Closed-Loop Control of Force During Electrical Stimulation of Muscle

The control of contractions elicited by electrical stimulation of muscle could be improved if there was a linear repeatable input-output relationship. The input is the command to the controlled stimulator and the output is the evoked contraction. Systems employing closed-loop force feedback to provide regulation of contractions were investigated in these studies. Force was modulated by both recruitment and temporal summation during intramuscular stimulation. Closed-loop systems with combined proportional and integral control were found to be stable and linear and to have good compensation for variations in muscle properties. A low proportional loop gain (approximately unity) was found necessary to prevent oscillation when modulating recruitment. Ratios of integral to proportional gain of about 10 gave the fastest response without compromising stability. The response time of the closed-loop system was as fast as or faster than the open-loop system.     

An EMG Feedback Control Functional Electrical Stimulation Cycling System

The prevalence of stroke and its residual disability is getting higher and higher in the whole world population. The functional electrical stimulation cycling system (FES-CS) is useful for hemiplegic patients to make the muscles of stroke patients be under hybrid activation. The raw electromyography (EMG) takes down the residual muscle force of stroke subjects; and the peak-to-peak of stimulus EMG indicates the force enhancement benefiting from electrical stimulation. This research proposed an EMG feedback control protocol of FES-CS, which includes a physiological signal recorder, a FPGA control module, DAC and electrical stimulation circuits. Using the strength of real-time EMG signal obtained from patients as a feedback to control the stimulation output intensity of FES cycling system.     

Closed-loop control of ankle position using muscle afferentfeedback with functional neuromuscular stimulation

Describes a closed-loop functional neuromuscular stimulation system that uses afferent neural activity from muscle spindle fibers as feedback for controlling position of the ankle joint. Ankle extension against a load was effected by neural stimulation through a dual channel intrafascicular electrode of a fascicle of the tibial nerve that innervated the gastrocnemius muscle. Ankle joint angle was estimated from recordings of tibialis anterior and lateral gastrocnemius spindle fiber activity made with dual channel intrafascicular electrodes. Experiments were conducted in neurally intact anesthetized cats and in unanesthetized decerebrate cats to demonstrate the feasibility of this system. The system was able to reach and maintain a fixed target ankle position in the presence of a varying external moment ranging in magnitude between 7.3 and 22 N-cm opposing the action of the ankle extensor, as well as track a sinusoidal target ankle position up to a frequency of 1 Hz in the presence of a constant magnitude 22- or 37-N-cm external moment     

Suppression of stimulation artifacts from myoelectric-evokedpotential recordings

A system that allows detection of single and double differential surface myoelectric signals during electrical stimulation of either the nerve or the muscle motor point, using surface electrodes, is described. The input referred stimulation artifact is limited to less than 24 μV _pp by a switching constant current/constant voltage output stage, slew rate limiting, and time windowing of the detected signal. The system is suitable for muscle crosstalk and for muscle fatigue investigation during functional electrical stimulation, in addition to measuring muscle or nerve conduction velocity     

Sliding mode closed-loop control of FES: controlling the shank movement

Functional electrical stimulation (FES) enables restoration of movement in individuals with spinal cord injury. FES-based devices use electric current pulses to stimulate and excite the intact peripheral nerves. They produce muscle contractions, generate joint torques, and thus, joint movements. Since the underlying neuromuscular-skeletal system is highly nonlinear and time-varying, feedback control is necessary for accurate control of the generated movement. However, classical feedback/closed-loop control algorithms have so far failed to provide satisfactory performance and were not able to guarantee stability of the closed-loop system. Because of this, only open-loop controlled FES devices are in clinical use in spite of their limitations. The purpose of the reported research was to design a novel closed-loop FES controller that achieves good tracking performance and guarantees closed-loop stability. Such a controller was designed based on a mathematical neuromuscular-skeletal model and is founded on a sliding mode control theory. The controller was used to control shank movement and was tested in computer simulations as well as in actual experiments on healthy and spinal cord injured subjects. It demonstrated good robustness, stability, and tracking performance properties.     

