Biomedical subjects

J J Abbas

Publications and source records attributed to J J Abbas.

11 recordsLinked to original sources

PubMed2001

Real-time interaction between a neuromorphic electronic circuit and the spinal cord.

We present a novel demonstration of real-time dynamic interaction between an oscillatory spinal cord (isolated lamprey nervous system) and electronic hardware that mimics the spinal motor pattern generating circuitry. The spinal cord and the neuromorphic circuit were interfaced in unidirectional and bidirectional modes. Bidirectional coupling resulted in stable, persistent oscillations. This experimental platform offers a unique paradigm to examine the intrinsic dynamics of neural circuitry. The neuromorphic analog very large scale integration (aVLSI) design and real-time capabilities of this approach may provide a particularly powerful means of restoring complex neuromotor function using neuroprostheses.

Animals↗

PubMed2001

Adaptive control of cyclic movements as muscles fatigue using functional neuromuscular stimulation.

For individuals with spinal cord injuries, functional neuromuscular stimulation (FNS) systems can be used to activate paralyzed muscles in order to restore function, provide exercise, or assist in movement therapy. In previous work, the pattern generator/pattern shaper (PG/PS) adaptive controller was evaluated on subjects with spinal cord injuries and was able to automatically adjust stimulation parameters to account for individual subject differences and system response nonlinearities. In this study, the PG/PS control system was utilized in extended trials. Results indicated that the controller adapted stimulation patterns in an online manner to account for changes in system properties due to fatigue.

Adult↗

PubMed2000

Electrical stimulation: a societal perspective.

Societal perspective on functional electrical stimulation is colored by media influence, popular thought, and political climate as much as by the science that supports it. The purpose of this article is to examine how these influences facilitate or inhibit the application of electrical stimulation in today's world and to describe the challenges facing the use of electrical stimulation in the future. Emphasis will be placed on perceived need, cost, and available resources and how these factors must be addressed to utilize functional electrical stimulation successfully in society.

Attitude to Health↗

PubMed2000

Sensitivity and versatility of an adaptive system for controlling cyclic movements using functional neuromuscular stimulation.

This study evaluated an adaptive control system (the PG/PS control system [2]) that had been designed for generating cyclic movements using functional neuromuscular stimulation (FNS). Extensive simulations using computer-based models indicated that a broad range of control system parameter values performed well across a diverse population of model systems. The fact that manual tuning is not required for each individual makes this control system particularly attractive for implementation in FNS systems outside of research laboratories.

Algorithms↗

PubMed2000

Adaptive neural network control of cyclic movements using functional neuromuscular stimulation.

In this study, we evaluated the performance of an adaptive feedforward controller and its ability to automatically develop and customize stimulation patterns for use in functional neuromuscular stimulation (FNS) systems. Results from previous experiments using the pattern generator/pattern shaper (PG/PS) controller to generate isometric contractions demonstrated its ability to adjust stimulation patterns to account for recruitment nonlinearities and muscle dynamics. In this study, the PG/PS controller was tested under isotonic conditions. This evaluation required the PG/PS controller to account for muscle length-tension and force-velocity properties as well as limb dynamics. The performance of the adaptive controller was also compared with that of a proportional-derivative (PD) feedback controller. The PG/PS controller is composed of a neural network system that adaptively filters a periodic signal to produce a muscle stimulation pattern for generating cyclic movements. We used computer-simulated models to determine controller parameters for the PG/PS and PD controller that perform well across a variety of musculoskeletal systems. The controllers were then experimentally evaluated on both legs of two subjects with spinal cord injury. Results indicated that the PG/PS controller was able to achieve and maintain better tracking performance than the PD controller. This study indicates that the PG/PS control system may provide an effective mechanism for automatically customizing stimulation patterns for individuals using FNS systems.

Algorithms↗

PubMed1999

Brain-spinal cord interactions stabilize the locomotor rhythm to an external perturbation.

Motor networks within the spinal cord of vertebrates are capable of generating rhythmic locomotor output even in the absence of phasic sensory input. In an intact animal these spinal pattern generators are affected by descending inputs from the brain and by sensory inputs. The role of the feedforward-feedback (FF-FB) loops between the brain and the spinal cord in the control of locomotion are not well understood. We hypothesized that the dynamic interaction between the brain and the spinal cord would affect the response of the neural system to external perturbation. We investigated this hypothesis in an in-vitro brain-spinal cord fictive locomotion preparation of a primitive vertebrate, lamprey. In tandem, we analyzed the behavior of a neural network model representing the brain and multiple segments of the spinal cord. Our experimental results indicate that with intact FF-FB loops, phase locked entrainment of the spinal motor activity can be obtained on direct stimulation of the spinal cord. However, the effect is localized with minimal influence on distal spinal segments. The intersegmental coupling strength is strong as indicated by a fast recovery of the perturbed rhythm to the natural frequency on termination of the perturbation. With the FF-FB loop interrupted, the perturbation was capable of altering the motor activity from multiple sites in the spinal cord. Also, upon termination of the perturbation there was a prolonged period before recovery of the original natural frequency. Model analyses support our interpretation of the experimental results. In the neural network model with the brain-spinal cord loops closed there was a localized effect on the oscillatory rhythm and strong intersegmental coupling. Also, the analysis indicated the presence of a smaller entrainment range and many more periodic orbits than with the loops open. The results suggest that the increased variability in the locomotor rhythm and decreased sensitivity to perturbation observed in the presence of intact brain spinal cord connections may be a reflection of a higher dimensional system with many periodic orbits. The higher dimension could allow the system to collectively remain within the attractor space of one of these periodic orbits and thus remain resilient to perturbation.

