Veena N. Hegde

RANDOM NOISE CANCELLATION IN BIOMEDICAL SIGNALS USING VARIABLE STEP SIZE GRIFFITH LMS ADAPTIVE LINE ENHANCER

This paper presents a new method of random noise cancellation for removing artefacts from biomedical signals using an adaptive line enhancer (ALE). The ALE is implemented using proposed time domain variable step size Griffith least mean square (VSGLMS) algorithm. The technique is based on the adaptation of the gradient of the error surface. The method makes both the step size and the gradient free from observation noise and reduces the gradient mis-adjustment error. Here, both the gradient and the scale factor for the step size are free from the input noise effects, which makes the algorithm robust to both stationary and non-stationary observation noise. Further the additional computational load involved for this is marginal. The VSGLMS adaptive filter technique for ALE is tested on noise cancellation of two types of bio-medical signals — separation of electro cardiogram (ECG) signal from a background of electro myogram (EMG) and heart sound signal (HSS) from lung sound signal (LSS). Application of VSGLAM...

A novel concept of Smart Headphones using Active Noise Cancellation and speech recognition

This project presents an engineering low cost solution to a contemporary issue of speech recognition in a headphone. The “Smart Headphone” has been brought out as a prototype design in which two principles of Active Noise Cancellation (ANC) have been achieved using a Digital Signal Processor (TMS320C5416). The system will detect the surrounding environment in real time and process the significant information to the user and thereby reducing the risk of accidents. It can warn users of incoming traffic (e.g. fire engines and ambulances) nearby and surrounding danger. It can be controlled by the users voice commands; such as increasing or decreasing volume with the help of an interface controlled by a microcontroller (MSP430F2013) and the voice recognition module VR 3.1. The multifunction intelligent headphone will also notify the user if someone is trying to talk to them. The system presented here has profound implications for future studies of Wearable Computing and would help the society in a great way reducing the amount of traffic accidents suffered by people due to wearing headphones while driving or walking unaware of the surroundings.

Comparison of characterizing and data analysis methods for detecting abnormalities in ECG

The electrocardiogram (ECG) is an important bioelectrical signal which gives valuable information about the functional aspects of the heart both in normal and abnormal conditions. For several decades a considerable amount of research activity has been directed towards advancement in the clinical diagnosing of this disease using surface ECG and symptoms. This paper compares different methods that have evolved over the years for elimination of different types of noise present in ECG and for characterizing ECG for the detection of myocardial ischemia and infarction which is a life threatening heart disease. The first part of the review gives broad overview of the research undergone in the area of denoising methods deployed and second part describes different types of ischemia and methods to detect the disease using ECG.

AquaPredicto — Freshwater quality management system for lakes

Lakes are important part of urban ecosystem. They are small aquatic bodies, but perform significant environmental, social and economic functions. Their contribution ranges from being a source of drinking water, recharging groundwater, acting as sponges to control flooding, supporting biodiversity and providing livelihoods. Many economic sectors such as agriculture, domestic applications consider lakes as easily available source of water for their day to day needs. Lakes may be man-made or natural, fresh water or brackish; but they play a very vital role in maintaining environmental sustainability particularly in urban environments. In todays urbanization, especially in contexts when the cities are facing the challenges of enhanced traffic and pollution, lakes and freshwater bodies are the hopes for restoring the ecosystem. At present, in India, lakes and wetlands are in extremely bad shape and are suffering from varying degrees of environmental degradation. Despite knowing their environmental, social and economic significance, city planners have given least importance to protect them and have even destroyed these water bodies. Due to unplanned industrialization, much of the landscape around the lakes in urban area and their surroundings has been covered by impervious surfaces. As a result, instead of rainwater, it is the sewage and effluents that are filling up urban water bodies. Once the known sponges of urban area, today urban lakes have turned into hazards needing utmost attention, that get choked even with low rainfall and overflow into the blocked canals during high rainfall. In recent times, during the rainy season, the lakes and fresh water bodies have become reasons for causing floods in the city. The cities are witnessing eventual disappearance of these sponges that has exacerbated floods and sharpened the pain of droughts. In an attempt to provide a solution to this complex problem, our paper presents a model and testing mechanism towards bringing the awareness about the lake water health monitoring. Our system consists of sensors including temperature, Total Dissolved Solids (TDS) and pH sensor to calculate the water quality index and create the mathematical model to predict the variation of the parameters in the future. The system will help the stakeholders and public to be aware of the condition of the lakes and take corrective actions to prevent further degradation.