Assessment of closed-loop ventilatory stability in obstructive sleep apnea

Previous studies on ventilatory control in obstructive sleep apnea (OSA) have generally indicated depressed chemosensitivity, implying greater stability of the chemical control of breathing in these subjects. However, these results were based on tests involving steady-state or quasi-steady measurements obtained in wakefulness. We have developed a method for assessing the dynamic stability characteristics of chemoreflex control in OSA patients during sleep. While continuous positive airway pressure was applied to stabilize the upper airways, acoustically stimulated arousals were used to perturb the respiratory system during sleep. The fluctuations in esophageal pressure that ensued were analyzed, using a closed-loop minimal model, to estimate the chemoreflex loop impulse response (CLIR). Tests using simulated data confirmed the validity of our estimation algorithm. Application of the method to arousal responses measured in six OSA and five normal subjects revealed no statistically significant differences in gain margins and loop gain magnitudes between the two groups. However, the CLIR in the OSA subjects exhibited faster and more oscillatory dynamics. This result implies that, in addition to unstable upper airway mechanics, an underdamped chemoreflex control system may be another important factor that promotes the occurrence of periodic obstructive apneas during sleep.     

Neuro-fuzzy extraction of angular information from muscle afferentsfor ankle control during standing in paraplegic subjects: an animalmodel

This paper is part of a project whose aim is the implementation of closed-loop control of ankle angular position during functional electrical stimulation (FES) assisted standing in paraplegic subjects using natural sensory information. In this paper, a neural fuzzy (NF) model is implemented to extract angular position information from the electroneurographic signals recorded from muscle afferents using cuff electrodes in an animal model. The NF model, named dynamic nonsingleton fuzzy logic system is a Mamdani-like fuzzy system, implemented in the framework of recurrent neural networks. The fuzzification procedure implemented was the nonsingleton technique which has been shown in previous works to be able to take into account the uncertainty in the data. The proposed algorithm was tested in different situations and was able to predict reasonably well the ankle angular trajectories especially for small excursions (as during standing) and when the stimulation sites are far from the registration sites. This suggests it may be possible to use activity from muscle afferents recorded with cuff electrodes for FES closed-loop control of ankle position during quite standing.     

Gait phase information provided by sensory nerve activity duringwalking: applicability as state controller feedback for FES

In this study, we extracted gait-phase information from natural sensory nerve signals of primarily cutaneous origin recorded in the forelimbs of cats during walking on a motorized treadmill. Nerve signals were recorded in seven cats using nerve cuff or patch electrodes chronically implanted on the median, ulnar, and/or radial nerves. Features in the electroneurograms that were related to paw contact and lift-off were extracted by threshold detection. For four cats, a state controller model used information from two nerves (either median and radial, or ulnar and radial) to predict the timing of palmaris longus activity during walking. When fixed thresholds were used across a variety of walking conditions, the model predicted the timing of EMG activity with a high degree of accuracy (average error = 7.8%, standard deviation = 3.0%, n = 14). When thresholds were optimized for each condition, predictions were further improved (average error = 5.5%, standard deviation = 2.3%, n = 14). The overall accuracy with which EMG timing information could be predicted using signals from two cutaneous nerves for two constant walking speeds and three treadmill inclinations for four cats suggests that natural sensory signals may be implemented as a reliable source of feedback for closed-loop control of functional electrical stimulation (FES).     

Control of muscle relaxation during anesthesia: a novel approach for clinical routine

During general anesthesia drugs are administered to provide hypnosis, ensure analgesia, and skeletal muscle relaxation. In this paper, the main components of a newly developed controller for skeletal muscle relaxation are described. Muscle relaxation is controlled by administration of neuromuscular blocking agents. The degree of relaxation is assessed by supramaximal train-of-four stimulation of the ulnar nerve and measuring the electromyogram response of the adductor pollicis muscle. For closed-loop control purposes, a physiologically based pharmacokinetic and pharmacodynamic model of the neuromuscular blocking agent mivacurium is derived. The model is used to design an observer-based state feedback controller. Contrary to similar automatic systems described in the literature this controller makes use of two different measures obtained in the train-of-four measurement to maintain the desired level of relaxation. The controller is validated in a clinical study comparing the performance of the controller to the performance of the anesthesiologist. As presented, the controller was able to maintain a preselected degree of muscle relaxation with excellent precision while minimizing drug administration. The controller performed at least equally well as the anesthesiologist.     

