In neurological field, Cerebellar Ataxia (CA) prediction is done with Gait values of human actions. The Analysis of Gait (AoG) may lead the good treatment. The goal of this work was to develop a ...machine-learning-based model for predicting AoG using the poor gait patterns that occur before AoG. While executing designed AoG-provoking walking tasks, an accelerometer was connected to the lower back of 21 subjects with 12 different walking positions to gather acceleration impulses. The exercise was walking for one minute at each of 12 varied walking speeds on a split-belt treadmill in the range 0.6, 1.7 m/s in 0.1 m/s increments. To reduce the effects of weariness, the speed sequence was randomized and kept a secret from the subjects. Machine-learning algorithms like support vector machine (SVM) and k-nearest neighbours (KNN) have been tested in existing research studies. These algorithms perform well when the amount of data is little and the classification is binary. SVM, KNN, decision trees, and XGBoost algorithms have all been used in the proposed study on the CA data set. We discovered that the AdaBoost algorithm provides a more accurate categorization of the severity of CA disease.
Abstract
Cardiovascular disorder is a primary cause of mortality throughout the world in both developed and underdeveloped countries. Continuous cardiac monitoring enables clinicians to identify ...arrhythmias and other heart conditions. Tele-cardiology introduces remote monitoring devices for tracking the cardiac activity of the patients. The large volume of Electrocardiogram (ECG) data needs to be stored, processed and transmitted by these portable health care devices. The implementation of ECG compression in hardware platform is crucial for continuous health monitoring applications. The aim of this work is to implement field programmable gate array based set partitioning in hierarchical trees-based electrocardiogram compression. Discrete wavelet transform method is employed to break up the signal into sub bands. The transformed coefficients after discrete wavelet transform are passed through dead zone quantization which rejects low magnitude values of transformed coefficients lying around zero. These quantized coefficients are then encoded by lossless set partitioning used in hierarchical trees compression approach. The introduction of dead zone quantization in the proposed technique is found to be effective and yields an increased compression ratio of 10.33 with decreased distortion value of 1.04 percent for ECG record 117 of MIT-BIH arrhythmia database.
Maritime surveillance using remote-sensing images is one of the emerging technologies. Because of the inaccessibility of real-time remote-sensing images, it is imperative to model them. The main ...intention of this study is to investigate the factors influencing the detection of submarines, irrespective of the imaging sensors. In the present work, submarine wakes (Bernoulli hump and Kelvin wake) are modeled and integrated with the sea surface to examine the key features of the submarine. Here, the sea surface is simulated by linear Airy theory using the Elfouhaily spectrum, and novel submarine position projection in imaging coordinate (SPPIC) technique is introduced to generate synthetic free surface wakes in different orientations. Besides, Computational Fluid Dynamics (CFD) technology is utilized to assess and endorse the SPPIC-based simulated wake models. The Beaufort scale is used to validate the modeled sea surface, and the root mean square error of the model is 0.314 m. Then, the simulated submarine wakes are verified by analyzing its essential features and extracting the significant parameters of submarine, such as moving velocity, heading angle, and diving depth. Further, the current research explores these significant characteristics in the context of ocean waves. The Fourier transform technique is employed to retrieve the heading angle and velocity of the submarine. The introduction of variance distribution in the Radon transform method resolves the 180⁰ ambiguity problem in heading angle calculation. Additionally, negative exponential relation is established between the diving depth of the submarine and the height of the Bernoulli hump. From this empirical equation, one can fetch the diving depth of the submarine. The discrete wavelet transform approach enhances the edges of the wedge Kelvin wake in the presence of sea waves and is demonstrated with real-time synthetic aperture radar images. Moreover, primary wake features are investigated and evaluated for different classes of submarines.
•Modeling of free surface submarine wakes at various orientations, velocities, and depths using the SPPIC method.•Computational Fluid Dynamics (CFD) technology is utilized to assess and endorse the SPPIC-based simulated wake models.•The exploration of submarine's wake characteristics in the context of ocean waves using wavelet filter.•Retrieval of the submarine's primary parameters such as velocity, heading angle, and depth using Fourier and Radon techniques.•A new empirical relation is derived to inverse the depth of the submarine from its Bernoulli hump height measurements.
Artificial intelligence (AI) is the emerging field to diagnose and analyze chronic illnesses like Cerebellar Ataxia (CA),Spinocerebellar Ataxia (SCA), and Parkinson's disease. AI technologies such as ...machine learning and deep learning assist many doctors, diagnosis departments, and medical personnel in identifying and analyzing neurological disorders
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