO and SAW are superior in terms of domination. The set coverage of SC-MOPSO is 0.06 dominant over NSGA-II compared with only a mastery of 0.04 of NSGA-II over SC-MOPSO. At the same time, it showed competitive performance with NSGA-III.
Fulltext Role of EEG as biomarker in the early detection and classification of dementia

Al-Qazzaz NK, Ali SH, Ahmad SA, Chellappan K, Islam MS, Escudero J

ScientificWorldJournal, 2014;2014:906038.
PMID: 25093211 DOI: 10.1155/2014/906038

The early detection and classification of dementia are important clinical support tasks for medical practitioners in customizing patient treatment programs to better manage the development and progression of these diseases. Efforts are being made to diagnose these neurodegenerative disorders in the early stages. Indeed, early diagnosis helps patients to obtain the maximum treatment benefit before significant mental decline occurs. The use of electroencephalogram as a tool for the detection of changes in brain activities and clinical diagnosis is becoming increasingly popular for its capabilities in quantifying changes in brain degeneration in dementia. This paper reviews the role of electroencephalogram as a biomarker based on signal processing to detect dementia in early stages and classify its severity. The review starts with a discussion of dementia types and cognitive spectrum followed by the presentation of the effective preprocessing denoising to eliminate possible artifacts. It continues with a description of feature extraction by using linear and nonlinear techniques, and it ends with a brief explanation of vast variety of separation techniques to classify EEG signals. This paper also provides an idea from the most popular studies that may help in diagnosing dementia in early stages and classifying through electroencephalogram signal processing and analysis.
Fulltext Surface electromyography signal processing and classification techniques

Chowdhury RH, Reaz MB, Ali MA, Bakar AA, Chellappan K, Chang TG

Sensors (Basel), 2013;13(9):12431-66.
PMID: 24048337 DOI: 10.3390/s130912431

Electromyography (EMG) signals are becoming increasingly important in many applications, including clinical/biomedical, prosthesis or rehabilitation devices, human machine interactions, and more. However, noisy EMG signals are the major hurdles to be overcome in order to achieve improved performance in the above applications. Detection, processing and classification analysis in electromyography (EMG) is very desirable because it allows a more standardized and precise evaluation of the neurophysiological, rehabitational and assistive technological findings. This paper reviews two prominent areas; first: the pre-processing method for eliminating possible artifacts via appropriate preparation at the time of recording EMG signals, and second: a brief explanation of the different methods for processing and classifying EMG signals. This study then compares the numerous methods of analyzing EMG signals, in terms of their performance. The crux of this paper is to review the most recent developments and research studies related to the issues mentioned above.
Amelioration of inflammation in young men with cardiovascular risks participating pedometer-based walking programme

Omar NO, Ahmad RA, Mohd Shah MS, Aminuddin AA, Chellappan KC

Med J Malaysia, 2021 05;76(3):375-381.
PMID: 34031337

INTRODUCTION: Inflammation plays a central role in the pathogenesis of cardiovascular events. The lack of exercise among Malaysians and the increasing cardiovascular diseases among young men are of concern. The aim of this study was to evaluate the reducing of inflammation by measuring C-Reactive protein (CRP), interleukin-6 (IL-6) and tumour necrosis factor-alpha (TNF-α).
MATERIALS AND METHODS: A total of 70 young men (20 - 40 years) who were sedentary, achieving less than 5,000 steps/day in casual walking with 2 or more cardiovascular risk factors were recruited in Institute of Vocational Skills for Youth (IKBN Hulu Langat). Subjects were randomly assigned to a control group (CG) (n=34; no change in walking) and pedometer group (PG) (n=36; minimum target: 8,000 steps/day). All parameter was measured at baseline, at 6 weeks and after 12 weeks.
RESULTS: At post intervention, the CG step counts were similar (4983 ± 366vs 5697 ± 407steps/day). The PG significant increased step count from 4996 ± 805 to 10,128 ±511 steps/day (p<0.001). The PG showed significant improvement in anthropometric variables and lipid (time and group effect p<0.001). After intervention, CRP, IL-6 and TNF- α were significantly reduced for time and group effect (p<0.001). However, no changes were seen in CG.
CONCLUSION: The pedometer-based walking programme improved health status in terms of improving inflammation and arterial stiffness.
Fulltext CT brain image advancement for ICH diagnosis

