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Eddie Y K Ng

Publications and source records attributed to Eddie Y K Ng.

8 recordsLinked to original sources
PubMed2006

Parametric study of the biopotential equation for breast tumour identification using ANOVA and Taguchi method.

Extensive literatures have shown significant trend of progressive electrical changes according to the proliferative characteristics of breast epithelial cells. Physiologists also further postulated that malignant transformation resulted from sustained depolarization and a failure of the cell to repolarize after cell division, making the area where cancer develops relatively depolarized when compared to their non-dividing or resting counterparts. In this paper, we present a new approach, the Biofield Diagnostic System (BDS), which might have the potential to augment the process of diagnosing breast cancer. This technique was based on the efficacy of analysing skin surface electrical potentials for the differential diagnosis of breast abnormalities. We developed a female breast model, which was close to the actual, by considering the breast as a hemisphere in supine condition with various layers of unequal thickness. Isotropic homogeneous conductivity was assigned to each of these compartments and the volume conductor problem was solved using finite element method to determine the potential distribution developed due to a dipole source. Furthermore, four important parameters were identified and analysis of variance (ANOVA, Yates' method) was performed using design (n = number of parameters, 4). The effect and importance of these parameters were analysed. The Taguchi method was further used to optimise the parameters in order to ensure that the signal from the tumour is maximum as compared to the noise from other factors. The Taguchi method used proved that probes' source strength, tumour size and location of tumours have great effect on the surface potential field. For best results on the breast surface, while having the biggest possible tumour size, low amplitudes of current should be applied nearest to the breast surface.

Analysis of Variance↗
PubMed2006

Explaining left ventricular pressure dynamics in terms of LV passive and active elastances.

There has been much characterization of the heart as a pump by means of models based on elastance and compliance. The present paper puts forward the new concept of time-varying passive and active elastance. The biomechanical basis of cyclic elastances of the left ventricle (LV) is presented. Elastance is defined in terms of the relationship between ventricular pressure and volume as dP = EdV+ VdE, where E includes passive elastance, Ep, and active elastance, Ea. By incorporating this concept in LV models to simulate diastolic (filling) and systolic phases, a time-varying expression has been obtained for Ea, and an LV volume dependent expression has been obtained for Ep. It is proposed to use these two elastances Ea and Ep to represent the intrinsic LV properties. The active elastance, Ea, can be used to characterize the LV contractile state and represents LV pressure variation due to LV volume variation (such as during the filling and ejection phases). The passive elastance, Ep, can serve as a measure of LV resistance to filling. Furthermore, it has been demonstrated how the LV pressure dynamics (and LV pressure response to LV volume) can be explained in terms of Ea and Ep.

Blood Pressure↗
PubMed2005

Left ventricular shape-based contractility index.

This study develops contractility indices in terms of the left ventricular (LV) ellipsoidal geometrical shape-factor. The contractility index (CONT1) is given by the maximum value dsigma(*)/dt wherein sigma(*)=sigma/P, sigma is the wall stress, and sigma(*) is expressed in terms of the shape factor S (the ratio of the minor axis and major axis, B/A, of the instantaneous LV ellipsoidal model). Another contractility index (CONT2) is also developed based on how far apart the in vivo S at the start of ejection is from its optimized value, CONT2=(S(se)-S(se)(op))/S(se)(op), where S(se) refers to the value of S at the start of ejection, S(se)(op) is the derived optimal value of S(se) for which sigma* is maximum. The values of S(=B/A) were calculated from cineventriculographically monitored LV volume, myocardial volume and wall-thickness. Then both the contractility indices were evaluated in normal subjects, as well as in patients with mild heart failure and in patients with severe heart failure. The normal values of CONT1 and CONT2 are 8.75+/-2.30s(-1) and 0.09+/-0.07, respectively. CONT1 decreased in patients with mild and severe heart failures to 5.78+/-1.30 and 3.90+/-1.30, respectively. CONT2 increased in patients with mild and severe heart failures to 0.11+/-0.09 and 0.23+/-0.12, respectively. This implies that a non-optimal and less ellipsoidal shape is associated with decreased contractility (and poor systolic function) of the LV. CONT1 and CONT2 are useful as non-invasively determinable quantitative indices of LV contractility, to distinguish between normal and pathologic LVs.

