Conductive polymer foam surface improves the performance of a capacitive EEG electrode

Spatial Variation Generation Algorithm for Motor Imagery Data Augmentation: Increasing the Density of Sample Vicinity

The imbalanced development between deep learning-based model design and motor imagery (MI) data acquisition raises concerns about the potential overfitting issue-models can identify training data well but fail to generalize test data. In this study, a Spatial Variation Generation (SVG) algorithm for MI data augmentation is proposed to alleviate the overfitting issue. In essence, SVG generates MI data using variations of electrode placement and brain spatial pattern, ultimately elevating the density of the raw sample vicinity. The proposed SVG prevents models from memorizing the training data by replacing the raw samples with the proper vicinal distribution. Moreover, SVG generates a uniform distribution and stabilizes the training process of models. In comparison studies involving five deep learning-based models across eight datasets, the proposed SVG algorithm exhibited a notable improvement of 0.021 in the area under the receiver operating characteristic curve (AUC). The improvement achieved by SVG outperforms other data augmentation algorithms. Further results from the ablation study verify the effectiveness of each component of SVG. Finally, the studies in the control group with varying numbers of samples show that the SVG algorithm consistently improves the AUC, with improvements ranging from approximately 0.02 to 0.15.

Hook Fabric Electroencephalography Electrode for Brain Activity Measurement without Shaving the Head

In this research, novel electroencephalogram (EEG) electrodes were developed to detect high-quality EEG signals without the requirement of conductive gels, skin treatments, or head shaving. These electrodes were created using electrically conductive hook fabric with a resistance of 1 Ω/sq. The pointed hooks of the conductive fabric establish direct contact with the skin and can penetrate through hair. To ensure excellent contact between the hook fabric electrode and the scalp, a knitted-net EEG bridge cap with a bridging effect was employed. The results showed that the hook fabric electrode exhibited lower skin-to-electrode impedance compared to the dry Ag/AgCl comb electrode. Additionally, it collected high-quality signals on par with the standard wet gold cups and commercial dry Ag/AgCl comb electrodes. Moreover, the hook fabric electrode displayed a higher signal-to-noise ratio (33.6 dB) with a 4.2% advantage over the standard wet gold cup electrode. This innovative electrode design eliminates the need for conductive gel and head shaving, offering enhanced flexibility and lightweight characteristics, making it ideal for integration into textile structures and facilitating convenient long-term monitoring.

The Feature, Performance, and Prospect of Advanced Electrodes for Electroencephalogram

Recently, advanced electrodes have been developed, such as semi-dry, dry contact, dry non-contact, and microneedle array electrodes. They can overcome the issues of wet electrodes and maintain high signal quality. However, the variations in these electrodes are still unclear and not explained, and there is still confusion regarding the feasibility of electrodes for different application scenarios. In this review, the physical features and electroencephalogram (EEG) signal performances of these advanced EEG electrodes are introduced in view of the differences in contact between the skin and electrodes. Specifically, contact features, biofeatures, impedance, signal quality, and artifacts are discussed. The application scenarios and prospects of different types of EEG electrodes are also elucidated.

Recent Advances in Stretchable and Wearable Capacitive Electrophysiological Sensors for Long-Term Health Monitoring

Over the past several years, wearable electrophysiological sensors with stretchability have received significant research attention because of their capability to continuously monitor electrophysiological signals from the human body with minimal body motion artifacts, long-term tracking, and comfort for real-time health monitoring. Among the four different sensors, i.e., piezoresistive, piezoelectric, iontronic, and capacitive, capacitive sensors are the most advantageous owing to their reusability, high durability, device sterilization ability, and minimum leakage currents between the electrode and the body to reduce the health risk arising from any short circuit. This review focuses on the development of wearable, flexible capacitive sensors for monitoring electrophysiological conditions, including the electrode materials and configuration, the sensing mechanisms, and the fabrication strategies. In addition, several design strategies of flexible/stretchable electrodes, body-to-electrode signal transduction, and measurements have been critically evaluated. We have also highlighted the gaps and opportunities needed for enhancing the suitability and practical applicability of wearable capacitive sensors. Finally, the potential applications, research challenges, and future research directions on stretchable and wearable capacitive sensors are outlined in this review.

