Dry Electrodes Research Articles

Structured 3D Printed Dry ECG Electrodes Using Copper Based Filament

Commercial Silver and Silver Chloride (Ag/AgCl) wet electrodes are used to monitor electrocardiogram (ECG) signals in numerous bioimpedance applications. These electrodes are single-use components that irritate the skin during the replacement and removal of electrodes, making the process uncomfortable for the patient. This study introduces the use of a copper-based filament with the highest reported conductivity (0.006 Ω.cm) in biomedical applications, showcasing the process parameters of 3D printed, semi-flexible and wearable dry electrodes to monitor ECG signals. The effect of the printing-process parameters on the electrical performance is thoroughly investigated (10 parameters and >100 electrode samples) to find the printed electrodes’ highest conductivity and lowest impedance. The results showed the concentric and flat dry electrode structures of Tbed = 80 °C and Tnozzle = 140 and 150 °C with the best performance, confirming that different electrode structures and printing parameters significantly influence electrodes' functionality, conductivity, and impedance measurements.

(Near‐) Infrared Drying of Lithium‐Ion Battery Electrodes: Influence of Energy Input on Process Speed and Electrode Adhesion

The drying of electrodes represents a critical process step in the production of lithium‐ion batteries. In this process step, unfavorably adjusted drying conditions can result in deteriorated electrode properties. Furthermore, the process speed is restricted by limited heat and mass transfer in purely convective drying. To counteract those effects, energy input by near‐infrared (NIR) radiation is a promising approach. Herein, analytical considerations are carried out to demonstrate the suitability of infrared radiation with regard to achievable electrode temperatures and drying rates. In an experimental approach, aqueous processed graphite anodes are dried with an NIR module, varying the power and the amount of convection for different experiments. The temperature profiles of the electrodes and the drying rates are measured and analyzed, and the electrodes are subsequently characterized using adhesion measurements. The results obtained show that energy input by NIR radiation during the drying of electrodes can lead to an increased drying speed, electrode temperature during drying, and adhesion force of the dry electrode. These findings indicate that the binder distribution during NIR drying is advantageous in terms of electrode adhesion, compared with convectively dried electrodes produced at comparable drying rates, positioning the process promisingly with regard to high throughput rates.

An enhanced motor imagery EEG signals prediction system in real-time based on delta rhythm

This work aims to develop a brain–computer interface (BCI) system based on electroencephalogram (EEG) signals, that is capable of remote controlling rehabilitation systems using wireless connections. This system can extract delta waves from raw EEG in real-time to predict motor imagery (MI) tasks. Where we built a simple acquisition device that acquires EEG signals using three dry electrodes, these non-invasive channels are positioned on the scalp surface at the occipital and central lobes. After the acquisition step, we amplify the signals and remove permanent noise during the preprocessing step. Then, in the feature extraction step, we extract possible features from each channel. Then, we select only some important features at the feature selection step, by the calculation of each feature’s contribution score. In the classification phase using machine learning algorithms, we select the light gradient boosting machine (LGBM) algorithm enhanced by the multi-verse optimization (MVO) algorithm, which enables the building of optimum prediction models. Also, this work employed a data analysis phase. Where to evaluate the characteristics independent between features at each step, we analysed the data using the correlation matrix results. As well as, we analysed the data changes temporally and spatially between MI tasks at each step. Therefore, the classification results indicated that the system accuracy score is over 90%. While in related work, we have an accuracy value ranging between 79% and 89%. These comparative results show the best quality of our system proposed for this work-based delta wave.

Electroencephalogram signals emotion recognition based on convolutional neural network-recurrent neural network framework with channel-temporal attention mechanism for older adults.

Reminiscence and conversation between older adults and younger volunteers using past photographs are very effective in improving the emotional state of older adults and alleviating depression. However, we need to evaluate the emotional state of the older adult while conversing on the past photographs. While electroencephalogram (EEG) has a significantly stronger association with emotion than other physiological signals, the challenge is to eliminate muscle artifacts in the EEG during speech as well as to reduce the number of dry electrodes to improve user comfort while maintaining high emotion recognition accuracy. Therefore, we proposed the CTA-CNN-Bi-LSTM emotion recognition framework. EEG signals of eight channels (P3, P4, F3, F4, F7, F8, T7, and T8) were first implemented in the MEMD-CCA method on three brain regions separately (Frontal, Temporal, Parietal) to remove the muscle artifacts then were fed into the Channel-Temporal attention module to get the weights of channels and temporal points most relevant to the positive, negative and neutral emotions to recode the EEG data. A Convolutional Neural Networks (CNNs) module then extracted the spatial information in the new EEG data to obtain the spatial feature maps which were then sequentially inputted into a Bi-LSTM module to learn the bi-directional temporal information for emotion recognition. Finally, we designed four group experiments to demonstrate that the proposed CTA-CNN-Bi-LSTM framework outperforms the previous works. And the highest average recognition accuracy of the positive, negative, and neutral emotions achieved 98.75%.

