Hybrid stimulator for chronic experiments

Design of a Wireless, Modular and Programmable Neuromuscular Electrical Stimulator. ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. ANNUAL INTERNATIONAL CONFERENCE 2019;2019:3815-3818. [PMID: 31946705 DOI: 10.1109/embc.2019.8856848] [Citation(s) in RCA: 0] [Impact Index Per Article: 0]

The use of electrical stimulation to elicit single twitches and tetanic contractions of skeletal muscles has increased markedly in the last years, with applications ranging from basic physiology to clinical settings. Addressing all possible needs required by different applications with an electrical stimulator is challenging as it requires the device to be highly flexible in terms of stimulation configurations (number of channels and electrode location), and possibility to control the stimulation patterns (timing and stimulation profiles). This paper describes a new wireless, modular, and programmable electrical stimulator integrating the possibility to acquire and use biomechanical signals to trigger the stimulation output. A closed-loop FES Cycling setup has been presented to show a possible application of the system.

A blink restoration system with contralateral EMG triggered stimulation and real-time artifact blanking

Patients suffering from facial paralysis are on the hazard of disfigurement and loss of vision due to loss of blink function. Functional-electrical stimulation (FES) is one possible way of restoring blink and other functions in these patients. A blink restoration system for uni-lateral facial paralyzed patients is described in this paper. The system achieves restoration of synchronized blink through processing the myoelectric signal of orbicularis oculi at the normal side in real-time as the trigger to stimulate the paralyzed eyelid. Design issues are discussed, including EMG processing, stimulating strategies and real-time artifact blanking. Two artifact removal approaches based on sample and hold and digital filtering technique are proposed and implemented. Finally, the whole system has been verified on rabbit models.

Surface EMG as a fatigue indicator during FES-induced isometric muscle contractions

The electromyogram (EMG) signal has potential as an indicator of stimulated muscle fatigue in applications of functional electrical stimulation (FES). In particular, it could be used to detect near lower limb collapse due to the associated muscle fatigue in FES-aided standing systems and thereby prevent falling. Surface EMG measurement, however, is hampered by stimulation artifact during FES. Modified surface stimulation and EMG detection equipment were designed and built to minimize this artifact and to permit detection of the electrical signal generated by the muscle during contraction. Artifact reduction techniques included shorting stimulator output leads between stimulus pulses and limiting and blanking slew rate in the EMG processing stage. Isometric fatigue experiments were performed by stimulating the quadriceps muscle of 20 able-bodied (a total of 125 trials) and three spinal cord injured (18 trials) subjects. Fatigue-tracking performance indicators were derived from the root-mean-square (RMS) of the EMG amplitude and from the median frequency (MF) of the EMG power spectral content. The results demonstrate that reliable fatigue tracking indicators for practical FES applications will be difficult to obtain, but that amplitude-based measures in spinal cord injured subjects show promise.

Detection and removal of stimulation artifacts in electroencephalogram recordings

Stimulation artifacts are short-duration, high-amplitude spikes which can be observed in electroencephalogram (EEG) recordings whenever surface functional electrical stimulation (FES) is applied during recordings. Stimulation artifacts are of non-physiologic origin and hence have to be removed before analysis of the EEG can take place. In this paper, algorithms for the detection and removal of stimulation artifacts are presented. The algorithms require only little computational resources and can be applied online, while signals are recorded. Therefore, the algorithms are suitable for applications such as online control of FES based neuroprostheses by a brain-computer interface. Tests are performed with datasets recorded from two subjects for artifact durations ranging from 0.5 ms to 10 ms. After application of the artifact removal algorithms the signal-to-noise ratio of the reconstructed signals ranges from 15 dB to 45 dB, depending on the duration of artifacts and the type of algorithm.

Electrically evoked auditory steady state responses in cochlear implant users

Auditory steady state responses are neural potentials in response to repeated auditory stimuli. This study shows that electrically evoked auditory steady state responses (EASSRs) to low-rate pulse trains can be reliably recorded by electrodes placed on the scalp of a cochlear implant (CI) user and separated from the artifacts generated by the electrical stimulation. Response properties are described, and the predictive value of EASSRs for behaviorally hearing thresholds is analyzed. For six users of a Cochlear Nucleus CI, EASSRs to symmetric biphasic pulse trains with rates between 35 and 47 Hz were recorded with seven scalp electrodes. The influence of various stimulus parameters was assessed: pulse rate, stimulus intensity, monopolar or bipolar stimulation mode, and presentation of either one pulse train on one electrode or interleaved pulse trains with different pulse rates on multiple electrodes. To compensate for the electrical artifacts caused by the stimulus pulses and radio frequency transmission, different methods of artifact reduction were employed. The validity of the recorded responses was confirmed by recording on-off responses, determination of response latency across the measured pulse rates, and comparison of amplitude growth of stimulus artifact and response amplitude. For stimulation in the 40 Hz range, response latencies of 35.6 ms (SD = 5.3 ms) were obtained. Responses to multiple simultaneous stimuli on different electrodes can be evoked, and the electrophysiological thresholds determined from EASSR amplitude growth in the 40 Hz range correlate well with behaviorally determined threshold levels for pulse rates of 41 Hz.