Animals↗

PubMed1997

Experimental evaluation of an adaptive feedforward controller for use in functional neuromuscular stimulation systems.

An adaptive feedforward control system has been evaluated for use in functional neuromuscular stimulation (FNS) systems. The control system, which utilizes neural network techniques, was used to generate isometric muscle contractions to track a periodic torque trajectory signal. The evaluation of the control system was performed using percutaneous intramuscular electrodes to stimulate the quadriceps muscles of spinal cord injured adolescents. Results of the evaluation indicate that the control system automatically customized its parameters for controlling isometric muscle torque in a particular muscle and that the parameters were adapted on-line to account for changes in muscle properties due to fatigue. This study demonstrates that this control system may play an important role in the development of practical FNS systems that are capable of automatically adjusting stimulation parameters to fit the needs of a particular individual at a given time.

Adaptation, Physiological↗

PubMed1997

Evaluation of FNS control systems: software development and sensor characterization.

Functional Neuromuscular Stimulation (FNS) systems activate paralyzed limbs by electrically stimulating motor neurons. These systems have been used to restore functions such as standing and stepping in people with thoracic level spinal cord injury. Research in our laboratory is directed at the design and evaluation of the control algorithms for generating posture and movement. This paper describes software developed for implementing FNS control systems and the characterization of a sensor system used to implement and evaluate controllers in the laboratory. In order to assess FNS control algorithms, we have developed a versatile software package using Lab VIEW (National Instruments, Corp). This package provides the ability to interface with sensor systems via serial port or A/D board, implement data processing and real-time control algorithms, and interface with neuromuscular stimulation devices. In our laboratory, we use the Flock of Birds (Ascension Technology Corp.) motion tracking sensor system to monitor limb segment position and orientation (6 degrees of freedom). Errors in the sensor system have been characterized and nonlinear polynomial models have been developed to account for these errors. With this compensation, the error in the distance measurement is reduced by 90 % so that the maximum error is less than 1 cm.

Computer Systems↗

PubMed1996

New control strategies for neuroprosthetic systems.

The availability of techniques to artificially excite paralyzed muscles opens enormous potential for restoring both upper and lower extremity movements with neuroprostheses. Neuroprostheses must stimulate muscle, and control and regulate the artificial movements produced. Control methods to accomplish these tasks include feedforward (open-loop), feedback, and adaptive control. Feedforward control requires a great deal of information about the biomechanical behavior of the limb. For the upper extremity, an artificial motor program was developed to provide such movement program input to a neuroprosthesis. In lower extremity control, one group achieved their best results by attempting to meet naturally perceived gait objectives rather than to follow an exact joint angle trajectory. Adaptive feedforward control, as implemented in the cycle-to-cycle controller, gave good compensation for the gradual decrease in performance observed with open-loop control. A neural network controller was able to control its system to customize stimulation parameters in order to generate a desired output trajectory in a given individual and to maintain tracking performance in the presence of muscle fatigue. The authors believe that practical FNS control systems must exhibit many of these features of neurophysiological systems.

Electric Stimulation Therapy↗

PubMed1995

Neural network control of functional neuromuscular stimulation systems: computer simulation studies.

A neural network control system has been designed for the control of cyclic movements in Functional Neuromuscular Stimulation (FNS) systems. The design directly addresses three major problems in FNS control systems: customization of control system parameters for a particular individual, adaptation during operation to account for changes in the musculoskeletal system, and attaining resistance to mechanical disturbances. The control system was implemented by a two-stage neural network that utilizes a combination of adaptive feedforward and feedback control techniques. A new learning algorithm was developed to provide rapid customization and adaptation. The control system was evaluated in a series of studies on a computer simulated musculoskeletal model. The model of electrically stimulated muscle used in the study included nonlinear recruitment, linear dynamics, and multiplicative nonlinear torque-angle and torque-velocity scaling factors. The skeletal model consisted of a one-segment planar system with passive constraints on joint movement. Results of the evaluation have demonstrated that the control system can provide automated customization of the feedforward controller parameters for a given musculoskeletal system. It can account for changes in the musculoskeletal system by adapting the feedforward controller parameters on-line and it can resist the effects of mechanical disturbances. These results suggest that this design may be suitable for the control of FNS systems and other dynamic systems.

Adaptation, Physiological↗

PubMed1991

Feedback control of coronal plane hip angle in paraplegic subjects using functional neuromuscular stimulation.

This paper reports on an investigation of feedback control of coronal plane posture in paraplegic subjects who stand using functional neuromuscular stimulation (FNS). A feedback control system directed at regulating coronal plane hip angle in neutral position was designed, implemented, and evaluated in two paraplegic subjects. The control system included sensor mounting and signal processing techniques, a two-stage feedback controller, stimulation hardware, and a set of percutaneous intramuscular electrodes. The feedback controller consisted of two-stages in cascade: a modified discrete-time proportional-integral-derivative (PID) stage and a nonlinear single-input, multiple-output stage to determine the stimulation to be sent to several muscles. The focus of this work was on evaluating the performance of the feedback controller by comparing the response of the feedback-controlled system to that of an open-loop stimulation system. In an evaluation based on temporal response characteristics the controlled system exhibited a 41% reduction in root-mean-squared (rms) error (where error is defined as the deviation from the desired angle), a 52% reduction in steady-state error, and a 22% reduction in hip compliance. In addition, the feedback-controlled system exhibited significant reductions in variability of these measures on several days. These results demonstrate the ability of the feedback controller to improve the temporal response characteristics of the FNS control system.

Diagnosis, Computer-Assisted↗