Selective stimulation of sacral nerve roots for bladder control: astudy by computer modeling

The aim of this study was to investigate theoretically the conditions for the activation of the detrusor muscle without activation of the urethral sphincter and afferent fibers, when stimulating the related sacral roots, Therefore, the sensitivity of excitation and blocking thresholds of nerve fibers within a sacral root to geometric and electrical parameters in tripolar stimulation using a cuff electrode, have been simulated by a computer model. A 3D rotationally symmetrical model, representing the geometry and electrical conductivity of a nerve root surrounded by cerebrospinal fluid and a cuff was used, in combination with a model representing the electrical properties of a myelinated nerve fiber. The electric behavior of nerve fibers having different diameters and positions in a sacral root was analyzed and the optimal geometric and electrical parameters to be used for sacral root stimulation were determined. The model predicts that an asymmetrical tripolar cuff can generate unidirectional action potentials in small nerve fibers. While blocking the large fibers bidirectionally. This result shows that selective activation of the detrusor may be possible without activation of the urethral sphincter and the afferent fibers     

Stimulation Pattern-Free Control of FES Cycling: Simulation Study

The aim of this paper is to investigate control strategies for functional electrical simulation (FES) cycling, with particular focus on the generation of stimulation intensities for multiple muscles, without any predetermined stimulation pattern. The control system is developed by imitating the biological neuronal control system. Specifically, the control signal on the level of joint torque (quasi-joint torque) is generated from the feedback information of lower extremities. The quasi-joint torque is then distributed to each muscle and the muscle delay is compensated, and finally, the stimulation intensity is determined. Parameters of the control system are optimized by the genetic algorithm with cost function of energy consumption and cadence error. The proposed control system is evaluated by computer simulation. The controller generates efficient stimulation even during the muscle fatigue process and successfully continues cycling without any predetermined stimulation pattern. Moreover, the controller is robust to the parameter error in the muscle delay compensator and also to the disturbances. It is expected that the proposed method would improve the FES cycling performance and relieve patients by eliminating the experimental determination of the stimulation patterns.     

Estimation of M-wave scale factor during sustained contractions at high stimulation rate

In this paper, we propose a time-domain index to assess M-wave widening during high-frequency stimulation, as an objective parameter for quantifying muscle fatigue. At high stimulation frequencies, signal truncation, due to the delivery of the electrical stimulus before the M-wave generated by the previous stimulus extinguishes, biases the spectral frequency variables usually computed to estimate M-wave widening. Thus, we propose an estimator of the scale factor between two truncated M-waves. The estimator is derived from the Scale Transforms of the two signals, with an efficient implementation that avoids limits of resolution. The method was tested on both simulated and experimental signals. The simulations showed that the proposed technique is significantly less affected by signal truncation than previous approaches. The experimental recordings were collected from 11 subjects at stimulation frequencies of 20, 40, and 60 Hz. The scale factor estimation assessed M-wave widening in the three conditions, differentiating between the different rates of change of signal widening. The method proved to be significantly superior to M-wave spectral analysis. The technique can be applied to investigate myoelectric manifestations of muscle fatigue at stimulation rates that could not be analyzed in the past and, thus, opens new perspectives in the evaluation of electrical stimulation for training and rehabilitation protocols.     