Graphene nano-platelets polyvinyl alcohol nanocomposite electrode for real time ECG signal acquisition

This paper highlights the development of graphene nanoplatelets polyvinyl alcohol(GNP@PVA) nanocomposite electrode to acquire real time Electrocardiogram(ECG) signal. In order to create GNP@PVA nanocomposite, solution casting was used. By drop casting the GNP@PVA nanocomposite onto a commercial silver/silver chloride (Ag/AgCl) electrode with different GNP concentrations, namely 0, 0.5, 0.75, and 1 wt/wt% are created. The 3-lead ECG system is designed using Arduino microcontroller, GNP@PVA electrode and AD8232 sensor. To investigate the physical, spectral, and microcrystalline characteristics of the prepared nanocomposites, the prepared GNP@PVA electrode is subjected to various analyses, including scanning electron microscope (SEM) analysis, X-ray diffraction (XRD), Fourier Transform Infrared Spectroscopy (FTIR) and Raman spectroscopy. The results demonstrated that ECG signals acquired by GNP@PVA (1%) has increased R peak value along with high sensitivity. To validate the performance and efficiency of designed GNP@PVA electrode, the acquired real time ECG signal is compared with commercial Ag/AgCl electrode. In contrast to commercial Ag/AgCl electrode, the designed GNP@PVA dry electrode has high signal to noise ratio of 21 due to high conductivity.

Fabrication of Textile-Based Dry Electrode and Analysis of Its Surface EMG Signal for Applying Smart Wear.

Ag/AgCl hydrogel electrodes, which are wet electrodes, are generally used to acquire bio-signals non-invasively. Research concerning dry electrodes is ongoing due to the following limitations of wet electrodes: (1) skin irritation and disease when attached for a long time; (2) poor adhesion due to sweat; and (3) considerable cost due to disposable use. Accordingly, electrodes in film, embroidery, and knit forms were manufactured from conductive sheets and conductive yarns, which are typical textile-type dry electrode materials, using different manufacturing methods and conditions. The prepared electrodes were conducted to measure the morphology, surface resistance, skin-electrode impedance, EMG signal acquisition, and analysis. The conductive sheet type electrode exhibited a similar skin-impedance, noise, and muscle activation signal amplitude to the Ag/AgCl gel electrode due to the excellent adhesion and shape stabilization. Embroidery electrodes were manufactured based on two-dimension lock stitch (Em_LS) and three-dimension moss-stitch (Em_MS). More stable EMG signal acquisition than Em_LS was possible when manufactured with Em_MS. The knit electrode was manufactured with the typical structures of plain, purl, and interlock. Although it was possible to acquire EMG signals, considerable noise was generated as the shape and size of the electrodes were changed due to the stretch characteristics of the knit structure. Finally, the applicability of the textile-type dry electrode was confirmed by combining it with a wearable device. More stable and accurate EMG signal acquirement will be possible through more precise parameter control in the future.

Novel replaceable EEG electrode system

Abstract Due to the direct contact between electrode and scalp, dry EEG electrodes are exposed to increased mechanical wear compared to conventional gel-based electrodes. However, state-of-the-art commercial cap systems commonly use permanently fixated electrodes which can lead to downtime of the EEG cap during professional repair and replacement as well as reduced overall lifetime. An easily replaceable EEG electrode would furthermore improve hygiene, especially for newborn and infant applications. We propose a novel replaceable electrode system, consisting of an electrode holder, a snap top, a contact ring fixated inside the electrode holder, and a replaceable electrode. The production process consists of 3D printing, silicone molding, resin casting, and electroless plating. The replaceable electrode system is integrated into a multichannel EEG cap system. A verification study is conducted with 30 volunteers. The operators experienced that the new electrode holder eases adjustment of the electrode to have proper contact with the scalp. During the study, defective electrodes can be replaced without a soldering process. Furthermore, all electrodes stayed in the holder and did not fall off the cap for the whole session. In conclusion, the novel replaceable electrode system is suitable for EEG measurements.