Humans↗
PubMed2005

Passive and active ventricular elastances of the left ventricle.

BACKGROUND: Description of the heart as a pump has been dominated by models based on elastance and compliance. Here, we are presenting a somewhat new concept of time-varying passive and active elastance. The mathematical basis of time-varying elastance of the ventricle is presented. We have defined elastance in terms of the relationship between ventricular pressure and volume, as: dP = EdV + VdE, where E includes passive (Ep) and active (Ea) elastance. By incorporating this concept in left ventricular (LV) models to simulate filling and systolic phases, we have obtained the time-varying expression for Ea and the LV-volume dependent expression for Ep. METHODS AND RESULTS: Using the patient's catheterization-ventriculogram data, the values of passive and active elastance are computed. Ea is expressed as [formula: see text] Epis represented as: [formula: see text]. Ea is deemed to represent a measure of LV contractility. Hence, Peak dP/dt and ejection fraction (EF) are computed from the monitored data and used as the traditional measures of LV contractility. When our computed peak active elastance (Ea,max) is compared against these traditional indices by linear regression, a high degree of correlation is obtained. As regards Ep, it constitutes a volume-dependent stiffness property of the LV, and is deemed to represent resistance-to-filling. CONCLUSIONS: Passive and active ventricular elastance formulae can be evaluated from a single-beat P-V data by means of a simple-to-apply LV model. The active elastance (Ea) can be used to characterize the ventricle's contractile state, while passive elastance (Ep) can represent a measure of resistance-to-filling.

Blood Pressure↗
PubMed2005

Is thermal scanner losing its bite in mass screening of fever due to SARS?

Severe acute respiratory syndrome (SARS) is a highly infectious disease caused by a coronavirus. Screening to detect a potential SARS infected person plays an important role in preventing the spread of SARS. The use of infrared thermal imaging cameras has been proposed as a noninvasive, speedy, cost effective and fairly accurate means for mass blind screening of potential SARS infected persons. Infrared thermography provides a digital image showing temperature patterns. This has been previously utilized in the detection of inflammation and nerve dysfunctions. It is believed that IR cameras can potentially be used to detect subjects with fever, the cardinal symptom of SARS, and avian influenza. The accuracy of the infrared system can, however, be affected by human, environmental, and equipment variables. It is also limited by the fact that the thermal imager measures the skin temperature and not the core body temperature. As known, the body determines a temperature as its so-called "set point" at any one time during the body temperature regulation. Fever happens if the hypothalamus detects pyrogens and then raises the set point. The time course of a typical fever can be divided into three stages. When the fever initiates, the body attempts to raise its temperature but vasoconstriction occurs to prevent heat loss through the skin. With this reason, some individuals at this stage of fever (at the rising slope and immediately after fever begins or falling slope after the fever breaks) will not be detected by the scanner if it is not designed to detect subject at the plateau of the fever (with her/his high core temperature) in particular. This paper aims to study the effectiveness of infrared systems for its application in mass blind screening to detect subjects with elevated body temperature. For this application, it is critical for thermal imagers to be able to identify febrile from normal subjects accurately. Minimizing the number of false positive and false negative cases, improves the efficiency of the screening stations. False negative results should be avoided at all costs, as letting a SARS infected person through the screening process may result in potentially catastrophic results. Various statistical methods such as linear regression, Receiver Operating Characteristics analysis, and neural networks based classification were used to analyze the temperature data collected from various sites on the face on both the frontal and side profiles. Two important conclusions were drawn from the analysis: the best region on the face to obtain temperature readings and the optimal preset threshold temperature for the thermal imager. To conclude, the current research application will remain an interest and useful for reference by both local and overseas manufacturers of thermal scanners, users, and various government and private establishments. As elevation of body temperature is a common presenting symptom for many illnesses including infectious diseases, thermal imagers are useful tools for mass screening of body temperature not only for SARS but also during other public health crisis where widespread transmission of infection is a concern.