Robust closed-loop control of isometric muscle force usingpulsewidth modulation

The design of feedback controllers to accurately and robustly regulate the properties of electrically stimulated muscle is considered. Reliable, precise control is necessary for the development of neuroprosthetic devices to improve gradation and repeatability of force. A digital closed-loop controller has been developed which regulates muscle force by modulating the pulsewidth of a constant-amplitude electrical simulation pulse train. This controller has been evaluated in slow- and fast-twitch muscles (cat soleus and plantaris) in acute experiments. In isometric tests, it was found to regulate muscle force with low sensitivity to modeling errors and disturbances while satisfying stability, repeatability, linearity, and step/ramp response criteria over a wide range of commands     

A discrete-time control algorithm applied to closed-loop pacing of HL-1 cardiomyocytes

Electrical stimulation represents a useful tool for electrophysiologic investigation of electrically excitable cells such as cardiomyocytes. The stimulation threshold and electrophysiologic response to precisely timed pulses yields valuable information regarding physiologic processes. However, determining these parameters accurately, while simultaneously resolving time-dependent or transient effects has been difficult or impossible with previous methods. This paper presents a discrete-time algorithmic controller used for closed-loop electrical stimulation of HL-1 clonal cardiomyocytes cultured on, and stimulated using, a planar microelectrode array. We introduce the temporal error-controlled algorithm (TECA), that is well-suited to control using capture fraction, a low data rate, highly quantized feedback parameter describing stimulation efficacy. HL-1 cardiomyocytes were electrically stimulated and resulting parameters were used to develop a representative model of partial capture, enabling extensive analysis of the algorithm. The performance of this approach is compared via computer simulation to a previously introduced conditional convergence algorithm to quantify its performance and relative advantages. Operation of the TECA is demonstrated by tracking the real-time biological response of stimulation threshold to a rapid increase in extracellular potassium concentration in four independent cell cultures. This work enables the use of stimulation threshold as a real-time, continuously monitored parameter with considerable utility in cardiac pharmacology, electrophysiology, and cell-based biosensing.     

Snore signal enhancement and activity detection via translation-invariant wavelet transform

Acoustical properties of snores have been widely studied as a potentially cost-effective and reliable alternative to diagnosing obstructive sleep apnea (OSA), with a common recognition that the diagnostic accuracy depends heavily on the snore signal quality and intelligibility. This paper proposes a novel preprocessing system that performs two critical tasks concurrently in a translation-invariant wavelet transform domain. These tasks include enhancement of snore signals via a level-correlation-dependent (LCD) threshold, and identification of snore presence through a snore activity (SA) detector. Various experiments were conducted to warrant the robustness of the system in terms of theoretical statistics quality, signal-to-noise ratio, mean opinion score, and clinical usefulness in detecting OSA. Results indicate that the proposed LCD threshold and SA detector are highly comparable to the existing denoising methodologies using level-dependent threshold and segmentation approaches using short-time energy and zero-crossing rate, yielding the best results in all the experiments. Given the strong initial performance of the proposed preprocessing system for snore signals, continued exploration in this direction could potentially lead to additional improvement in signal integrity, thereby increasing the diagnostic accuracy for OSA.     

Using evoked EMG as a synthetic force sensor of isometricelectrically stimulated muscle

A method for the estimation of the force generated by electrically stimulated muscle during isometric contraction is developed here. It is based upon measurements of the evoked electromyogram (EMG) [EEMG] signal. Muscle stimulation is provided to the quadriceps muscle of a paralyzed human subject using percutaneous intramuscular electrodes, and EEMG signals are collected using surface electrodes. Through the use of novel signal acquisition and processing techniques, as well, as a mathematical model that reflects both the excitation and activation phenomena involved in isometric muscle force generation, accurate prediction of stimulated muscle forces is obtained for large time horizons. This approach yields synthetic muscle force estimates for both unfatigued and fatigued states of the stimulated muscle. In addition, a method is developed that accomplishes automatic recalibration of the model to account for day-to-day changes in pickup electrode mounting as well as other factors contributing to EEMG gain variations. It is demonstrated that the use of the measured EEMG as the input to a predictive model of muscle torque generation is superior to the use of the electrical stimulation signal as the model input. This is because the measured EEMG signal captures all of the neural excitation, whereas stimulation-to-torque models only reflect that portion of the neural excitation that results directly from stimulation. The time-varying properties of the excitation process cannot be captured by existing stimulation-to-torque models, but they are tracked by the EEMG-to-torque models that are developed here. This work represents a promising approach to the real-time estimation of stimulated muscle force in functional neuromuscular stimulation applications     

