Techniques of EMG signal analysis: detection, processing, classification and applications

Electromyography (EMG) signals can be used for clinical/biomedical applications, Evolvable Hardware Chip (EHW) development, and modern human computer interaction. EMG signals acquired from muscles require advanced methods for detection, decomposition, processing, and classification. The purpose of this paper is to illustrate the various methodologies and algorithms for EMG signal analysis to provide efficient and effective ways of understanding the signal and its nature. We further point up some of the hardware implementations using EMG focusing on applications related to prosthetic hand control, grasp recognition, and human computer interaction. A comparison study is also given to show performance of various EMG signal analysis methods. This paper provides researchers a good understanding of EMG signal and its analysis procedures. This knowledge will help them develop more powerful, flexible, and efficient applications

Wireless Ultrasound Video Transmission for Stroke Risk Assessment: Quality Metrics and System Design

In this paper we discuss the use of clinical quality criteria in the assessment and design of ultrasound video compression systems. Our goal is to design efficient systems that can be used to transmit quality ultrasound videos at the lowest possible bitrates. This led us to the development of a spatially- varying encoding scheme, where quantization levels are spatially varying as a function of the diagnostic significance of the video. Diagnostic Regions of Interest (ROIs) for carotid ultrasound medical video are defined, which are then used as input for Flexible Macroblock Ordering (FMO) slice encoding. Diagnostically relevant FMO slice encoding is attained by enabling variable quality slice encoding, tightly coupled by each region's diagnostic importance. Redundant Slices (RS) utilization increases compressed video's resilience over error prone transmission mediums. We present preliminary findings on three carotid ultrasound videos at CIF resolution, for packet loss rates up to 30%. Subjective quality evaluation incorporates a clinical rating system that provides for independent evaluations of the different parts of the video. Experimental results show that encoded videos attain enhanced diagnostic performance under noisy environments, while at the same time achieving significant bandwidth requirements reductions

Chemistry Central Journal Poster presentation Multi-objective de novo drug design using evolutionary graphs

© 2008 Nicolaou and Pattichis Drug discovery and development is a complex, lengthy process and failure of a candidate molecule can occur as a result of a combination of reasons, such as poor pharmacokinetics, lack of efficacy or toxicity. Drugs compromise the numerous, sometimes competing objectives so that the benefits to patients outweigh potential drawbacks and risks [1]. De novo drug design, involves searching an immense space of feasible, drug-like molecules to select those with the highest chances of becoming drugs using computational technology [2]. Traditionally, de novo design has focused on designing molecules satisfying a single objective, such as a similarity value to a known ligand or a virtual screening score, and ignored the presence of the multiple objectives required for drug-like behavior

Chemistry Central Journal Poster presentation Knowledge-driven multi-objective de novo drug design

© 2009 Nicolaou et al; licensee BioMed Central Ltd. Drug discovery is an inherently multi-objective process since drugs need to satisfy not only activity requirements but also a range of other properties such as selectivity and toxicity. However, drug discovery process practices, including both experimental and computational methods, commonly ignore this fact and focus on a single pharmaceutical objective at a time. De novo design, the branch of chemoinformatics addressing the in silico design of ligands from scratch, follows a similar approach typically focusing on a single objective, such as an interaction score to a target receptor or similarity to a known drug [1]. Recently, methods have appeared in the literature that attempt to design molecules satisfying multiple predefined objectives [2]. Motivated from the initial success o