A hand-held electrocardiogram (ECG) monitor with capacitive coupling is designed in this study that can rapidly detect ECG signals through clothing. This new device improves many deficiencies of the traditional ECG monitor, such as infection due to direct skin contacting, inconvenience, and time-consuming. In specificity, the hand-held ECG monitor consists of two parts, a sensor and an embedded terminal. ECG signals are initially detected by a sensing electrode placed on the chest through clothing, then treated by single ended differential amplification, filtering and master amplification, and later processed through A/D conversion and ECG signal transmission by CC2540 module. The waveform and heart rate are finally displayed on the screen based on digital filtering and data processing for the received ECG signal on the embedded terminal. Results confirm that the newly developed hand-held ECG monitor is capable of detecting real-time ECG signals through clothing with advantages of simple operation, portability and rapid detection.
In recent years, wearable devices grew up gradually and developed increasingly. Aiming at the problems of skin sensibility and the change of electrode impedance of Ag/AgCl electrode in the process of long-term electrocardiogram (ECG) signal monitoring and acquisition, this paper discussed in detail a new sensor technology–fabric electrode, which is used for ECG signal acquisition. First, the concept and advantages of fabric electrode were introduced, and then the common substrate materials and conductive materials for fabric electrode were discussed and evaluated. Next, we analyzed the advantages and disadvantages from the aspect of textile structure, putting forward the evaluation system of fabric electrode. Finally, the deficiencies of fabric electrode were analyzed, and the development prospects and directions were prospected.
Objective To review the progress and application of peripheral nervous microelectrode. Methods The recent articles on peripheral nervous microelectrode were extensively reviewed. The classification, the progress of the peripheral nervous microelectrode and its utilizable prospect in the control of electronic prosthesis were summarized. Results The microelectrodes had favorable functions of selective stimulation and recording. It provided an information transmitting interface between the electric prosthesis and peripheral nerves. Conclusion Peripheral nervous signal is a feasible signal source to control electronic prosthesis.
In order to accurately localize the image coordinates and serial numbers of intraoperative subdural matrix electrodes, a matrix electrode localization algorithm for image processing is proposed in this paper. Firstly, by using point-by-point extended electrode location algorithm, the electrode is expanded point-by-point vertically and horizontally, and the initial coordinates and serial numbers of each electrode are determined. Secondly, the single electrode coordinate region extraction algorithm is used to determine the best coordinates of each electrode, so that the image coordinates and serial numbers of all electrodes are determined point-by-point. The results show that the positioning accuracy of electrode serial number is 100%, and the electrode coordinate positioning error is less than 2 mm. The algorithms in this paper can accurately localize the image coordinates and the serial numbers of a matrix electrode arranged in an arc, which could aid drawing of cortical function mapping, and achieve precise positioning of brain functional areas, so that it can be widely used in neuroscience research and clinical application based on electrocorticogram analysis.
The growing rate of public health problem for increasing number of people afflicted with poor sleep quality suggests the importance of developing portable sleep electroencephalogram (EEG) monitoring systems. The system could record the overnight EEG signal, classify sleep stages automatically, and grade the sleep quality. We in our laboratory collected the signals in an easy way using a single channel with three electrodes which were placed in frontal position in case of the electrode drop-off during sleep. For a test, either silver disc electrodes or disposable medical electrocardiographic electrodes were used. Sleep EEG recorded by the two types of electrodes was compared to each other so as to find out which type was more suitable. Two algorithms were used for sleep EEG processing, i.e. amplitude-integrated EEG (aEEG) algorithm and sample entropy algorithm. Results showed that both algorithms could perform sleep stage classification and quality evaluation automatically. The present designed system could be used to monitor overnight sleep and provide quantitative evaluation.
The injury of the knee joint is usually accompanied with the generation of hydrops. The volume of hydrops can be used as a reference to evaluate the extent of knee joint injuries. Based on the principle of bioimpedance detection, in this paper, a new method is proposed to detect knee joint hydrops. Firstly, a three-dimensional model of the knee joint was established according to the physiological and anatomical structure of the knee joint. Secondly, a knee impedance detection system was constructed based on the four-electrode theory, and the relationship between the knee impedance change and the volume of hydrops was calculated by linear regression. Finally, the model of rat knee joint hydrops was established, and the knee joint impedance was measured under different hydrops content to deduce the relationship between the fluid content and the knee joint impedance. The fluid volume in the joint was calculated by measuring the knee joint impedance, and the error rate was less than 10%. The experimental results show that the method proposed in this paper can establish the relationship between the impedance of the knee and the volume of fluid and realize the detection of the fluid volume.
