Motor imaging therapy is of great significance to the rehabilitation of patients with stroke or motor dysfunction, but there are few studies on lower limb motor imagination. When electrical stimulation is applied to the posterior tibial nerve of the ankle, the steady-state somatosensory evoked potentials (SSSEP) can be induced at the electrical stimulation frequency. In order to better realize the classification of lower extremity motor imagination, improve the classification effect, and enrich the instruction set of lower extremity motor imagination, this paper designs two experimental paradigms: Motor imaging (MI) paradigm and Hybrid paradigm. The Hybrid paradigm contains electrical stimulation assistance. Ten healthy college students were recruited to complete the unilateral movement imagination task of left and right foot in two paradigms. Through time-frequency analysis and classification accuracy analysis, it is found that compared with MI paradigm, Hybrid paradigm could get obvious SSSEP and ERD features. The average classification accuracy of subjects in the Hybrid paradigm was 78.61%, which was obviously higher than the MI paradigm. It proves that electrical stimulation has a positive role in promoting the classification training of lower limb motor imagination.
In order to investigate the effect of deep brain stimulation on diseases such as epilepsy, we developed a closed-loop electrical stimulation system using LabVIEW virtual instrument environment and NI data acquisition card. The system was used to detect electrical signals of epileptic seizures automatically and to generate electrical stimuli. We designed a novel automatic detection algorithm of epileptic seizures by combining three features of field potentials: the amplitude, slope and coastline index. Experimental results of rat epileptic model in the hippocampal region showed that the system was able to detect epileptic seizures with an accuracy rate 91.3% and false rate 8.0%. Furthermore, the on-line high frequency electrical stimuli showed a suppression effect on seizures. In addition, the system was adaptive and flexible with multiple work modes, such as automatic and manual modes. Moreover, the simple time-domain algorithm of seizure detection guaranteed the real-time feature of the system and provided an easy-to-use equipment for the experiment researches of epilepsy control by electrical stimulation.
In the treatment of drug-refractory epilepsy in children, surgical treatment has a good clinical effect. However, for children whose surgical site is difficult to determine and who cannot undergo resectional surgery, neuromodulation techniques are one of the treatments that can be considered. At present, new neuromodulation technologies in children mainly include transcutaneous vagus nerve stimulation (transcutaneous auricular vagus nerve stimulation, ta-VNS), deep brain stimulation (deep brain stimulation, DBS), reactive nerve stimulation (responsive neurostimulation, RNS), transcranial magnetic stimulation (transcranial magnetic stimulation, TMS), transcranial direct current stimulation (transcranial direct current stimulation, TDCS) and transcranial alternating current stimulation (transcranial alternating current stimulation, TACS). This article briefly discussed the clinical efficacy and safety of various currently available neuromodulation technologies, so as to provide a reference for the rational selection and application of neuromodulation technologies, and improve the clinical efficacy and quality of life of children with drug-refractory epilepsy.
Currently, commercial devices for electrical neural stimulations can only provide fixed stimulation paradigms with preset constant parameters, while the development of new stimulation paradigms with time-varying parameters has emerged as one of the important research directions for expanding clinical applications. To facilitate the performance of electrical stimulation paradigms with time-varying parameters in animal experiments, the present study developed a well-integrated stimulation system to output various pulse sequences by designing a LabVIEW software to control a general data acquisition card and an electrical stimulus isolator. The system was able to generate pulse sequences with inter-pulse-intervals (IPI) randomly varying in real time with specific distributions such as uniform distribution, normal distribution, gamma distribution and Poisson distribution. It was also able to generate pulse sequences with arbitrary time-varying IPIs. In addition, the pulse parameters, including pulse amplitude, pulse width, interphase delay of biphasic pulse and duration of pulse sequence, were adjustable. The results of performance tests of the stimulation system showed that the errors of the parameters of pulse sequences output by the system were all less than 1%. By utilizing the stimulation system, pulse sequences with IPI randomly varying in the range of 5~10 ms were generated and applied in rat hippocampal regions for animal experiments. The experimental results showed that, even with a same mean pulse frequency of ~130 Hz, for neuronal populations, the excitatory effect of stimulations with randomly varying IPIs was significantly greater than the effect of stimulations with fixed IPIs. In conclusion, the stimulation system designed here may provide a useful tool for the researches and the development of new paradigms of neural electrical stimulations.
Transcranial electric stimulation (TES) is a non-invasive, economical, and well-tolerated neuromodulation technique. However, traditional TES is a whole-brain stimulation with a small current, which cannot satisfy the need for effectively focused stimulation of deep brain areas in clinical treatment. With the deepening of the clinical application of TES, researchers have constantly investigated new methods for deeper, more intense, and more focused stimulation, especially multi-electrode stimulation represented by high-precision TES and temporal interference stimulation. This paper reviews the stimulation optimization schemes of TES in recent years and further analyzes the characteristics and limitations of existing stimulation methods, aiming to provide a reference for related clinical applications and guide the following research on TES. In addition, this paper proposes the viewpoint of the development direction of TES, especially the direction of optimizing TES for deep brain stimulation, aiming to provide new ideas for subsequent research and application.
