Ganesh R. Naik

Ganesh R. Naik received B.E. degree in Electronics and Communication Engineering from the University of Mysore, India, in 1997. He received his M.E. degree in Communication and Information Engineering from Griffith University, Brisbane, Australia, in 2002, and the PhD degree in the area of Electronics Engineering, specialised in Biomedical Engineering and Signal processing from RMIT University, Melbourne, Australia, in 2009. He is currently Chancellor's Post Doctoral Research Fellow at Faculty of Engineering and Information Technology (FEIT), UTS. As an early career researcher, he has edited 9 books, authored more than 80 papers in peer reviewed journals, conferences, and book chapters over the last five years. His research interests include EMG signal processing, Pattern recognition, Blind Source Separation (BSS) techniques, Biomedical signal processing, Human Computer Interface (HCI) and Audio signal processing. Currently he serves as an associate editor for two Springer journals (Circuits, Systems, and Signal Processing and Australasian Physical & Engineering Sciences in Medicine). He is also a reviewer and member of editorial board in several reputed journals. He is a recipient of the Baden–Württemberg Scholarship from the University of Berufsakademie, Stuttgart, Germany (2006–2007). In 2010, Dr. Naik is awarded with ISSI overseas fellowship from skilled Institute Victoria, Australia.

Publications

Facial Muscle Activity Patterns for Recognition of Utterances in Native and Foreign Language: Testing for its Reliability and Flexibility
Facial Muscle Activity Patterns for Recognition of Utterances in Native and Foreign Language: Testing for its Reliability and Flexibility
Sridhar Arjunan, Dinesh Kant Kumar, Hans Weghorn, Ganesh Naik. © 2014. 19 pages.
The need for developing reliable and flexible human computer interface is increased and applications of HCI have been in each and every field. Human factors play an important...
Applications, Challenges, and Advancements in Electromyography Signal Processing
Applications, Challenges, and Advancements in Electromyography Signal Processing
Ganesh R. Naik. © 2014. 404 pages.
Electromyography (EMG) is a procedure for assessing and recording the electrical activity produced by skeletal muscles. Since the contracting skeletal muscles are greatly...
Emerging Theory and Practice in Neuroprosthetics
Emerging Theory and Practice in Neuroprosthetics
Ganesh R. Naik, Yina Guo. © 2014. 377 pages.
Neuroprosthetics is a fast-growing area that brings together the fields of biomedical engineering and neuroscience as a means to interface the neural system directly to...
Neuroprosthetics: Introduction
Neuroprosthetics: Introduction
Ganesh R. Naik. © 2014. 7 pages.
Neuroprostheses use electric stimuli to stimulate neural structures, muscles, or receptors in order to support, augment, or partly restore the respective disordered or lost...
ICA as Pattern Recognition Technique for Gesture Identification: A Study Using Bio-Signal
ICA as Pattern Recognition Technique for Gesture Identification: A Study Using Bio-Signal
Ganesh Naik, Dinesh Kant Kumar, Sridhar Arjunan. © 2013. 20 pages.
In recent times there is an urgent need for a simple yet robust system to identify natural hand actions and gestures for controlling prostheses and other computer assisted...
Facial Muscle Activity Patterns for Recognition of Utterances in Native and Foreign Language: Testing for its Reliability and Flexibility
Facial Muscle Activity Patterns for Recognition of Utterances in Native and Foreign Language: Testing for its Reliability and Flexibility
Sridhar Arjunan, Dinesh Kant Kumar, Hans Weghorn, Ganesh Naik. © 2012. 20 pages.
The need for developing reliable and flexible human computer interface is increased and applications of HCI have been in each and every field. Human factors play an important...
ICA as Pattern Recognition Technique for Gesture Identification: A Study Using Bio-Signal
ICA as Pattern Recognition Technique for Gesture Identification: A Study Using Bio-Signal
Ganesh Naik, Dinesh Kant Kumar, Sridhar Arjunan. © 2012. 21 pages.
In recent times there is an urgent need for a simple yet robust system to identify natural hand actions and gestures for controlling prostheses and other computer assisted...
Semi Blind Source Separation for Application in Machine Learning
Semi Blind Source Separation for Application in Machine Learning
Ganesh Naik, Dinesh Kant Kumar. © 2012. 17 pages.
Unsupervised learning is a class of problems in machine learning which seeks to determine how the data are organized. Unsupervised learning encompasses many other techniques that...