Neelu Jain

A Survey on Integrated Wireless Healthcare Framework for Continuous Physiological Monitoring

Wireless Body Area Network in recent years has received significant attention, due to their market potential to reduce the healthcare cost as well as load of medical professionals, resulting in higher efficiency. This paper addresses the available wireless body area network prototypes and the issues related to hardware implementations, software and wireless protocols and how smart phones can be used as full featured portable computer in providing healthcare services. These systems are comprised of various types of small physiological sensors ie, ECG, SpO2 attached to the human body for measuring the physiological parameters and transmit them to remote devices.

Performance and Evaluation of Smartphone Based Wireless Blood Pressure Monitoring System Using Bluetooth

In medical practice, blood pressure is intensively studied parameter and often measured for diagnosis at primary healthcare level. In this paper, the state-of-the-art Bluetooth technology has been used for designing an innovative wireless blood pressure monitoring system to display the systolic and diastolic blood pressure values on Android-based smartphone. A pilot study was undertaken on 12 healthy subjects to validate the performance of developed prototype by comparing with OMRON HEM-7111 and mercury sphygmomanometer. Comparison shows an accuracy of 98.63% and 97.13% with OMRON HEM-7111 and 98.99% and 98% with mercury sphygmomanometer for systolic blood pressure and diastolic blood pressure, respectively. Bias value in Bland-Altman plots gives good level of agreement within 95% confidence limits. The developed prototype device mean and standard deviation of differences is less than 5 and 8 mmHg, respectively, and it fulfills the recommendation criteria as per the requirement of the Association for Advancement of Medical Instruments protocol.

Resource Allocation Models for Cognitive Radio Networks: A Study

networks (CRN) using game theory are presented. The study includes the concept of cognitive radio (CR) networks, cooperative and non-cooperative game theory, and modeling of strategic interaction process for CR enabled secondary users. The prime objective of the present study is to compare existing game models for CR networks in terms of concept, approach, system model, and issues associated with each model. At last, conclusion for implementing game models in the cognitive radio networks for effective management of available radio resources is given to provide direction to researchers for future work.

Text Extraction from Document Images- A Review

extraction in an image is a challenging task in the computer vision. Text extraction plays an important role in providing useful and valuable information. This paper discusses various approaches such as Adaptive Local Connectivity Map (ALCM), Expectation Maximization (EM), Maximization Likelihood (ML), Markov Random Field (MRF), Spiral Run Length Smearing Algorithm (SRLSA), Curvelet transform etc. for extracting text from scanned book covers, journals, multi-color document, handwritten document, ancient document and newspaper document images. Text line segmentation is a major component for document image analysis. Text in documents depend upon various factors such as language, styles, font, sizes, color, background, orientation, fluctuating text lines, crossing or touching text lines. This paper provides performance comparison of several existing methods suggested by researchers in document text extraction on the basis of recall rate, precision rate, processing time, accuracy etc. KeywordsCharacter Recognition (OCR), Morphological Component Analysis (MCA), Undecimated Wavelet Transform (UWT), Discrete Wavelet Transform (DWT), Connected Component Analysis (CCA), Adaptive Local Connectivity Map (ALCM), Expectation Maximization (EM), Maximum Likelihood (ML), Spiral Run Length Smearing Algorithm (SRLSA), Resolution Enhancement (RE), Markov Random Field (MRF), Maximum A-posteriori Probability (MAP), Block Energy Analysis (BEA), Support Vector Machine (SVM), Thin Line Coding (TLC), Constrained Run Length Algorithm (CRLA). .

Performance analysis of text-dependent speaker recognition system based on template model based classifiers

Speaker recognition technology has found its usage in varied different fields including security systems, banking operations and forensic laboratories etc. due to its easy implementation, flexibility and security. Each of these applications demand high performance i.e. high speaker recognition rate. In this paper, MFCC based text-dependent SR system is presented. The speaker voice is modeled by Mel spaced frequency spectrum. The performance of the system has been evaluated using our own recorded subject database and compared on the basis of two template model based classifiers - Nearest Neighbor (NN) and Vector Quantization (VQ), in terms of parameters such as recognition accuracy rate, system processing time, number of users and size of the training database. Based on the experiments, it was found that VQ performed better than NN for all the parameters. Although both the classifiers use Euclidean distance as a similarity determination function between training and testing data but NN being an instance based algorithm (lazy algorithm) do not build any model for training data and hence lags behind VQ in performance whereas the VQ builds code vectors of different users by clustering as soon as the training data is fed.

