NUST Institutions Library Catalogue Search for 'kw,wrdl: (su-br:"Biomedical Technology.")'

Introduction to biomedical equipment technology

By Joseph J.Carr. New Delhi : Pearson Education Pte. Ltd 2001 . xv, 743 p. : , Includes bibliographical references and index 25 cm.. 8178083272

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Advanced Biomaterials : Fundamentals, Processing, and Applications /

Hoboken, N.J. : | [Westerville, Ohio] : John Wiley & Sons ; | The American Ceramic Society, 2009 . xxii, 746 p., [8] p. of plates : , This volume is an outcome of the International Conference on Design of Biomaterials, organised at Indian Institute of Technology Kanpur, India during 8-11th December, 2006. 25 cm.. 9780470193402 (cloth) | 0470193409 (cloth)

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Laser Material Processing

By Steen, William M.. 9781849960618

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Handbook of Biomedical Instrumentation

By Khandpur. New York : | Maidenhead : McGraw-Hill Professional Publishing | McGraw-Hill Education [Distributor] 2015 9789339205430 | 933920543X (Trade Paper)

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Biomedical Engineering (E-Book)

By Carlos Alexandre Barros de Mello. India In-Teh 2009 . x,658 P;

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Recent Advances in Biomedical Engineering (E-Book)

By Dr Ganesh R Naik. India In-Teh 2009 . xii,660 P;

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Bio-nanotechnology : a revolution in food, biomedical, and health sciences /

Chichester, West Sussex ; | Ames, Iowa : Wiley-Blackwell, 2013 . xvii, 803 p., [32] p. of plates : , H.B 26 cm.. 9780470670378 (hardback : alk. paper) | 0470670371 (hardback : alk. paper)

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Analyzing and Decoding Natural Reach & Grasp Action Using Convolutional Neural Network /

By Nazir, Abida . . 44p. , Reaching and Grasping is most signi cant component of human life.Translation of EEG in the form of upper limb movement is of great importance for realization of natural neuroprosthesis control and restoration of hand movements of patients with motor disorders. Patients su ering from spinal cord injury (SCI)problems have lost most of voluntary motor control functions. Such type of loss can be cured using movement related cortical potentials (MRCPS) analysis. Brain computer interface with limb neuro-prosthesis is considered as a solution to such problems. This study anlyzes EEG signals in relation with natural reach and grasp actions. EEG signals have movement related cortical potentials (MRCPS) which can be used to decode upper limb movements. This experiment was performed in Graz University of Technology Austria and they o ered free access dataset for further exploration.Total 45 subjects were involved in this study, 15 subjects with every type of electrode:gel,water and dry performed the experiment. All subjects accomplished self-initiated 80 reach and grasp actions toward a spoon within the jar (lateral grasp) and toward an empty glass (palmar grasp).EEG signals are recorded using three types of electrodes: water based, Gel based and Dry electrodes. In this study signals are classi ed using Deep learning technique i.e Convulotional Neural Networks. For analysis, EEG signals were preprocessed using various lteration techniques. After ltration data is fed into classi er for classi cation of signals. Data is divided into test set and training set. Grand average peak accuracy calculated on unseen test data resulted in 54.2% classi cation accuracy i.e Gel based accuracy approached 56.8.4%, water based 52.7% and dry based 51.8%. 30cm.

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Adaptive Hemodynamic Signal Estimation Using Kalman Estimator /

By Quddusi, Basiq Warrad . . 80p. , Functional Near Infrared Spectroscopy (fNIRS) is a technology that measures changes in the oxygenation level of blood present in brain whenever an activity is performed by human being. It is a non-invasive technique and uses near infrared light to detect changes in the concentration of two chromophores i.e., oxygenated and deoxygenated haemoglobin. During the recording, information related to neural activity in fNIRS signals gets compromised. This is due to the interference of noises from the environment outside as well as inside the human body. External noises can be light in the room and powerline noise. Internal noises are physiological noises such as cardiac, respiratory and mayer waves. Therefore, during analysis, it is required to remove these noises first and then extract main activity signal i.e., hemodynamic signal. Many techniques and methods have been proposed and practiced up to this date. Among them the most popular technique is General Linear Modelling (GLM). GLM models the signal by breaking it down into sum of all components present in the signal along with an error term. Previous studies and research that have used GLM for the reconstruction of activity signal used single frequency value for each noise but in reality, the frequency for each noise varies with the level of activity performed by the subject. This can lead to less accurate reconstruction of activity signal. In this study, this problem is kept under consideration and a method is developed to keep account for all the values of frequency that can corrupt fNIRS signal. Ranges of frequencies are considered instead of single values. These frequency ranges are first extracted using Continuous Wavelet Transform (CWT) and their possible magnitudes are estimated using Kalman filter. Similarly, activity signal is extracted from fNIRS signal using Discrete Wavelet Transform (DWT) and then its magnitude is estimated using Kalman filter. Output of these two steps is fed to GLM for reconstruction of possible hemodynamic signal. Results from this method are compared with the results of conventional GLM and significant improvement is observed both visually and statistically. 30cm,.

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Omics technologies and bio-engineering : towards improving quality of life /

. xvii, 625 pages : 25 cm. 9780128046593 | 0128046597

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Omics technologies and bio-engineering : towards improving quality of life /

. xvii, 625 pages : 25 cm. 9780128046593 | 0128046597

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