Low cost eye based human computer interface system (Eye controlled mouse)

This paper presents a low cost eye based Human Computer Interface (HCI) developed for amputees and paralyzed persons. The system is a computer interface that provides the functionality of an input device like mouse based on eye actions such as eye blink, eye-gaze and gaze control. For initialization, the subject just holds his/her head still for a few seconds: using involuntary blinks that would naturally occur during this time, the system both locates the users eye pair as well as forms online templates of the open and shut eyes of the specific user, valid for the rest of that session. The located eyes are tracked in real time using template matching and histogram back projection. Reasonable amount of head motion, carried out at reasonable speeds, are automatically detected and compensated. Automatic re-initialization of the system occurs if the user goes out of frame or during excessive rapid head movement. When the eyes are detected as more than 70% open, the iris tracker module is triggered. In order to detect the iris, the eye image is subjected to image conditioning to eliminate the eyelashes and eyebrow. The iris is detected on the basis of colour and shape, and the Hough transform is used on the region to determine its centre and radius. Iris detection is continuously repeated whenever the eye is open, so that it is continuously tracked. Later on, continuous gaze does the mouse clicking action replacing the mouse of the computer with this HCI.

Optical theremin based true Random Number Generation (TRNG) system

The aim of this paper is to develop a hardware Random Number Generator (RNG) by using an optical Theremin. Theremin is a noncontact electronic musical instrument based on the principle of heterodyne. It has two antennas to control volume and pitch of the sound which form a pair of resonant RLC oscillators. In the presented system, optical sensors (Photodiodes) have been used to produce the notes of the Theremin by varying the intensity of incident light beam. Two photodiodes have been used for this purpose to control gain and pitch of the sound notes. These sound waves are then sampled to give amplitude levels which forms the desired Random Number Sequence and is unique for every tune produced by the Theremin. Since random numbers are at the core of all encryption algorithms and network security such as SSH/SSL, generating high-entropy random numbers is the prime need of the hour.

Parallel Processing Architecture for ECG Signal Analysis

—Research in detecting QRS peaks in ECG signals has progressed to an acceptable extent and hence has gained adequate confidence with respect to the validity of the outputs produced. In view of the dynamics associated with ECG signals, their variants among subjects owing to varied types of problems encountered; it has become essential to, continuously, expand the scope of analysis to provide more and useful information from the ECG data. This warrants for a flexible architecture for ECG signal analysis. This paper presents one such flexible architecture. The authors are working towards identification of appropriate interfaces and their definitions.

DCT-BASED VARIABLE STEP SIZE GRIFFITHS' LMS ALGORITHM FOR RANDOM NOISE CANCELLATION IN ECGs

This paper presents a new random noise cancellation technique for cancelling muscle artifact effects from ECG using ALE in the transformed domain. For this a transform domain variable step size griffith least mean square (TVGLMS) algorithm is proposed. The technique is based on the adaptation of the gradient of the error surface. The method frees both the step size and the gradient from observation noise and reduces the gradient mis-adjustment error. The sluggishness introduced due to the averaging of the gradient in the time domain is overcome by the transformed domain approach. The proposed algorithm uses a discrete cosine transform (DCT)-based signal decomposition due to its improved frequency resolution compared to a discrete Fourier transform (DFT). Furthermore, as the data used symmetrical, DCT usage results in low leakage (bias and variance). The performance of the proposed method has been tested on ECG signals combined with WGN, extracted from MIT database, and compared with several existing techniques like LMS, NLMS, and VGLMS.