Narender P. Reddy

Interstitial fluid flow as a factor in decubitus ulcer formation

Abstract Decubitus ulcers form as a result of prolonged excessive external pressure on soft tissue. The mechanisms of ulcer formation are poorly understood. In this preliminary study, the effects of external pressure on interstitial fluid dynamics are analysed, using a simple mathematical model. Calculations revealed that an inverse relationship exists, between the intensity and duration of external pressure required for the interstitial fluid volume in the pressurized region to reach a given portion of its initial volume, which is similar to the experimentally observed relationship between the intensity and duration of external pressure required to produce threshold damage. The preliminary analysis suggests that interstitial fluid flow may play an important role in the ulcer formation.

Fractal analysis of surface EMG signals from the biceps

Nonlinear analysis techniques are necessary to understand the complexity of the EMG. The purpose of the present study was to determine the fractal dimension of surface EMG obtained from the biceps brachii of normal subjects during isokinetic flexion-extension of the arm. The measurements were obtained with different loading conditions on the arm and for various rates of flexion-extension. Fractal dimensions of the surface EMG signals were calculated for each of these conditions. ANOVA results showed statistically significant differences between the fractal dimensions calculated for different loading conditions and rates of flexion-extensin (P < or = 0.005). Linear regression analysis showed a correlation coefficient of 0.99 between the fractal dimension and the load, and a correlation coefficient of 0.98 between the fractal dimension and the rate of flexion-extension. The results of the study show that the fractal dimension can be used along with other parameters to characterize the EMG signal.

Hybrid fuzzy logic committee neural networks for recognition of swallow acceleration signals

Biological signals are complex and often require intelligent systems for recognition of characteristic signals. In order to improve the reliability of the recognition or automated diagnostic systems, hybrid fuzzy logic committee neural networks were developed and the system was used for recognition of swallow acceleration signals from artifacts. Two sets of fuzzy logic-committee networks (FCN) each consisting of seven member networks were developed, trained and evaluated. The FCN-I was used to recognize dysphagic swallow from artifacts, and the second committee FCN-II was used to recognize normal swallow from artifacts. Several networks were trained and the best seven were recruited into each committee. Acceleration signals from the throat were bandpass filtered, and several parameters were extracted and fed to the fuzzy logic block of either FCN-I or FCN-II. The fuzzified membership values were fed to the committee of neural networks which provided the signal classification. A majority opinion of the member networks was used to arrive at the final decision. Evaluation results revealed that FCN correctly identified 16 out of 16 artifacts and 31 out of 33 dysphagic swallows. In two cases, the decision was ambiguous due to the lack of a majority opinion. FCN-II correctly identified 24 out of 24 normal swallows, and 28 out of 29 artifacts. In one case, the decision was ambiguous due to the lack of a majority opinion. The present hybrid intelligent system consisting of fuzzy logic and committee networks provides a reliable tool for recognition and classification of acceleration signals due to swallowing.

Mechanisms of decubitus ulcer formation — An hypothesis

Understanding of the etiology of decubitus ulcer formation is fragmentary and the existing literature contains much experimental data that are inconsistent with the idea that pressure sore formation is due extensively to depriving a tissue region of blood. In fact, there is substantial data that illustrate that tissue can remain viable for very extended lengths of time, up to 13 hours, when subjected to externally applied pressures that collapse the blood microvasculature in a region. Based on these observations and on studies done in this laboratory on lymph propulsion and pressure sore prevention, an hypothesis has been formulated that is consistent with the published data and with clinical observations. The hypothesis states that a major contributing factor to pressure sores is the tissue necrosis that is caused by the accumulation of anaerobic metabolic waste products due to occlusion of the lymph vessels.

Noninvasive acceleration measurements to characterize the pharyngeal phase of swallowing

Swallowing disorder (dysphagia) presents a major problem in the rehabilitation of stroke and head injured patients. In the present investigation, a new technique is developed for noninvasive assessment of the pharyngeal phase of the swallowing mechanism. Acceleration was measured with two ultra-miniature accelerometers placed on the skin over the throat. Simultaneously, the swallow suction pressure was monitored. Swallowing in normal individuals gave rise to a characteristic acceleration pattern which was quite reproducible, and was in phase with the swallow pressure. In dysphagic patients, the acceleration response was either absent or significantly delayed. The accelerometry technique provides a tool for continuing patient assessment and demonstrating the clinical improvements.