Shaik Amir NS, Kang LZ, Mukari SA, Sahathevan R, Chellappan K

Healthc Technol Lett, 2020 Feb;7(1):1-6.
PMID: 32190334 DOI: 10.1049/htl.2018.5003

A critical step in detection of primary intracerebral haemorrhage (ICH) is an accurate assessment of computed tomography (CT) brain images. The correct diagnosis relies on imaging modality and quality of acquired images. The authors present an enhancement algorithm which can improve the clarity of edges on CT images. About 40 samples of CT brain images with final diagnosis of primary ICH were obtained from the UKM Medical Centre in Digital Imaging and Communication in Medicine format. The images resized from 512 × 512 to 256 × 256 pixel resolution to reduce processing time. This Letter comprises of two main sections; the first is denoising using Wiener filter, non-local means and wavelet; the second section focuses on image enhancement using a modified unsharp masking (UM) algorithm to improve the visualisation of ICH. The combined approach of Wiener filter and modified UM algorithm outperforms other combinations with average values of mean square error, peak signal-to-noise ratio, variance and structural similarity index of 2.89, 31.72, 0.12 and 0.98, respectively. The reliability of proposed algorithm was evaluated by three blinded assessors which achieved a median score of 65%. This approach provides reliable validation for the proposed algorithm which has potential in improving image analysis.
Fulltext Treatment failure to sodium stibogluconate in cutaneous leishmaniasis: A challenge to infection control and disease elimination

Silva H, Liyanage A, Deerasinghe T, Chandrasekara V, Chellappan K, Karunaweera ND

PLoS One, 2021;16(10):e0259009.
PMID: 34679130 DOI: 10.1371/journal.pone.0259009

The first-line treatment for Leishmania donovani-induced cutaneous leishmaniasis (CL) in Sri Lanka is intra-lesional sodium stibogluconate (IL-SSG). Antimony failures in leishmaniasis is a challenge both at regional and global level, threatening the ongoing disease control efforts. There is a dearth of information on treatment failures to routine therapy in Sri Lanka, which hinders policy changes in therapeutics. Laboratory-confirmed CL patients (n = 201) who attended the District General Hospital Hambantota and Base Hospital Tangalle in southern Sri Lanka between 2016 and 2018 were included in a descriptive cohort study and followed up for three months to assess the treatment response of their lesions to IL-SSG. Treatment failure (TF) of total study population was 75.1% and the majority of them were >20 years (127/151,84%). Highest TF was seen in lesions on the trunk (16/18, 89%) while those on head and neck showed the least (31/44, 70%). Nodules were least responsive to therapy (27/31, 87.1%) unlike papules (28/44, 63.6%). Susceptibility to antimony therapy seemed age-dependant with treatment failure associated with factors such as time elapsed since onset to seeking treatment, number and site of the lesions. This is the first detailed study on characteristics of CL treatment failures in Sri Lanka. The findings highlight the need for in depth investigations on pathogenesis of TF and importance of reviewing existing treatment protocols to introduce more effective strategies. Such interventions would enable containment of the rapid spread of L.donovani infections in Sri Lanka that threatens the ongoing regional elimination drive.
The effects of pedometer-based exercise on central and peripheral vascular functions among young sedentary men with CVD risk factors