Individuals with motor dysfunction caused by damage to the central nervous system are unable to transmit voluntary movement commands to their muscles, resulting in a reduced ability to control their limbs. However, traditional rehabilitation methods have problems such as long treatment cycles and high labor costs. Functional electrical stimulation (FES) based on brain-computer interface (BCI) connects the patient’s intentions with muscle contraction, and helps to promote the reconstruction of nerve function by recognizing nerve signals and stimulating the moving muscle group with electrical impulses to produce muscle convulsions or limb movements. It is an effective treatment for sequelae of neurological diseases such as stroke and spinal cord injury. This article reviewed the current research status of BCI-based FES from three aspects: BCI paradigms, FES parameters and rehabilitation efficacy, and looked forward to the future development trend of this technology, in order to improve the understanding of BCI-based FES.
Artificial prosthesis is an important tool to help amputees to gain or partially obtain abled human limb functions. Compared with traditional prosthesis which is only for decoration or merely has feedforward control channel, the perception and feedback function of prosthesis is an important guarantee for its normal use and self-safety. And this includes the information of position, force, texture, roughness, temperature and so on. This paper mainly summarizes the development and current status of artificial prostheses in the field of perception and feedback technology in recent years, which is derived from two aspects: the recognition way of perception signals and the feedback way of perception signals. Among the part of recognition way of perception signals, the current commonly adopted sensors related to perception information acquisition and their application status in prosthesis are overviewed. Additionally, from the aspects of force feedback stimulation, invasive/non-invasive electrical stimulation, and vibration stimulation, the feedback methods of perception signals are summarized and analyzed. Finally, some problems existing in the perception and feedback technology of artificial prosthesis are proposed, and their development trends are also prospected.
A realizaton project of electrical stimulator aimed at motor dysfunction of stroke is proposed in this paper. Based on neurophysiological biofeedback, this system, using an ARM9 S3C2440 as the core processor, integrates collection and display of surface electromyography (sEMG) signal, as well as neuromuscular electrical stimulation (NMES) into one system. By embedding Linux system, the project is able to use Qt/Embedded as a graphical interface design tool to accomplish the design of stroke rehabilitation apparatus. Experiments showed that this system worked well.
Objective To review the advances of functional electrical stimulation(FES) in treatment of peripheral nerve injuries. Methods By index of recent literature, the measures of stimulation, the mechanisms of FES and unsolved problems were evaluated and analyzed. Results Great advances have been made in the treatment of peripheral nerve injuries. It can not only enhance the regeneration of injured peripheral nerve, but also prevent muscular atrophy. Conclusion FES is an effective treatment for peripheral nerve injuries.
Transcranial magneto-acoustic electrical stimulation (TMAES) is a novel method of brain nerve regulation and research, which uses induction current generated by the coupling of ultrasound and magnetic field to regulate neural electrical activity in different brain regions. As the second special envoy of nerve signal, calcium plays a key role in nerve signal transmission. In order to investigate the effect of TMAES on prefrontal cortex electrical activity, 15 mice were divided into control group, ultrasound stimulation (TUS) group and TMAES group. The TMAES group received 2.6 W/cm2 and 0.3 T of magnetic induction intensity, the TUS group received only ultrasound stimulation, and the control group received no ultrasound and magnetic field for one week. The calcium ion concentration in the prefrontal cortex of mice was recorded in real time by optical fiber photometric detection technology. The new object recognition experiment was conducted to compare the behavioral differences and the time-frequency distribution of calcium signal in each group. The results showed that the mean value of calcium transient signal in the TMAES group was (4.84 ± 0.11)% within 10 s after the stimulation, which was higher than that in the TUS group (4.40 ± 0.10)% and the control group (4.22 ± 0.08)%, and the waveform of calcium transient signal was slower, suggesting that calcium metabolism was faster. The main energy band of the TMAES group was 0?20 Hz, that of the TUS group was 0?12 Hz and that of the control group was 0?8 Hz. The cognitive index was 0.71 in the TMAES group, 0.63 in the TUS group, and 0.58 in the control group, indicating that both ultrasonic and magneto-acoustic stimulation could improve the cognitive ability of mice, but the effect of the TMAES group was better than that of the TUS group. These results suggest that TMAES can change the calcium homeostasis of prefrontal cortex nerve clusters, regulate the discharge activity of prefrontal nerve clusters, and promote cognitive function. The results of this study provide data support and reference for further exploration of the deep neural mechanism of TMAES.