Measurements of acceleration during videofluorographic evaluation of dysphagic patients

Accelerometry represents a noninvasive technique for the assessment of the swallowing mechanism. However, the underlying physiological events that give rise to the acceleration signal are poorly understood. In the present study, the acceleration signal was measured simultaneously during videofluorography examination. Preliminary results revealed that the signal occurred during laryngeal elevation and the magnitude of acceleration correlated well with the laryngeal displacement. Acceleration measurements present a potentially useful noninvasive tool.

Biomechanical measurements to characterize the oral phase of dysphagia

Several biomechanical parameters that characterize the oral musculature are identified and techniques for quantifying these parameters in normal and dysphagic patients are discussed. These parameters include lip closure pressure, lip interface shear force, tongue thrust, and swallow pressure. Significant differences were found in each of these parameters measured in normal and dysphagic patients. The quantitative measurements can aid the physician in choosing the appropriate therapy during the course of rehabilitation of stroke and head injured patients.<<ETX>>

Neural network committees for finger joint angle estimation from surface EMG signals

BackgroundIn virtual reality (VR) systems, the users finger and hand positions are sensed and used to control the virtual environments. Direct biocontrol of VR environments using surface electromyography (SEMG) signals may be more synergistic and unconstraining to the user. The purpose of the present investigation was to develop a technique to predict the finger joint angle from the surface EMG measurements of the extensor muscle using neural network models.MethodologySEMG together with the actual joint angle measurements were obtained while the subject was performing flexion-extension rotation of the index finger at three speeds. Several neural networks were trained to predict the joint angle from the parameters extracted from the SEMG signals. The best networks were selected to form six committees. The neural network committees were evaluated using data from new subjects.ResultsThere was hysteresis in the measured SMEG signals during the flexion-extension cycle. However, neural network committees were able to predict the joint angle with reasonable accuracy. RMS errors ranged from 0.085 ± 0.036 for fast speed finger-extension to 0.147 ± 0.026 for slow speed finger extension, and from 0.098 ± 0.023 for the fast speed finger flexion to 0.163 ± 0.054 for slow speed finger flexion.ConclusionAlthough hysteresis was observed in the measured SEMG signals, the committees of neural networks were able to predict the finger joint angle from SEMG signals.

A computer model of the lymphatic system.

Abstract A mathematical model of the whole body lymphatic network, which simulates the lymph propulsion along the network from the periphery through the thoracic duct into the venous system, is developed using the fundamental conservation laws and current notions of lymphology. Only the major lymphatic vessels are considered. The set of mathematical equations are then translated into a series of FORTRAN statements for the purpose of digital computer simulation of the pressure and flow patterns along the network. The model analysis revealed interesting characteristics of lymphatic contractility at various points along the network.

A fuzzy logic diagnosis system for classification of pharyngeal dysphagia

Identification and classification of the dysphagic patient at risk of aspiration is important from a clinical point of view. Recently, we have developed techniques to quantify various biomechanical parameters that characterize the dysphagic patient, and have developed an expert system to classify patients based on these measurements. The purpose of the present investigation was to develop a fuzzy logic diagnosis system for classification of the patient with pharyngeal dysphagia into four categories of risk for aspiration. Non-invasive acceleration and swallow pressure measurements were obtained and five parameters were extracted from these measurements. A set of membership functions were defined for each parameter. The measured parameter values were fuzzified and fed to a rule base which provided a set of output membership values corresponding to each of the categories. The set of output values were defuzzified to obtain a continuous measure of classification. The fuzzy system was evaluated using the data obtained from 22 subjects. There was a complete agreement between the fuzzy system classification and the clinicians classification in 18 of the 22 patients. The fuzzy system overestimated the risk by half a category in two patients and underestimated by half a category in two patients. The fuzzy logic diagnosis system, together with the biomechanical measures, provides a tool for continued patient assessment on a daily basis to identify the patient who needs further videofluorography examination.