Instrumentation for ENG and EMG recordings in FES systems

An electronic circuit for analog processing of neural (electroneurogram or ENG) and muscular (electromyogram or EMG) signals in functional electrical stimulation (FES) systems is described. The basic circuit consists of a low-noise gated preamplifier, bandpass filter, amplifier, and a blanking circuit to minimize stimulation artifacts during electrical stimulation. This device was tested in chronic recordings using a triphasic cliff electrode for nerves and epimysial electrodes for muscles in the hind limbs of cats. The device was used for nerve recordings in the presence of electrical stimulation of muscles in the same leg. The recordings showed rejection of stimulation and muscle (M-wave) artifacts, while retaining the information of interest     

Detection and classification of sensory information from acute spinal cord recordings

One avenue of research for partial restoration of function following spinal cord injury is the use of neural prostheses, an example of which is functional electrical stimulation (FES) devices for motor functions. Neural prostheses may also be useful for the extraction of sensory information directly from the nervous system. We suggest the spinal cord as a possible site for the detection of peripheral sensory information from neural activity alone. Acute multichannel extracellular recordings were used to extract neural spike activity elicited from peripheral sensations from the spinal cords of rats. To test the recording method and classification potential, eight classes of sensory events were recorded consisting of electrical stimulation of seven locations on rat forepaws, and another class of data during which no stimulus was present. A dual-stage classification scheme using principal component analysis and k-Means clustering was devised to classify the sensory events during single trials. The eight tasks were correctly identified at a mean accuracy of 96%. Thus, we have shown the methodology to detect and classify peripheral sensory information from multichannel recordings of the spinal cord. These methods may be useful, for example, in a closed-loop FES for restoration of hand grasp.     

A versatile microprocessor-based multichannel stimulator forskeletal muscle cardiac assist

A versatile, microprocessor-based stimulator for skeletal muscle cardiac assist (SMCA) has been designed, constructed, and used in several studies. The stimulator uses multiple bipolar electrodes to deliver arbitrarily specified electrical stimulus sequences to three nerve branches of the latissimus dorsi muscle. The electrodes are electrically isolated to effect regional stimulation of the muscle. The width, amplitude, and interpulse interval of each pulse in the stimulus sequence are independently variable, and the three channels are independently programmable, allowing a wide variety of stimulus patterns. Battery powered units have been used in studies for up to one year. In this paper, the stimulator and sample applications in SMCA are described     

An adaptive detector of genioglossus EMG reflex using Berkner transform for time latency measurement in OSA pathophysiological studies

To investigate obstructive sleep apnea syndrome mechanisms, we developed a device to measure the surface electromyogram (EMG) time latency reflex of the genioglossus muscle stimulated by time and amplitude calibrated negative pharyngeal pressure drops. The reflex signals were found to be disturbed by transient signals that generate false alarms. Thus, to reduce false alarm occurrences we designed an adaptive multiscale method. Continuous wavelet transform (CWT) is widely used in biomedical signal event detection processes. The Berkner transform is an approximation of a CWT that is based on a hierarchical scheme similar to discrete wavelet transform. We used the Berkner transform to build a multiscale detector because it offers the possibility of maxima coefficients linkage that leads to good accuracy in reflex onset localization. As a contribution to this novel approach we used a reconstruction formula to develop an adaptive method for scale range determination in our surface EMG reflex detector. Finally, we characterized our detector in terms of accuracy and robustness, first on synthesized signals and second, on signals acquired on apneic patients and healthy subjects. Preliminary results showed a significant difference (p < 0.01) between the two populations regarding the genioglossus muscle mean latency time. These physiological findings may partly explain why the upper airway protective reflex occurring when a negative pressure is applied to the upper airway is ineffective in OSA patients, leading to pharyngeal collapse.