In order to solve the problems of insufficient stimulation channels and lack of stimulation effect feedback in the current electrical stimulation system, a functional array electrode electrical stimulation system with surface electromyography (sEMG) feedback was designed in this paper. Firstly, the effectiveness of the system was verified through in vitro and human experiments. Then it was confirmed that there were differences in the number of amperage needed to achieve the same stimulation stage among individuals, and the number of amperage required by men was generally less than that of women. Finally, it was verified that the current required for square wave stimulation was smaller than that for differential wave stimulation if the same stimulation stage was reached. This system combined the array electrode and sEMG feedback to improve the accuracy of electrical stimulation and performed the whole process recording of feedback sEMG signal in the process of electrical stimulation, and the electrical stimulation parameters could change with the change of the sEMG signal. The electrical stimulation system and sEMG feedback worked together to form a closed-loop electrical stimulation working system, so as to improve the efficiency of electrical stimulation rehabilitation treatment. In conclusion, the functional array electrode electrical stimulation system with sEMG feedback developed in this paper has the advantages of simple operation, small size and low power consumption, which lays a foundation for the introduction of electrical stimulation rehabilitation treatment equipment into the family, and also provides certain reference for the development of similar products in the future.
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.
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.
An automatic control system was designed to suppress pathological tremor on wrist joint with two degrees of freedom (DoF) using functional electrical stimulation (FES). The tremor occurring in the wrist flexion-extension and adduction-abduction was expected to be suppressed. A musculoskeletal model of wrist joint was developed to serve as the control plant, which covered four main muscles (extensor carpi radialis longus, extensor carpi ulnaris, flexor carpi radialis, and flexor carpi ulnaris). A second-order mechanical impedance model was used to describe the wrist skeletal dynamics. The core work was to design the controller and a hybrid control strategy was proposed, which combined inverse model based on feed forward control and linear quadratic regulator (LQR) optimal control. Performance of the system was tested under different input conditions (step signal, sinusoidal signal, and real data of a patient). The results indicated that the proposed hybrid controller could attenuate over 94% of the tremor amplitude on multi-DoF wrist joint.
Transcranial temporal interference stimulation (tTIS) is a novel non-invasive transcranial electrical stimulation technique that achieves deep brain stimulation through multiple electrodes applying electric fields of different frequencies. Current studies on the mechanism of tTIS effects are primarily based on rodents, but experimental outcomes are often significantly influenced by electrode configurations. To enhance the performance of tTIS within the limited cranial space of rodents, we proposed various electrode configurations for tTIS and conducted finite element simulations using a realistic mouse model. Results demonstrated that ventral-dorsal, four-channel bipolar, and two-channel configurations performed best in terms of focality, diffusion of activated brain regions, and scalp impact, respectively. Compared to traditional transcranial direct current stimulation (tDCS), these configurations improved by 94.83%, 50.59%, and 3 514.58% in the respective evaluation metrics. This study provides a reference for selecting electrode configurations in future tTIS research on rodents.
Median nerve electrical stimulation is a common peripheral nerve electrical stimulation treatment technology in clinic. With simple operation, it has been widely used in clinical to promote coma after craniocerebral trauma, relieve pain, improve cognition, Parkinson’s disease and so on. However, its mechanism has always been a hot topic and difficult part. At present, there are a large number of clinical efficacy studies and animal experiments of median nerve electrical stimulation at home and abroad. This article reviews the clinical application and animal experiments of median nerve electrical stimulation in recent years, and summarizes its mechanism, hoping to contribute to relevant clinical applications and research.
Objective To systematically evaluate the orthotic effect of functional electrical stimulation (FES) on the improvement of walking in stroke patients with foot drop. Methods The randomized controlled trials (RCTs) that investigated the orthotic effect of FES on walking in stroke patients with foot drop were electronically searched in the databases such as PubMed, Web of Science, The Cochrane Library (Issue 1, 2013), EMbase, CBM, CNKI, VIP and WanFang Data from January 2000 to January 2013, and the relevant references of included papers were also manually searched. Two reviewers independently screened the trials according to the inclusion and exclusion criteria, extracted the data, and assessed the methodology quality. The meta-analyses were performed using RevMan 5.1 software. Results A total of 8 RCTs involving 255 patients were included. The results of meta-analyses on 4 RCTs showed that, compared with the conventional rehabilitation intervention, the functional electrical stimulation could significantly improve the walking speed, with significant difference (MD=0.09, 95%CI 0.00 to 0.18, P=0.04). The other indicators were only descriptively analyzed due to the incomplete data. Conclusions Functional electrical stimulation is effective in improving walking speed, but it is uncertain of other therapeutic indicators. So it should be further proved by conducting more high quality, large sample and multi-center RCTs.
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.
Objective To review researches of treatment of peripheral nerve injury with neuromuscular electrical stimulation (NMES) regarding mechanism, parameters, and cl inical appl ication at home and abroad. Methods The latest original l iterature concerning treatment of peri pheral nerve injury with NMES was extensively reviewed. Results NMES should be used under individual parameters and proper mode of stimulation at early stage of injury. It could promote nerve regeneration and prevent muscle atrophy. Conclusion NMES plays an important role in cl inical appl ication of treating peripheral nerve injury, and implantable stimulation will be the future.
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.