Title: Performance index assessment of intelligent computing methods in EMG-based neuromuscular diseases
Authors: Babita Pandey; R.B. Mishra
Addresses: Department of Computer Science and Engineering, School of Computing and Information Technology, Lovely Professional University, Block-34, Phagwara, Panjab 144402, India ' Department of Computer Engineering, Information Technology, Banaras Hindu University, UP 221005, India
Abstract: In the medical systems, there is a lack of determining and assessing the performance measure of the intelligent computing methods (ICM) deployed in the diagnosis of bioelectric signals (EEG/EMG/ECG)-based diseases. There have been few attempts for performance measure of mathematical models in medical computing. In this paper, we have developed a heuristic method for the assessment of performance measure in the diagnosis of EMG-based neuromuscular diseases. Firstly, we review the various ICM then we perform qualitative assessment of mathematical, algorithmic and heuristic content, data acquisition cost as well as medical consultancy cost of various parameter of EMG and non-EMG (psychological, cognitive and muscular). The computational overhead (CO) of EMG parameters, overall computational overhead (OCO) and clinical consultancy cost (CC) are determined. Finally, performance index (PI) is computed based on the two overheads and clinical cost. A graph showing the comparative view of CO of EMG parameters, OCO and CC is plotted and PI is shown for all the methods.
Keywords: neuromuscular diseases; intelligent computing; system complexity assessment; general complexity assessment; GCA; computational overheads; performance index; performance measures; mathematical modeling; electromyography; EMG; clinical consultancy costs.
International Journal of Knowledge Engineering and Soft Data Paradigms, 2013 Vol.4 No.1, pp.42 - 71
Available online: 18 Mar 2013Full-text access for editors Access for subscribers Purchase this article Comment on this article