Informatics Publishing Limited

S. Sathish ¹, K. Nithyakalyani ¹, S. Vinurajkumar ¹, C. Vijayalakshmi ¹, J. Sivaraman ¹

Affiliations
1 Department of Biomedical Engineering, Vel Tech Multitech, Chennai - 600062, Tamil Nadu, IN

Abstract

Aim: In recent years, physically challenged people faces more constraint in day to-day movements. In this work, an EMG based hands-free control system for a wheelchair is proposed. Methods: Trapezium EMG signals are acquired, analyzed and then processed into a controlled movements (forward, left, right, etc.) using an embedded circuits for the wheelchair. Results: The system allows the patient to choose a smooth independent movement in the control state or non-control state. The movements depend upon the strength of the EMG signals acquired. Conclusion: The entire system consists of EMG electrodes, a microcontroller and a DC motor for the operation of the wheelchair. The control system is incorporated with muscle processing circuits which give an independent and safe movement to the paraplegic patients.

Keywords

EMG, Microcontrollers, Trapezium Muscle, Wheelchair

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P. Padmapriya ¹, K. Manikandan ¹, K. Jeyanthi ¹, V. Renuga ¹, J. Sivaraman ¹

Affiliations
1 Department of Biomedical Engineering, Vel Tech Multitech, Chennai – 600062, Tamil Nadu, IN

Abstract

Aim: This paper proposes the automatic support system for detecting the tumor cells by analyzing the scalp EEG by means of RBF technique. Objectives: To acquire the EEG signal from the various electrodes. The artificial neural network will be focused to split up the EEG signal whether cyst i.e. tumor or regular. Methods: The EEG signal is been acquired from the subject using EEG scalp electrodes. The various features such as mean, variance, co-variance, Eigen values and Eigen vectors are extracted from those signals using the Principal Component Analysis. Radial Basis Function (RBF) networks are feed-forward networks which uses a supervised training algorithm are used for function approximation, time series prediction and system control. The RBF is used to train and classify the signal whether the subject is normal or suffering from abnormalities. Results: The features are been extracted using the Principal Component Analysis and the features are skilled. Thus the acquired signals are been classified as cyst or normal. Conclusion: Thus in this paper an automatic system is been developed for diagnosing the tumor cells by means of analyzing EEG signal which is non-invasive method. It can also extend for analyzing other diseases seizures of epilepsy, Alzheimer's disease.

Keywords

EEG, Neural Network, Principal Component Analysis, Radial Basis Function

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S. Vinurajkumar ¹, V. Renuga ¹, K. Nithyakalyani ¹, K. Jeyanthi ¹, N. Malathy ², J. Sivaraman ¹

Affiliations
1 Department of Biomedical Engineering, Vel Tech Multitech, Chennai - 600062, Tamil Nadu, IN
2 Department of Electronics and Instrumentation Engineering, RMK Engineering College, Chennai - 601206, Tamil Nadu, IN

Abstract

Objectives: This study involves the measurement of obstructions in the blood flow of an arterial system. An attempt is made to find the correlation between the pressure and flow of the blood. Methods: The obstructed area produces vascular sounds which are acquired through disturbed blood flow patterns. The measurements are carried over by audio frequency analysis of the sound observed during arterial stenosis. These sounds can be measured using piezoelectric film sensor by placing it in the wrist and mid arm in the blood flow path. Results:The sounds that initiate in the narrowed arteries is measured by non-invasive, sensitive piezoelectric film sensor that captures the vibration caused by the flow of blood inside arteries and generate appropriate waveform for different flow conditions. Conclusion: The waveforms are analyzed in spectrum analyzer and compared with the normal flow patterns and if the values deviate from normal it is concluded for occlusion or clot that happened in the blood flow passage.

Keywords

Arterial Stenosis, Blood Flow, Occlusion, Piezoelectric Film Sensor

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S. Logesh Kumar ¹, M. Swathy ², S. Sathish ¹, J. Sivaraman ¹, M. Rajasekar ³

Affiliations
1 Department of Biomedical Engineering, Vel Tech Multitech, Chennai - 600062, Tamil Nadu, IN
2 Department of Biomedical Engineering, St. Peter’s University, Chennai - 600054, Tamil Nadu, IN
3 Department of Computer Science Engineering, Vel Tech Multitech, Chennai - 600062, Tamil Nadu, IN

Abstract

The detection of lung cancer through image processing is an important tool for diagnoses. Different methods were employed to detect the cancerous cell of a lung with image pre processing such as Gabor filter, image segmentation using watershed segmentation and feature extraction by using MATLAB. In this experiment, various Computed Tomography (CT) images of lung were used as input image and obtained the output image in JPEG format. The resultant output of this technique was evaluated. Based on the results, it shows that watershed segmentation technique is showed better results than other segmentation techniques for lung cancer cell identification.

Keywords

CT Lung Cancer Image, Image Segmentation, Thresholding Operation, Watershed Method

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K. Manikandan ¹, Logesh Kumar ¹, J. Sivaraman ¹, P. Padmapriya ¹, C. Vijayalakshmi ¹

Affiliations
1 Department of Biomedical Engineering, Vel Tech Multitech, Chennai - 600062, Tamil Nadu, IN

Abstract

Objective: The purpose of the study is to develop a system for measuring the pressure level at several points on the foot sole. Methodology: The pressure sensors placed on the pressure plate develops a voltage for the corresponding exerted pressure and the voltages are amplified to a considerable value and fed into the multiplexer for digitization by using A/D convertor for further processing. All the data are normalized to obtain an appropriate image. The image colour intensities indicate different pressure distributions of the foot. Findings: The diabetes patients are made to walk on the pressure device and the distributions of pressure are simulated with various color coding using Visual Basic (VB) and the range of pressure from minimum to maximum is validated. Applications/Improvements: The pressure distribution of a patient is found in the foot sole and an appropriate foot wear can be designed to avoid foot ulcers and other deformations.

Keywords

Capacitive Sensor, Contact Area, Diabetes, Pressure Level

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P. Vimal Prabhu ¹, J. Sivaraman ², S. Sathish ², S. Vinurajkumar ², K. Manikandan ¹

Affiliations
1 Department of Biomedical Engineering, Indian Institute of Technology, Hyderabad - 502285, Telangana, IN
2 Department of Biomedical Engineering, Vel Tech MultiTech, Chennai - 600062, Tamil Nadu, IN

Abstract

Objective: This study analyzes the dilation and constriction (elastic) properties of blood vessels using a non invasive Photoplethysmography method. The dilation and constriction of blood vessel changes as a function of aging which can be analyzed using the shape of Phototplethsymogram. Methods: A preliminary test is conducted in twenty sinus rhythm subjects in the range between 20 to 73 years. Findings: The parameters like peak ratio, time ratios, valley to peak ratio, stiffness index and augmentation index are the indices to determine the dilation and constriction properties of the blood vessels. Applications/Improvements: The above parameters are evaluated with the help of appropriate hardware and software. Neural networks is trained using these parameters to classify the level of elasticity, using which the abnormalities such as Atherosclerosis, aortic stenosis, aortic regurgitation can be diagnosed.

Keywords

Atherosclerosis, Dicrotic Notch, Peak Ratio, Photoplethysmography, Sinus Rhythm

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