A new graph-theoretic approach to determine the similarity of genome sequences based on nucleotide triplets.

Methods of finding sequence similarity play a significant role in computational biology. Owing to the rapid increase of genome sequences in public databases, the evolutionary relationship of species becomes more challenging. But traditional alignment-based methods are found inappropriate due to their time-consuming nature.

Genome sequence comparison under a new form of tri-nucleotide representation based on bio-chemical properties of nucleotides.

Genetic sequence analysis, classification of genome sequence and evolutionary relationship between species using their biological sequences, are the emerging research domain in Bioinformatics. Several methods have already been applied to DNA sequence comparison under tri-nucleotide representation. In this paper, a new form of tri-nucleotide representation is proposed for sequence comparison.

Optimal choice of k-mer in composition vector method for genome sequence comparison.

Several proteins and genes are members of families that share a public evolutionary. In order to outline the evolutionary relationships and to recognize conserved patterns, sequence comparison becomes an emerging process. The current work investigates critically the k-mer role in composition vector method for comparing genome sequences.

Analyzing text recognition from tactually evoked EEG.

Tactual exploration of objects produce specific patterns in the human brain and hence objects can be recognized by analyzing brain signals during tactile exploration. The present work aims at analyzing EEG signals online for recognition of embossed texts by tactual exploration. EEG signals are acquired from the parietal region over the somatosensory cortex of blindfolded healthy subjects while they tactually explored embossed texts, including symbols, numbers, and alphabets.

A Generic Transferable EEG Decoder for Online Detection of Error Potential in Target Selection.

Reliable detection of error from electroencephalography (EEG) signals as feedback while performing a discrete target selection task across sessions and subjects has a huge scope in real-time rehabilitative application of Brain-computer Interfacing (BCI). Error Related Potentials (ErrP) are EEG signals which occur when the participant observes an erroneous feedback from the system. ErrP holds significance in such closed-loop system, as BCI is prone to error and we need an effective method of systematic error detection as feedback for correction.

Vibrotactile feedback for conveying object shape information as perceived by artificial sensing of robotic arm.

This work is a preliminary study towards developing an alternative communication channel for conveying shape information to aid in recognition of items when tactile perception is hindered. Tactile data, acquired during object exploration by sensor fitted robot arm, are processed to recognize four basic geometric shapes. Patterns representing each shape, classified from tactile data, are generated using micro-controller-driven vibration motors which vibrotactually stimulate users to convey the particular shape information.

Bypassing the Natural Visual-Motor Pathway to Execute Complex Movement Related Tasks Using Interval Type-2 Fuzzy Sets.

In visual-motor coordination, the human brain processes visual stimuli representative of complex motion-related tasks at the occipital lobe to generate the necessary neuronal signals for the parietal and pre-frontal lobes, which in turn generates movement related plans to excite the motor cortex to execute the actual tasks. The paper introduces a novel approach to provide rehabilitative support to patients suffering from neurological damage in their pre-frontal, parietal and/or motor cortex regions. An attempt to bypass the natural visual-motor pathway is undertaken using interval type-2 fuzzy sets to generate the approximate EEG response of the damaged pre-frontal/parietal/motor cortex from the occipital EEG signals.

Texture- and deformability-based surface recognition by tactile image analysis.

Deformability and texture are two unique object characteristics which are essential for appropriate surface recognition by tactile exploration. Tactile sensation is required to be incorporated in artificial arms for rehabilitative and other human-computer interface applications to achieve efficient and human-like manoeuvring. To accomplish the same, surface recognition by tactile data analysis is one of the prerequisites.

Synthesis of gelatin nano/submicron particles by binary nonsolvent aided coacervation (BNAC) method.

A newly developed modified coacervation method is utilized to synthesize gelatin nano/submicron particles (GN/SPs) as a drug carrier. Binary nonsolvent aided coacervation (BNAC) method is a modified single step coacervation method, which has yielded approximately a threefold lower particle size and higher average yield in terms of weight percentage of around 94% in comparison to the conventional phase separation methods. In this study 0.