Body Temperature↗
PubMed2005

Systolic modeling of the left ventricle as a mechatronic system: determination of myocardial fiber's sarcomere contractile characteristics and new performance indices.

BACKGROUND: In this paper, the left ventricle (LV) is modeled as a cylinder with myocardial fibers located helically within its wall. A fiber is modeled into myocardial structural units (MSUs); the core entity of each MSU is the sarcomeric contractile element. The relationship between the sarcomere unit's contractile force and shortening velocity is expressed in terms of the LV model's wall stress and deformation, and hence in terms of the monitored LV pressure and volume. Then, the LV systolic performance is investigated in terms of a mechatronic (excitation-contraction) model of the sarcomere unit located within the LV cylindrical model wall. METHODS: The governing equation of dynamics of the LV myocardial structural unit (MSU) is developed, involving the parameters of the series-elastic element (SE), the viscous element (VE) and the contractile element (CE). We then relate the MSU's force and displacement variables (in terms of SE, VE and CE parameters) to the LV pressure and volume, using the patient's catheterization-ventriculogram data. We thereby evaluate the MSU elements' parameters. RESULTS: We then determine the sarcomere (CE) 'force vs. shortening-velocity' characteristics as well as the power generated by the sarcomere (or CE) element. These are deemed to be important LV functional indices. When our computed sarcomeric peak-power is compared against the traditional LV contractility indices (by linear regression), a high degree of correlation is obtained. CONCLUSIONS: We have provided herein, a LV systolic-phase (cylindrical geometry) model whose wall contains the myocardial fibers having sarcomere units. We have expressed the LV myocardial sarcomere's CE (force vs. shortening-velocity) characteristics in terms of the LV pressure-volume data. These CE properties express the intrinsic performance capacity of the LV. Hence, indices containing these properties are deemed to reflect LV performance. In this regard, our new LV contractility index correlates very well with the traditional LV contractility index dP/dt(max).

Biomechanical Phenomena↗
PubMed2004

Analysis of IR thermal imager for mass blind fever screening.

BACKGROUND: Obtaining meaningful temperature for the human body requires identifying a body site that will provide reliable data across a large population. It is important to understand that skin temperature does not solely depend on body-core temperature and may be affected by other physiological and environmental factors. Currently, there is lack of empirical data in correlating facial surface temperature with body core temperature. Present IR systems in use at airports/immigration checkpoints have not been scientifically validated particularly in regards to the false-negative rate. As a result, they may create a false sense of security by underestimating the number of febrile (and possibly infected) individuals. This article evaluates the effectiveness of thermal scanner when it is being used for mass blind screening of potential fever subjects such as SARS or bird flu patients. METHODS: Bio-statistics with regression analysis and ROC is applied to analyse the data collected (502) from the SARS hospital in Singapore and conclusive results are drawn from them. The results are vital in determining two very important pieces of information: the best and yet practical region on the face to take readings and optimal pre-set threshold temperature for the thermal imager. RESULTS: (1) The thermal scanner can be used as a first line tool for the mass blind screening of hyperthermia, (2) the readings from the scanner suggest good correlation with the ear temperature readings, (3) an imager temperature threshold should be determined by the environmental factors, outdoor condition in particular, the physiological site offset and the performance characteristics of thermal imager to warrant the most accurate and reliable screening operation. CONCLUSIONS: The analysis suggested that the thermal imager used holds much promise for mass blind screening when the readings from a specific region have a good correlation with the ear temperature. From the regression analysis, the best reading is taken from the maximum temperature in the eye region, followed by the maximum temperature in the forehead region. With ROC analysis, a randomly selected individual from the fever group has a test value larger than that for a randomly selected individual from the normal group in 97.2% of the time. The test can distinguish between the normal and febrile groups and an optimum threshold temperature for the thermal imager can be found. The pre-set threshold cut-off temperature for the current thermal imager was found to be 36.3 degrees C with reference to the associated environmental condition. Any temperature readings that exceed this reading will trigger off the alarm and a thermometer will be used to verify the whether the person is having fever.

Adult↗