Dry Electrodes for Human Bioelectrical Signal Monitoring

Bioelectrical or electrophysiological signals generated by living cells or tissues during daily physiological activities are closely related to the state of the body and organ functions, and therefore are widely used in clinical diagnosis, health monitoring, intelligent control and human-computer interaction. Ag/AgCl electrodes with wet conductive gels are widely used to pick up these bioelectrical signals using electrodes and record them in the form of electroencephalograms, electrocardiograms, electromyography, electrooculograms, etc. However, the inconvenience, instability and infection problems resulting from the use of gel with Ag/AgCl wet electrodes can't meet the needs of long-term signal acquisition, especially in wearable applications. Hence, focus has shifted toward the study of dry electrodes that can work without gels or adhesives. In this paper, a retrospective overview of the development of dry electrodes used for monitoring bioelectrical signals is provided, including the sensing principles, material selection, device preparation, and measurement performance. In addition, the challenges regarding the limitations of materials, fabrication technologies and wearable performance of dry electrodes are discussed. Finally, the development obstacles and application advantages of different dry electrodes are analyzed to make a comparison and reveal research directions for future studies.

Electrode Humidification Design for Artifact Reduction in Capacitive ECG Measurements

For wearable capacitive electrocardiogram (ECG) acquisition, capacitive electrodes may cause severe motion artifacts due to the relatively large friction between the electrodes and the dielectrics. In some studies, water can effectively suppress motion artifacts, but these studies lack a complete analysis of how water can suppress motion artifacts. In this paper, the effect of water on charge decay of textile electrode is studied systematically, and an electrode controllable humidification design using ultrasonic atomization is proposed to suppress motion artifacts. Compared with the existing electrode humidification designs, the proposed electrode humidification design can be controlled by a program to suppress motion artifacts at different ambient humidity, and can be highly integrated for wearable application. Firstly, the charge decay mode of the textile electrode is given and it is found that the process of free water evaporation at an appropriate free water content can be the dominant way of triboelectric charge dissipation. Secondly, theoretical analysis and experiment verification both illustrate that water contained in electrodes can accelerate the decay of triboelectric charge through the free water evaporation path. Finally, a capacitive electrode controllable humidification design is proposed by applying integrated ultrasonic atomization to generate atomized drops and spray them onto textile electrodes to accelerate the decay of triboelectric charge and suppress motion artifacts. The performance of the proposed design is verified by the experiment results, which shows that the proposed design can effectively suppress motion artifacts and maintain the stability of signal quality at both low and high ambient humidity. The signal-to-noise ratio of the proposed design is 33.32 dB higher than that of the non-humidified design at 25% relative humidity and is 22.67 dB higher than that of non-humidified electrodes at 65% relative humidity.

A Novel Analog Front End with Voltage-Dependent Input Impedance and Bandpass Amplification for Capacitive Biopotential Measurements

This paper proposes a novel analogue front end (AFE) that has three features: voltage-dependent input impedance, bandpass amplification, and stray capacitance reduction. With a view to applying the AFE to capacitive biopotential measurements (CBMs), the three features were investigated separately in a schematic and mathematical manner. Capacitive electrocardiogram (cECG) or capacitive electromyogram (cEMG) measurements using the AFE were performed in low-humidity conditions (below 35% relative humidity) for a total of seven human subjects. Performance evaluation of the AFE revealed the following: (1) the proposed AFE in cECG measurement with 1.70-mm thick clothing reduced the baseline recovery time and root mean square voltage of respiratory interference in subjects with healthy-weight body mass index (BMI), and increased R-wave amplitude for overweight-BMI subjects; and (2) the proposed AFE in cEMG measurement of biceps brachii muscle yielded stable electromyographic waveforms without the marked DC component for all subjects and a significant (p < 0.01) increase in the signal-to-noise ratio. These results indicate that the proposed AFE can provide a feasible balance between sensitivity and stability in CBMs, and it could be a versatile replacement for the conventional voltage follower used in CBMs.

Soft dry electroophthalmogram electrodes for human machine interaction

Current soft surface electrodes have attracted more and more attentions owing to their potential applications in biological signal monitoring, human-machine interaction (HMI) and Internet of Things (IoT). The paper presents that soft dry electrode based on polydimethylsiloxane-carbon black (PDMS-CB) conductive polymer is designed and fabricated to continuous, long-term, stable electroophthalmogram (EOG) signal recordings for HMI applications. The features corresponding to the different eye motions are extracted from the EOG data via the soft dry electrodes. Linear discriminant analysis (LDA) recognition algorithms are proposed to recognize eye motion behaviors for controlling the motion of the mobile robots. Experiment results have been demonstrated that LDA recognition algorithm achieves a relatively high recognition accuracy of 90.63% for recognizing four eye movements ('Up', 'Down', 'Right', and 'Left'). The control commands are generated with different eye motions and transmitted to the mobile robot through WiFi communication unit, which the mobile robot is successfully controlled. The soft dry electrodes have the potential in a comfortable, simple, wearable and wireless control of rehabilitation devices.