Motor imagery, P300 and error-related EEG-based robot arm movement control for rehabilitation purpose.

The paper proposes a novel approach toward EEG-driven position control of a robot arm by utilizing motor imagery, P300 and error-related potentials (ErRP) to align the robot arm with desired target position. In the proposed scheme, the users generate motor imagery signals to control the motion of the robot arm. The P300 waveforms are detected when the user intends to stop the motion of the robot on reaching the goal position.

Object-shape recognition and 3D reconstruction from tactile sensor images.

This article presents a novel approach of edged and edgeless object-shape recognition and 3D reconstruction from gradient-based analysis of tactile images. We recognize an object's shape by visualizing a surface topology in our mind while grasping the object in our palm and also taking help from our past experience of exploring similar kind of objects. The proposed hybrid recognition strategy works in similar way in two stages.

Automatic feature selection of motor imagery EEG signals using differential evolution and learning automata.

Brain-computer interfacing (BCI) has been the most researched technology in neuroprosthesis in the last two decades. Feature extractors and classifiers play an important role in BCI research for the generation of suitable control signals to drive an assistive device. Due to the high dimensionality of feature vectors in practical BCI systems, implantation of efficient feature selection algorithms has been an integral area of research in the past decade.

Investigation of in vitro iontophoresis facilitated transdermal delivery of glycine.

The research presented in this paper discusses the potential of iontophoresis facilitated transdermal delivery of glycine. Iontophoresis has been widely investigated as a noninvasive transdermal drug delivery system. Iontophoresis is the use of a low electric current to carry ionized as well as unionized drug molecules across tissues (like skin) in a noninvasive technique.

Pattern recognition in tachographic gait records of normal and lower extremity handicapped human subjects.

The electromechanical behaviour of the tachographic gait recording system developed by earlier research scientists was analysed. Some alterations were incorporated and the resulting modified system was used to record the gait of 25 normal, healthy, able-bodied adult males with sedentary habits, and 67 subjects having different types of lower extremity handicap. Some of the findings obtained from analysis of these gait records are reported in this paper.

Static weight-bearing patterns of below-knee amputees using patellar-tendon-bearing prostheses.

While the weight-bearing patterns under human feet during dynamic conditions (i.e. walking or running) have been investigated by many scientists, only a few studies have been reported on such patterns during erect standing posture.

An integrated biomechanical-bioenergetic technique for evaluation of human locomotion.

The existing locomotion evaluation techniques are based either on bioenergetic measurements or on biomechanical principles and procedures. While the former basis has been preferred by a few, published literature in this field has contained more information on the latter. No significant work combining both the approaches in a single measurement system is known so far.

An improved approach for performance evaluation in lower extremity involvement.

An investigation has been carried out to confirm the relationship between heart rate and energy expenditure in case of normal and lower extremity handicapped persons and, to explore the difference, if any, between both the relationships. Studies have been made on 8 below-knee amputees fitted with patellar-tendon-bearing (PTB) prostheses and 10 normal subjects, taken as two separate groups and also, on 1 below-knee amputee and 1 control subject as individuals. It has been found that a significant difference exists between both the relationships and hence, separate heart rate-energy expenditure relationship is needed to evaluate the performance of lower extremity handicapped in clinics and in industry without going into the cumbersome, clumsy and time consuming methods of estimating physiological cost.

Use of a gait abnormality index for locomotion efficiency evaluation.

A number of gait curves obtained from 16 healthy, able-bodied adult males were selected as "normal" gait curves and thereafter analysed with a view to defining a "Gait Abnormality Index", which may be used as quantitative measure of human performance in locomotion. Similar studies on five groups of handicapped subjects, each group having 8 to 10 subjects with a particular type of handicap, indicate the suitability of this index for application in locomotion efficiency evaluation.