Omar N, Yeoh BS, Chellappan K, Chui SZ, Salamt N, Aminuddin A

Front Physiol, 2023;14:1062751.
PMID: 37057183 DOI: 10.3389/fphys.2023.1062751

Introduction: Cardiovascular diseases (CVDs) remain the main cause of morbidity and mortality in Malaysia and worldwide. This is mainly due to an increase in the prevalence of CVD risk factors such as hypertension, dyslipidemia, smoking, and obesity. Increased physical activity has been recommended as a modality to improve CVD risk. Pulse wave velocity (PWVCF), augmentation index (AI), and finger photoplethysmography fitness (PPGF) index have been introduced to assess the vascular functions related to CVD risk factors. The effects of long-term exercise on PPGF index are not established. Materials and Methods: A total of 70 young men who were sedentary with two or more cardiovascular risk factors were recruited. Subjects were randomly assigned to a control group (CG) (n = 34; no change in walking) and pedometer group (PG) (n = 36; minimum target: 8,000 steps/day). PWVCF and AI were measured via the Vicorder system. The PPGF index was obtained via the finger photoplethysmography method. All parameters were measured at baseline and after 6 and 12 weeks. Results: After intervention, the PG had significant increased step count from 4,996 ± 805 to 10,128 ± 511 steps/day (p < 0.001). The PG showed significant improvement in anthropometric variables, lipid, PWVCF, AI, and PPGF index (time and group effect p < 0.001). No changes were observed in CG. Conclusion: This signifies that pedometer-based walking program is beneficial in improving markers of vascular functions among young working sedentary men with CVD risk factors. Pedometer-based exercise should be encouraged to improve cardiovascular health.
Fulltext Assessment of a 16-Channel Ambulatory Dry Electrode EEG for Remote Monitoring

Shivaraja TR, Remli R, Kamal N, Wan Zaidi WA, Chellappan K

Sensors (Basel), 2023 Mar 31;23(7).
PMID: 37050713 DOI: 10.3390/s23073654

Ambulatory EEGs began emerging in the healthcare industry over the years, setting a new norm for long-term monitoring services. The present devices in the market are neither meant for remote monitoring due to their technical complexity nor for meeting clinical setting needs in epilepsy patient monitoring. In this paper, we propose an ambulatory EEG device, OptiEEG, that has low setup complexity, for the remote EEG monitoring of epilepsy patients. OptiEEG's signal quality was compared with a gold standard clinical device, Natus. The experiment between OptiEEG and Natus included three different tests: eye open/close (EOC); hyperventilation (HV); and photic stimulation (PS). Statistical and wavelet analysis of retrieved data were presented when evaluating the performance of OptiEEG. The SNR and PSNR of OptiEEG were slightly lower than Natus, but within an acceptable bound. The standard deviations of MSE for both devices were almost in a similar range for the three tests. The frequency band energy analysis is consistent between the two devices. A rhythmic slowdown of theta and delta was observed in HV, whereas photic driving was observed during PS in both devices. The results validated the performance of OptiEEG as an acceptable EEG device for remote monitoring away from clinical environments.
Augmentation index is a better marker for cardiovascular risk in young Malaysian males. A comparison of involvement of pulse wave velocity, augmentation index, and C-reactive protein

Aminuddin A, Chellappan K, Maskon O, Zakaria Z, Karim AA, Ngah WZ, et al.

Saudi Med J, 2014 Feb;35(2):138-46.
PMID: 24562512

To determine the association between carotid femoral pulse wave velocity (PWVCF) and augmentation index (AI) with future cardiovascular disease (CVD) risk, and to assess whether high sensitivity C-reactive protein (hs-CRP) is an important mediator towards these vascular changes, among young men.
Experimental feasibility study of estimation of the normalized central blood pressure waveform from radial photoplethysmogram

