Biomedical subjects

Narender P Reddy

Publications and source records attributed to Narender P Reddy.

3 recordsLinked to original sources

PubMed2006

Toward direct biocontrol using surface EMG signals: control of finger and wrist joint models.

Increased interest in virtual reality (VR) and telemanipulation has created a growing need for the development of new interfacing devices for measuring controlling actions of the human hand. The objective of the present study was to determine if surface electromyography signals (SEMG) from the flexor digitorum superficialis (FDS), and flexor carpi ulnaris (FCU) generated during flexion-extension of the human index finger and wrist can be used for controlling the flexion-extension of the finger and wrist of a simple geometric computer model. A simple geometric computer model of finger and wrist joints was developed. Eighteen subjects controlled the computer model using the SEMG signals from their FDS and FCU. The results indicate that the SEMG signals from the FDS and FCU muscles can be used as a direct biocontrol technique for controlling the finger and wrist models. This study establishes the proof of concept for direct biological control of the dynamic motion of the finger and wrist models for use in virtual reality environments and telemanipulation.

Computer Simulation↗

PubMed2005

Fractal analysis of acceleration signals from patients with CPPD, rheumatoid arthritis, and spondyloarthroparthy of the finger joint.

Arthritis is one of the leading causes of disability and affects a major segment of the population. Consequently, accurate diagnosis of arthritis is important. Arthritis due to calcium pyrophosphate deposition disease (CPPD), rheumatoid arthritis, and spondyloarthropathy, induce complex changes in the cartilage and the articular surface. The fractal dimension provides a measure of the complexity of a signal. Recently, we have developed non-invasive acceleration measurements to characterize the arthritic patients. The question remains if the fractal dimension of the acceleration signal is different for different arthritis conditions. The purpose of this study was to distinguish between different types of arthritis of the finger joint using the fractal dimension of the acceleration signal obtained from the finger joint of the arthritic patients. Acceleration signals were obtained from the finger joint of arthritis patients with rheumatoid arthritis, spondyloarthropathy, and calcium pyrophosphate deposition disease of the finger joint. ANOVA results showed that there were significant differences between the fractal dimension of acceleration signals from patients having calcium pyrophosphate deposition disease and rheumatoid arthritis and spondyloarthropathy. Fractal dimension of acceleration signals, in concert with other clinical symptoms, can be used to classify different types of arthritis.

Arthritis, Rheumatoid↗

PubMed2003

Speaker verification using committee neural networks.

Security is a major problem in web based access or remote access to data bases. In the present study, the technique of committee neural networks was developed for speech based speaker verification. Speech data from the designated speaker and several imposters were obtained. Several parameters were extracted in the time and frequency domains, and fed to neural networks. Several neural networks were trained and the five best performing networks were recruited into the committee. The committee decision was based on majority voting of the member networks. The committee opinion was evaluated with further testing data. The committee correctly identified the designated speaker in (50 out of 50) 100% of the cases and rejected imposters in (150 out of 150) 100% of the cases. The committee decision was not unanimous in majority of the cases tested.

Algorithms↗