Sundaram Swaminathan

Determination of single living cell’s dry/water mass using optofluidic chip

This paper presents an interferometric method for measuring the dry/wet mass of a single living cell using an optofluidic chip. It consists of the fiber Mach-Zehnder interferometer and the fiber-optical trap, both of which are integrated onto a single chip. In experiment, a single living cell is captured by the fiber-optical trap, and then the cell’s refractive index and diameter are simultaneously determined by the spectral shift in response to the buffer modulation. Hence, both cell dry and water masses can be calculated with a precision higher than 5%.

Segmentation and classification of heart sounds

An algorithm for segmentation of heart sounds (HSs) into a single cardiac cycle (Sl-Systole-S2-Diastole) using homomorphic filtering and k-means clustering and a three way classification of heart sounds into normal (N), systolic murmur (S), and diastolic murmur (D), based on neural networks is developed. This algorithm does not require additional reference signal such as ECG signal. Feature vectors are formed after segmentation by using Daubechies-2 wavelet detail coefficients at the second decomposition level. Redundant features are removed using principal component analysis (PCA). Multilayer perceptron-backpropagation neural network (MLP-BP) is used for classification of three different HSs. A classification accuracy of 94.5% and a segmentation accuracy (or performance) of 90.45% was achieved; thus, demonstrating that segmentation and classification of heart sounds without the aid of reference signal is achievable

Design of a mobile telemedicine system with wireless LAN

Many current telemedicine systems use hardwired fixed lines, like ISDN, LAN, and even ATM access for their data transmission and real-time telemonitoring. With the advent of new wireless broadband technologies, the migration of telemedicine applications to the wireless domain is imminent. Mobile telemedicine is a newly emerging yet promising area, integrating wireless communications for different telemedicine applications. In this study, the design of a wireless LAN telemedicine system is proposed. The system enables real-time, interactive integration of medical data, voice and video transmission in a wireless and mobile environment. The preliminary results show that it is possible to provide stable and reliable mobile medical services that are not possible with fixed systems. Some of the technical problems and economic aspects associated with the implementation of a mobile telemedicine system with wireless LAN are presented in the paper.

Novel analysis technique for a brain biometric system

We present various techniques to detect a target in an oddball paradigm. These techniques are presented with reference to two P300 paradigms being studied to build a biometric system using electroencephalogram (EEG) signals. The novel inblock paradigm presented in this paper proposes a possible variant to the known oddball paradigm and analyses the effect of spatial location of the target block with respect to the non-target block. It brings out a new approach in the oddball paradigm, wherein location of the target might help evoke a higher P300 potential. A comparison of the various analysis techniques studied for both the paradigms is also presented. Initial results from four subjects show that energy analysis gave improved results than the traditional amplitude analysis techniques for target detection in the studied oddball paradigms. The results were comparable for all subjects except for one subject where energy analysis provided better target detection, suggesting that energy based methods could be further explored. This proposed novel paradigm is a step towards the online brain biometric system which is being built for authentication in high security scenarios.

Classification of Homomorphic Segmented Phonocardiogram Signals Using Grow and Learn Network

A segmentation algorithm, which detects a single cardiac cycle (S 1-systole-S2-diastole) of phonocardiogram (PCG) signals using homomorphic filtering and K-means clustering and a three way classification of heart sounds into normal (N), systolic murmur (S) and diastolic murmur (D) using grow and learn (GAL) neural network, are presented. Homomorphic filtering converts a non-linear combination of signals (multiplied in time domain) into a linear combination by applying logarithmic transformation. It involves the retrieval of the envelope, a(n) of the PCG signal by attenuating the contribution of fast varying component, f(n) using an appropriate low pass filter. K-means clustering is a non-hierarchical partitioning method, which helps to indicate single cardiac cycle in the PCG signal. Segmentation performance of 90.45% was achieved using the proposed algorithm. Feature vectors were formed after segmentation by using Daubechies-2 wavelet detail coefficients at the second decomposition level. Grow and learn network was used for classification of the segmented PCG signals and a classification accuracy of 97.02% was achieved. It is concluded that homomorphic filtering and GAL network could be used for segmentation and classification of PCG signals without using a reference signal