Factors affecting the stimulus artifact tail in surface-recorded somatosensory-evoked potentials

Surface-recorded somatosensory-evoked potentials (SEPs) are neural signals elicited by an external stimulus. In the case of electrically induced SEPs, the artifact generated by the stimulation process can severely distort the signal. In some cases, the artifact tail often lasts well into the initiation of the SEP making the determination of absolute latency very difficult. In this work, a new approach was taken to identify factors that affect the tail of the artifact. The methodology adopted was the development of a lumped electrical circuit model of the artifact generation process. While the modeling of the instrumentation hardware is relatively simple, this is not the case with tissue and electrode/skin interface effects. Consequently, this paper describes a novel tissue modeling approach that uses an autoregressive moving average (ARMA) parametric technique and an artificial neural network (ANN) to estimate tissue parameters from experimental data. This coupled with an estimation of the stimulation electrode-skin impedance completes the lumped circuit model. Simulink (The Mathworks Inc.) was used to evaluate the model under several different conditions. These results show that both the stimulation electrode-skin interface impedance and nature of the body tissue directly under the recording electrodes have a profound effect on the appearance of the stimulus artifact tail. This was verified by experimentally recorded data obtained from the median nerve using surface electrodes. Conclusions drawn from this work include that stimulation electrodes with low series capacitance should be used whenever possible to minimize the duration of the artifact tail.

A Closed-Loop Electrical Stimulation System for Cardiac Cell Cultures

An integrated electrical stimulation and recording system was designed for closed-loop control and analysis of cardiac cultures on planar microelectrode arrays. Stimulated action potentials from HL-1 clonal myocyte cultures were digitized, stimulation artifacts were removed using nulling and filtering methods, and analysis was performed to determine stimulation efficacy in real time. Results of this analysis were used to determine future stimulation waveform parameters such as polarity, amplitude, pulse duration, and rate or pattern. Algorithms were designed utilizing real-time analysis and control to maintain a desired electrophysiological response of the culture, such as an arbitrary capture fraction value. This paper presents the hardware and software design of the stimulus pulse circuitry, artifact extraction, analysis, and control components of the system. Applications of this technology include the study of cardiac cell physiology, improving the speed and accuracy of traditional open-loop stimulation protocols, pharmacological screening, and improving the performance of biosensors based on sensing electrical activity in cardiac cultures.

Stimulation artifact in surface EMG signal: effect of the stimulation waveform, detection system, and current amplitude using hybrid stimulation technique

The purpose of this study was to investigate the amplitude properties of the artifact generated on the recorded surface electromyography (EMG) signals during transcutaneous electrical muscle stimulation. The factors which were investigated are the shape of the stimulation waveform, the distance of the stimulating electrode from the recording system, the interelectrode distance of the detection system, the spatial filter used for signal detection, and the stimulation current amplitude. Surface EMG signals were recorded during electrical stimulation of the biceps brachii motor point with a linear adhesive array of eight electrodes. Electrical stimulation was applied with seven stimulation waveforms (mono- and biphasic triangular, sinusoidal, and rectangular), generated by a specifically designed neuromuscular stimulator with hybrid output stage. The stimulation peak current was linearly increased from 0 mA to the maximum tolerated by the subject. The detection systems investigated were single and double differential with interelectrode distances multiple of 5 mm. Two trials for each contraction were performed on three different days. The average rectified artifact values (both absolute and normalized with respect to the corresponding M-wave values) were computed to investigate the artifact amplitude properties. Results indicated that, while the artifact average rectified value, normalized with respect to the M-wave amplitude, depended on the distance of the detecting electrodes from the stimulation point, it did not depend on the stimulation waveform, on the current intensity, on the interelectrode distance, and on the spatial filter. It was concluded that, using hybrid stimulation techniques, the selection of particular stimulation waveforms, interelectrode distances, or spatial filters has a minor effect on the reduction of the artifact when recording M-waves.

[A method for analysis of muscle activity during electric stimulation]

The measurement of the surface-EMG during electrical stimulation requires the suppression of the stimulus pulse close to the source. This is necessary because of the discharge currents spreading within the human body caused by the stimulation pulse and the drift effects at the electrodes distorting the EMG-signal. A measurement-system will be presented, which splits the EMG in a detection and a processing path. A special converter keeps the base line at zero level. The detection path sets the gain of the recording amplifier and identifies the stimulation pulse to control its suppression. The processing of the EMG is conducted in the main path way. By these means the EMG including M-wave is undistorted and unbiased presented. The results will be discussed taking the physiology relevance into account.

Stimulus artifact removal using a software-based two-stage peak detection algorithm

The analysis of stimulus evoked neuromuscular potentials or m-waves is a useful technique for improved feedback control in functional electrical stimulation systems. Usually, however, these signals are contaminated by stimulus artifact. A novel software technique, which uses a two-stage peak detection algorithm, has been developed to remove the unwanted artifact from the recorded signal. The advantage of the technique is that it can be used on all stimulation artifact-contaminated electroneurophysiologic data provided that the artifact and the biopotential are non-overlapping. The technique does not require any estimation of the stimulus artifact shape or duration. With the developed technique, it is not necessary to record a pure artifact signal for template estimation, a process that can increase the complexity of experimentation. The technique also does not require the recording of any external hardware synchronisation pulses. The method avoids the use of analogue or digital filtering techniques, which endeavour to remove certain high frequency components of the artifact signal, but invariably have difficulty, resulting in the removal of frequencies in the same spectrum as the m-wave. With the new technique the signal is sampled at a high frequency to ensure optimum fidelity. Instrumentation saturation effects due to the artifact can be avoided with careful electrode placement. The technique was fully tested with a wide variety of electrical stimulation parameters (frequency and pulse width) applied to the common peroneal nerve to elicit contraction in the tibialis anterior. The program was also developed to allow batch processing of multiple files, using closed loop feedback correction. The two-stage peak detection artifact removal algorithm is demonstrated as an efficient post-processing technique for acquiring artifact free m-waves.