Removal of Power Line Interference from ECG Signal
Design of RISCV Processor using Verilog
Designing and Analysis of Electrocardiogram Simulator Tool Kit
A Novel Communication System Based on Sign Language Recognition and Voice Conversion for Differently Abled Person
Cerebral Infraction Prediction System using ECG and PPG Bio-Signal
Blockchain 3.0: Towards a Secure Ballotcoin Democracy through a Digitized Public Ledger in Developing Countries
Fetal ECG Extraction from Maternal ECG using MATLAB
Brief Introduction to Modular Multilevel Converters and Relative Concepts and Functionalities
Detection of Phase to Phase Faults and Identification of Faulty Phases in Series Capacitor Compensated Six Phase Transmission Line using the Norm of Wavelet Transform
A Novel Approach to Reduce Deafness in Classical Earphones: MUEAR
A novel mathematical ECG signal analysis approach for features extraction using LabVIEW
Filtering of ECG Signal Using Adaptive and Non Adaptive Filters
Application of Polynomial Approximation Techniques for Smoothing ECG Signals
A Novel Approach to Improve the Wind Profiler Doppler Spectra Using Wavelets
A Novel Communication System Based on Sign Language Recognition and Voice Conversion for Differently Abled Person
Several studies and surveys have shown that having independent mobility brings significant benefits to both children and adults. While many people with disabilities are contained in traditional or motorized wheelchairs, some of the disabled community find difficulty in using wheelchairs. Many researchers have experimented with various technologies to make the wheelchair suitable for this purpose. The proposed design includes manual control and includes a voice activation system for people with physical disabilities. This paper describes a "Voice Controlled Collision Avoidance Wheelchair" for people with disabilities in which a voice command controls the movements of the wheelchair. The voice command is transmitted through a Bluetooth-enabled cellular device, and the command is transmitted and converted to a string using BT Voice Control for Arduino, and then to an SR-04 Bluetooth module connected to the Arduino board to control the wheelchair. The project also provides for smart wheelchairs by incorporating collision avoidance systems using an ultrasonic sensor and stairwell fall protection devices to prevent wheelchairs from falling downstairs.
The most convenient speech processing tool is Artificial Neural Networks (ANNs). The effectiveness has been tested with various real-time applications. The classifier using artificial neural networks identifies utterances based on features extracted from the speech signal. The proposed approach to multilingual speaker identification consists of two parts, such as a training part and a testing part. In the training part, the classifier is trained using speech feature vectors. The spoken language contains complete information, such as details about the content of the message and details about the speaker of that message. In the present work, the speech signal databases of different speakers in a multilingual environment were recorded in three Indian languages, i.e., Hindi, Marathi, and Rajasthani. The cepstral characteristics of the speech signal were extracted: Mel-Frequency Cepstral Coefficients (MFCC) and Gammatone Frequency Cepstral Coefficients (GFCC). The system is designed for speaker recognition through multilingual speech signals using MFCC, GFCC, and combined functions as acoustic characteristics. Training and testing were performed using the Neural Network (NN) function, robust Backpropagation Algorithm (BPA), and Radial Basis Functions (RBF), and the results were compared. The accuracy of the speaker identification system is 94.89% using BPA and 96.62% using the RBF neural network.
In signal processing, a filter is a device or process that removes some unwanted components or features from a signal. Digital filters are mainly divided into Infinite Impulse Response (IIR) filters and Finite Impulse Response (FIR) filters. FIR filters are mostly used in applications like image processing, communications, Digital Signal Processing (DSP) etc. One of the most used filters for designing of VLSI circuits is FIR filter. Systolic architecture is a Processing Element (PE) network that generates and passes data rhythmically through the system. The concept of systolic architecture can map high-level computing into hardware structures. FIR filter with systolic architectures provide better examples for efficient VLSI and FPGA implementations of many digital signal processing applications because of their modularity and regularity features.
A novel Power Line Interference (PLI) detection and suppression algorithm is proposed to preprocess Electrocardiogram (ECG) signals. A distinctive feature of this algorithm is the ability to detect the presence or absence of PLI in the ECG signal before applying the PLI suppression algorithm in the ECG signal. Only after the detection of PLI, it can be suppressed. We propose a PLI detector employing a classifier designed based on observations of the Root Mean Square (RMS) values of noise and reference ECG signals. An efficient recursive Least Mean Square (LMS) adaptive notch filter was also developed to serve the purpose of PLI suppression. An adaptive filter consists of a digital filter with adjustable coefficients and an LMS algorithm to modify the coefficient values to filter each sample. Experimental results demonstrate superior performance of this proposed algorithm.
The goal of this paper is to create an object detector model that can detect objects for visually impaired people and other commercial users by detecting it at a certain distance. Existing object detection algorithms required a huge amount of training data, which took longer and was extremely complex. This is also a difficult task. As a result, it presents a computer vision paradigm for converting an object to text by importing a pre-trained CAFFEMODEL (a machine learning model created by Caffe) framework dataset model, and the texts are further converted to speech. This method allows the detection of multiple objects on the same screen. It helps in real-time object detection. This paper discusses the concept, methodology, and system architecture for the implementation of the system in combination with the obtained intermediate results and analyzes the tools used in the proposed system. This system can then be implemented in any other system. Portable gadgets that detect objects at a certain distance from visually impaired people and transmit a voice signal.