Microsensor characterization in an integrated blood gas measurement system

In the healthcare sector, the monitoring of blood gases and other chemicals in the blood is crucial as they provide vital signs of the respiratory and metabolic well being of the human body. The measurement of blood gases is conventionally done using glass electrode sensors. The development of ion-sensitive field effect transistor (ISFET) has created a high potential in multiparameter chemical sensor devices. This microsensor is essentially based on the established MOSFET technology. In the design and characterisation of a pH ISFET sensor, the ISFET model was characterised and a final design has been evolved with the assistance of MATLAB and HSPICE software. Silicon nitrate (Si/sub 3/N/sub 4/) and aluminium oxide (Al/sub 2/O/sub 3/) were the ion-sensitive membranes considered in the model. pH analyses were performed on both the membranes to evaluate the electrical responses of the sensor to the change in pH. The effect of the physical parameters of the ISFET on the drain-source current output is studied. Various physical and electrical parameters have been analysed to propose an optimal output response of the ISFET sensor. The sensor achieved an average sensitivity of 50 mV/pH, which is comparable to other published works. By being capable of miniaturization, further advantages are gained, namely easier fabrication, better performance characteristics of the sensor, and the ability to integrate with other biomedical sensors on the same die without any electrical or spatial interferences.

Disaster recovery services in the cloud for SMEs

In brief, Disaster recovery (DR) covers the process, policies and procedures related to preparing for recovery or continuation of technology infrastructure critical to an organization after a natural or human-induced disaster. It is a critical aspect of Business Continuity Management (BCM), as without data, the business comes to a standstill. DR in cloud would allow SMEs to cut down their costs on expensive IT infrastructure and reduce the burden on IT department. This paper throws light upon the need for cloud and the services provided by cloud. It aims at provisioning the need for DR in companies and how DR in cloud would be the best service among all the cloud services and how the same would be highly beneficial to SMEs.

Effects of substrate temperature and V/III flux ratio on the growth of InAIAs on InP substrates by molecular beam epitaxy

Abstract Molecular beam epitaxial growth of In 0.52 Al 0.48 As epilayers on InP(100) substrates at a wide range of substrate temperatures (470–550°C) and at arsenic overpressures (V/III ratio) which are higher than previously reported [4] is carried out. Analysis performed using low temperature photoluminescence (PL) showed a strong dependence of the photoluminescence (PL) linewidth on the substrate temperature. Corresponding X-ray diffraction measurements showed the lowest lattice-mismatch between the In 0.52 Al 0.48 As epilayer and InP substrate to occur at the substrate temperature at which the lowest PL linewidth was achieved. However, within the range of V/III flux ratios investigated (32 to 266), narrow PL linewidths of less than 20 meV were measured, and the linewidths tend to be generally narrower at flux ratios greater than 150. The lowest value of 14 meV was recorded for the samples grown at a V/III ratio of 160. The lattice-mismatch between the epilayer and the substrate for these samples was also found to be relatively insensitive towards changes in the V/III flux ratios.

Image stabilization using memristors

The paper describes an image stabilization model based on the compensatory Vestibulo-Ocular Reflex. It provides for an anti-shake mechanism that helps ensure that the object being tracked by a camera always remains in focus and does not get blurred due to rotational or translational movements. The model uses memristors in order to develop a multi-directional circuit, which has a function similar to that of the neuron-synapse. Being a simulation of a human reflex action, the model is hardware dependent and uses minimum interaction with the processors. This ensures that the image stabilization response is fast and no undue load is made on the processor. This model has an immense application in robotics, where the motion of the robots head needs to be taken into account and a compensatory mechanism is required to provide a continuous sharp image for processing.

MEMS based piezoelectric sensor system for virus detection

In this paper we design a novel piezoelectric MEMS sensor for the detection of 100nm size viruses that include HIV and Herpes. A PZT-5A piezoelectric micro cantilever of length 500 μm is used in the model for sensing changes in mechanical vibrations caused by adsorption of virus mass of the order of ng at the tip of cantilever, producing an output signal at different resonant frequencies. A COMSOL model for the MEMS based piezoelectric sensor shows high sensitivity to changes in attached mass at the tip. This would allow the sensor system to be used for detection of specific viruses by incorporating appropriate biomarkers that provide selective binding for such viruses. Design of op-amp based signal processing circuits provides high gain, low noise output. The results strongly indicate the reliability of designed sensor for 100 nm HIV, Herpes viruses.