Adaptive Power Control Scheme for the Cognitive Radio System Based on Receiver Sensitivity

Cognitive radio has been proposed as the most promising technology to overcome the spectrum scarcity problem by exploiting the vacant frequency band of assigned licensed spectra; though some tradeoffs exist to protect the licensed primary user communication and to enhance the throughput of unlicensed secondary cognitive user. Through spectrum sensing and power control scheme, this issue can be addressed well as it allows the cognitive user to access the licensed band when primary user is not using it. In most of the previous works, it has been assumed that for transmission power control, perfect channel state information is available beforehand to the cognitive transmitter. This assumption does not hold good in practical scenarios and moreover it is difficult to implement spectrum sensing in device. To address this issue, a sensing free power control scheme based on CR receiver sensitivity is proposed in this paper. It allows cognitive user to controls its transmission power adaptively by approximating the distance from primary through cognitive receiver sensitivity. Simulation results are presented to verify the theoretical analysis.

An Intelligent Text to Speech System for Windows based Systems and Mobile Devices

Text-to-speech) systems are used invariably as part of our daily lives and have come a long way. In this paper TTS system using Concatenative synthesis based on the SDK (Software Development Kit) platform has been presented. This system is compatible with both computer and mobile devices. It has a user friendly GUI (graphical user interface) to control various speech parameters. Speech signal produced can be saved and listened to whenever required. Signal analysis of the output speech can also be done using TTS System. The results of these signal analysis along with the stored speech signal can be used for further applications depending upon the requirements. It is an intelligent system and is able to overcome various normalization problems.

Artifact removal from EEG: A comparison of techniques

EEG or Electroencephalography records the electrical activity taking place inside the brain due to communication occurring between neurons which are the constituting cells of the brain. It is an important bio-potential that reflects changes in brains complex internal activities and hence can provide useful insight into the brains functioning. In recent times it has been found to be useful in diagnosing neural diseases and also in the development of Human Machine Interfaces (HMI). However, EEG is highly susceptible to being corrupted by non-neural signals called artifacts which can significantly affect the end performance of EEG based system. Several techniques have been proposed in literature to remove these artifacts-automatically as well as manually. This paper tends to review three such techniques which broadly represent the main strategies being used by researchers and neurologists to clean EEG.

Drift-diffusion modeling and simulation of four terminal ballistic rectifier

In this paper we simulate two-cross junction based novel rectifier called ballistic rectifier by employing drift-diffusion model using Silvaco Atlas Software. The electrical (DC and RF) characteristics of the device have been characterized at room temperature demonstrating operation at the frequency of 1 THz. The results have been analyzed considering different device dimensions and surface charge densities of InGaAs based heterostructure at various temperatures. It has been observed that rectification of the device deteriorates with the increase in temperature due to the reduction in mean free path of the charge carriers.

A New Approach to Extract Text from Images based on DWT and K-means Clustering

AbstractText present in image provides important information for automatic annotation, indexing and retrieval. Therefore, its extraction is a well known research area in computer vision. However, variations of text due to differences in orientation, alignment, font, size, low image contrast and complex background make the problem of text extraction extremely challenging. In this paper, we propose a texture-based text extraction method using DWT with K-means clustering. First, the edges are detected from image by using DWT. Then, a small size overlapped sliding window is used to scan high frequency component sub-bands from which texture features of text and non-text regions are extracted. Based on these features, K-means clustering is employed to classify the image into text, simple background and complex background clusters. Finally, voting decision process and area based filtering are used to locate text regions exactly. Experimentation is carried out using public dataset ICDAR 2013 and our own dataset f...