Zahedi E, Sohani V, Ali MA, Chellappan K, Beng GK

J Healthc Eng, 2015;6(1):121-44.
PMID: 25708380 DOI: 10.1260/2040-2295.6.1.121

The feasibility of a novel system to reliably estimate the normalized central blood pressure (CBPN) from the radial photoplethysmogram (PPG) is investigated. Right-wrist radial blood pressure and left-wrist PPG were simultaneously recorded in five different days. An industry-standard applanation tonometer was employed for recording radial blood pressure. The CBP waveform was amplitude-normalized to determine CBPN. A total of fifteen second-order autoregressive models with exogenous input were investigated using system identification techniques. Among these 15 models, the model producing the lowest coefficient of variation (CV) of the fitness during the five days was selected as the reference model. Results show that the proposed model is able to faithfully reproduce CBPN (mean fitness = 85.2% ± 2.5%) from the radial PPG for all 15 segments during the five recording days. The low CV value of 3.35% suggests a stable model valid for different recording days.
Fulltext Effect of increasing heart rate on finger photoplethysmography fitness index (PPGF) in subjects with implanted cardiac pacemakers

Aminuddin A, Tan I, Butlin M, Avolio AP, Kiat H, Barin E, et al.

PLoS One, 2018;13(11):e0207301.
PMID: 30485318 DOI: 10.1371/journal.pone.0207301

Finger photoplethysmography (PPG) is a noninvasive method that measures blood volume changes in the finger. The PPG fitness index (PPGF) has been proposed as an index of vascular risk and vascular aging. The objectives of the study were to determine the effects of heart rate (HR) on the PPGF and to determine whether PPGF is influenced by blood pressure (BP) changes. Twenty subjects (78±8 years, 3 female) with permanent cardiac pacemakers or cardioverter defibrillators were prospectively recruited. HR was changed by pacing, in a random order from 60 to 100 bpm and in 10 bpm increments. At each paced HR, the PPGF was derived from a finger photoplethysmogram. Cardiac output (CO), stroke volume (SV) and total peripheral resistance (TPR) were derived from the finger arterial pressure waveform. Brachial blood pressure (BP) was measured by the oscillometric method. This study found that as HR was increased from 60 to 100 bpm, brachial diastolic BP, brachial mean BP and CO were significantly increased (p<0.01), whilst the PPGF and SV were significantly decreased (p<0.001). The effects of HR on the PPGF were influenced by BP, with a decreasing HR effect on the PPGF that resulted from a higher BP. In conclusion, HR was a significant confounder for PPGF and it must be taken into account in analyses of PPGF, when there are large changes or differences in the HR. The magnitude of this effect was BP dependent.
Fulltext Is Heart Rate a Confounding Factor for Photoplethysmography Markers? A Systematic Review

Md Lazin Md Lazim MR, Aminuddin A, Chellappan K, Ugusman A, Hamid AA, Wan Ahmad WAN, et al.

Int J Environ Res Public Health, 2020 04 10;17(7).
PMID: 32290168 DOI: 10.3390/ijerph17072591

Finger photoplethysmography (PPG) waveform is blood volume change of finger microcirculation that reflects vascular function. Reflection index (RI), stiffness index (SI) and second derivative of photoplethysmogram (SDPPG) are derived from PPG waveforms proposed as cardiovascular disease (CVD) markers. Heart rate (HR) is a known factor that affects vascular function. Individual resting HR variation may affect RI, SI and SDPPG. This review aims to identify studies about the relationship between HR with RI, SI and SDPPG among humans. A literature search was conducted in Medline via the Ebscohost and Scopus databases to find relevant articles published within 11 years. The main inclusion criteria were articles in the English language that discuss the relationship between HR with RI, SI and SDPPG using PPG among humans. The search found 1960 relevant articles but only six articles that met the inclusion criteria. SI and RI showed an association with HR. SDPPG (SDPPG-b/SDPPG-a ratio, SDPPG-d/SDPPG-a ratio, aging index (AGI) and revised aging index (RAGI)) also had an association with HR. Only RI had a considerable association with HR, the association between SI and HR was non-considerable and the association between HR and SDPPG was inconclusive. Further interventional studies should be conducted to investigate this issue, as a variation in resting HR may challenge the validity of PPG-based CVD markers.

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