A digital system for bioimpedance and electrical impedance tomography (EIT) measurement controlled by an ATmega16 microcontroller was constructed in our laboratory. There are eight digital electrodes using AD5933 to measure the impedance of the targets, and the data is transmitted to the computer wirelessly through nRF24L01. The structure of the system, circuit design, system testing, vitro measurements of animals' tissues and electrical impedance tomography are introduced specifically in this paper. The experimental results showed that the system relative error was 0.42%, and the signal noise ratio was 76.3 dB. The system not only can be used to measure the impedance by any two electrodes within the frequency of 1-100 kHz in a sweep scanning, but also can reconstruct the images of EIT. The animal experiments showed that the data was valid and plots were fitting with Cole-Cole theory. The testing verified the feasibility and effectiveness of the system. The images reconstructed of a salt-water tank are satisfactory and match with the actual distribution of the tank. The system improves the effectiveness of the front-end measuring signal and the stability of the system greatly.
ObjectiveThe purpose of this study was to compare the value of SEEG and subdural cortical electrodes monitoring in preoperative evaluation of epileptogenic zone. MethodsFeatures of patients using SEEG (48 cases) and subdural cortical electrodes monitoring (52 cases) to evaluate the epileptogenic zone were collected from June 2011 to June 2015. And the evaluation results, surgical effects and complications were compared. ResultsThere was no significant difference between SEEG and subdural cortical electrodes monitoring in identifying the epileptogenic zone or taking epileptic surgery, but SEEG could monitor multifocal and bilateral epileptogenic zone. And there was no significant difference in postoperative seizure control and intelligence improvement (P > 0.05). The total complication rate of SEEG was lower than subdural cortical electrodes monitoring, especially in hemorrhage and infection (P < 0.05). ConclusionsThere was no difference among SEEG and subdural cortical electrodes monitoring in surgical results, but SEEG with less hemorrhagic and infectious risks. SEEG is a safe and effective intracranial monitoring method, which can be widely used.
The effect of deep brain stimulation (DBS) surgery treatment for Parkinson's disease is determined by the accuracy of the electrodes placement and localization. The subthalamic nuclei (STN) as the implant target is small and has no clear boundary on the images. In addition, the intra-operative magnetic resonance images (MRI) have such a low resolution that the artifacts of the electrodes impact the observation. The three-dimensional (3D) visualization of STN and other nuclei nearby is able to provide the surgeons with direct and accurate localizing information. In this study, pre- and intra-operative MRIs of the Parkinson's disease patients were used to realize the 3D visualization. After making a co-registration between the high-resolution pre-operative MRIs and the low-resolution intra-operative MRIs, we normalized the MRIs into a standard atlas space. We used a special threshold mask to search the lead trajectories in each axial slice. After checking the location of the electrode contacts with the coronal MRIs of the patients, we reconstructed the whole lead trajectories. Then the STN and other nuclei nearby in the standard atlas space were visualized with the grey images of the standard atlas, accomplishing the lead reconstruction and nerve nuclei visualization near STN of all patients. This study provides intuitive and quantitative information to identify the accuracy of the DBS electrode implantation, which could help decide the post-operative programming setting.
Alzheimer’s disease (AD) is a chronic central neurodegenerative disease. The pathological features of AD are the extracellular deposition of senile plaques formed by amyloid-β oligomers (AβOs) and the intracellular accumulation of neurofibrillary tangles formed by hyperphosphorylated tau protein. In this paper, an in vitro pathological model of AD based on neuronal network chip and its real-time dynamic analysis were presented. The hippocampal neuronal network was cultured on the microelectrode array (MEA) chip and induced by AβOs as an AD model in vitro to simultaneously record two firing patterns from the interneurons and pyramidal neurons. The spatial firing patterns mapping and cross-correlation between channels were performed to validate the degeneration of neuronal network connectivity. This biosensor enabled the detection of the AβOs toxicity responses, and the identification of connectivity and interactions between neuronal networks, which can be a novel technique in the research of AD pathological model in vitro.