Enhancing the Usability of Brain-Computer Interface Systems

Brain-computer interfaces (BCIs) aim to enable people to interact with the external world through an alternative, nonmuscular communication channel that uses brain signal responses to complete specific cognitive tasks. BCIs have been growing rapidly during the past few years, with most of the BCI research focusing on system performance, such as improving accuracy or information transfer rate. Despite these advances, BCI research and development is still in its infancy and requires further consideration to significantly affect human experience in most real-world environments. This paper reviews the most recent studies and findings about ergonomic issues in BCIs. We review dry electrodes that can be used to detect brain signals with high enough quality to apply in BCIs and discuss their advantages, disadvantages, and performance. Also, an overview is provided of the wide range of recent efforts to create new interface designs that do not induce fatigue or discomfort during everyday, long-term use. The basic principles of each technique are described, along with examples of current applications in BCI research. Finally, we demonstrate a user-friendly interface paradigm that uses dry capacitive electrodes that do not require any preparation procedure for EEG signal acquisition. We explore the capacitively measured steady-state visual evoked potential (SSVEP) response to an amplitude-modulated visual stimulus and the auditory steady-state response (ASSR) to an auditory stimulus modulated by familiar natural sounds to verify their availability for BCI. We report the first results of an online demonstration that adopted this ergonomic approach to evaluating BCI applications. We expect BCI to become a routine clinical, assistive, and commercial tool through advanced EEG monitoring techniques and innovative interface designs.

Flexible capacitive electrodes for minimizing motion artifacts in ambulatory electrocardiograms

This study proposes the use of flexible capacitive electrodes for reducing motion artifacts in a wearable electrocardiogram (ECG) device. The capacitive electrodes have conductive foam on their surface, a shield, an optimal input bias resistor, and guarding feedback. The electrodes are integrated in a chest belt, and the acquired signals are transmitted wirelessly for ambulatory heart rate monitoring. We experimentally validated the electrode performance with subjects standing and walking on a treadmill at speeds of up to 7 km/h. The results confirmed the highly accurate heart rate detection capacity of the developed system and its feasibility for daily-life ECG monitoring.

Capacitive epidermal electronics for electrically safe, long-term electrophysiological measurements

Integration of capacitive sensing capabilities to epidermal electronic systems (EES) can enhance the robustness in operation for electrophysiological signal measurement. Capacitive EES designs are reusable, electrically safe, and minimally sensitive to motion artifacts. Experiments on human subjects illustrate levels of fidelity in ECG, EMG, and EOG recordings comparable to those of standard gel electrodes and of direct contact EES electrodes.

Brain-computer interfaces using capacitive measurement of visual or auditory steady-state responses

OBJECTIVE

Brain-computer interface (BCI) technologies have been intensely studied to provide alternative communication tools entirely independent of neuromuscular activities. Current BCI technologies use electroencephalogram (EEG) acquisition methods that require unpleasant gel injections, impractical preparations and clean-up procedures. The next generation of BCI technologies requires practical, user-friendly, nonintrusive EEG platforms in order to facilitate the application of laboratory work in real-world settings.

APPROACH

A capacitive electrode that does not require an electrolytic gel or direct electrode-scalp contact is a potential alternative to the conventional wet electrode in future BCI systems. We have proposed a new capacitive EEG electrode that contains a conductive polymer-sensing surface, which enhances electrode performance. This paper presents results from five subjects who exhibited visual or auditory steady-state responses according to BCI using these new capacitive electrodes. The steady-state visual evoked potential (SSVEP) spelling system and the auditory steady-state response (ASSR) binary decision system were employed.

MAIN RESULTS

Offline tests demonstrated BCI performance high enough to be used in a BCI system (accuracy: 95.2%, ITR: 19.91 bpm for SSVEP BCI (6 s), accuracy: 82.6%, ITR: 1.48 bpm for ASSR BCI (14 s)) with the analysis time being slightly longer than that when wet electrodes were employed with the same BCI system (accuracy: 91.2%, ITR: 25.79 bpm for SSVEP BCI (4 s), accuracy: 81.3%, ITR: 1.57 bpm for ASSR BCI (12 s)). Subjects performed online BCI under the SSVEP paradigm in copy spelling mode and under the ASSR paradigm in selective attention mode with a mean information transfer rate (ITR) of 17.78 ± 2.08 and 0.7 ± 0.24 bpm, respectively.

SIGNIFICANCE

The results of these experiments demonstrate the feasibility of using our capacitive EEG electrode in BCI systems. This capacitive electrode may become a flexible and non-intrusive tool fit for various applications in the next generation of BCI technologies.