Flexible electrodes for non-invasive brain–computer interfaces: A perspective

At the present time, brain–computer interfaces (BCIs) are attracting considerable attention due to their application potential in many fields. In this Perspective, we provide a brief review of flexible electrode technologies for non-invasive BCIs, mainly including two types of the most representative flexible electrodes: dry electrodes and semi-dry electrodes. We also summarize the challenges encountered by the different kinds of electrodes by comparing their strengths and weaknesses in terms of manufacturing scalability, applicability, comfort, contact impedance, long-term stability, and biocompatibility. In addition, we describe some advanced configurations and suggest potential applications for non-invasive BCIs based on flexible electrodes and consider future development prospects.

Impact of immediate and continuous heart rate feedback by dry electrode ECG on time to initiation of ventilation after birth: protocol for a randomised controlled trial

Introduction3%–8% of newborns need positive pressure ventilation (PPV) after birth. Heart rate (HR) is considered the most sensitive indicator of the newborns’ condition and response to resuscitative interventions. According to...

More creative ideas are associated with increased right posterior power and frontal-parietal/occipital coupling in the upper alpha band: A within-subjects study

The neurophysiological investigation of creative idea generation is a growing research area. EEG studies congruently reported the sensitivity of upper alpha power (10-12 Hz) for the creative ideation process and its outcome. However, the majority of studies were between-subject design studies and research directly comparing the neurophysiological activation pattern when generating more and less creative ideas within a person are rare. Therefore, the present study was specifically focused on investigating brain activation patterns associated with the generation of more vs. less creative ideas. We applied an alternate uses task (AU-task; i.e., finding original uses for everyday objects such as a brick) in a sample of 74 participants and recorded the brain activation during the AU-task and reference period. A portable EEG system with 21 dry electrodes arranged in the international 10–20 system and linked ear as reference was used. We found a higher increase of upper alpha power during creative ideation (relative to reference period, i.e., task-related power, TRP) over right posterior sites when people generated more compared to less creative ideas. This was accompanied by an increase of functional coupling (i.e., task-related coherence increase) between frontal and parietal/occipital sites, which suggests higher internal attention and more control over sensory processes. Taken together, these findings complement the existing creativity research literature and indicate the importance of alpha power for the creative ideation process also within people.

WE-123. A 256-channel dry electrode cap for rapid high-density EEG

WE-123. A 256-channel dry electrode cap for rapid high-density EEG

Comparative study of a single lead ECG in a wearable device

BackgroundTechnological advances have led to electrocardiograph (ECG) functionality becoming increasingly accessible in wearable health devices, which has the potential to vastly expand the clinician's ability to monitor, diagnose, and manage cardiac health conditions. However, achieving the high signal quality necessary to make an accurate and confident diagnosis is inherently challenging on consumer device-acquired ECGs. Effective signal conditioning is crucial to make ECG data from wearable devices clinically actionable. ObjectiveThis study evaluates the heart rate (HR) performance of ECG data collected on the HeartKey® Test Watch, a single lead, dry electrode wrist wearable, against data acquired on two criterion devices: the Bittium® Faros 180, a gold standard wet electrode ambulatory monitoring device, and the HeartKey Chest Module. MethodsECG data was simultaneously acquired on three devices during a multi-stage protocol (sitting, walking, standing) designed to reflect the motion noise of real-life scenarios. Raw ECGs from the HeartKey Test Watch and HeartKey Chest Module were processed through HeartKey software, and the accuracy of the outputted heart rate data was compared to that of the criterion device at each stage of the protocol. A beat rejection analysis was performed to provide insight into the degree of high-frequency noise present in ECGs recorded on the HeartKey Test Watch. ResultsData acquired on the HeartKey Test Watch and processed by HeartKey software generated HR metrics that closely matched that of the criterion devices throughout the protocol. Bland-Altman analysis showed a mean absolute HR difference of 0.74, 1.21, 0.80 bpm during the sitting, walking, and standing stages respectively, which is within the ± 10% or ±5 bpm range required by ANSI EC13. ECG data from the HeartKey Test Watch had a higher beat rejection rate relative to the HeartKey Chest Module (8.5% vs ∼0%) due to the excessive high-frequency noise generated during the motion-based protocol. ConclusionHeartKey software demonstrated highly accurate HR performance, comparable to that of the criterion Faros device, when processing challenging ECG data acquired on a single lead, dry electrode wrist wearable during both non-motion and motion-based protocols.

Analysis of solvent-free lithium-ion electrodes formed under high pressure and heat

Dry electrode manufacturing holds promise for reducing the time and energy required to produce lithium-ion cells. However, this method which uses no solvents has required slow and specialized processes such as dry spraying and electrostatic spraying, which has prevented adoption of the technology in commercial applications. To explore an alternative way to produce dry electrodes, a heated press was used to adhere the LiFePO4 active material onto the current collector. It was found that at high temperature and pressure, a dry Lithium Iron Phosphate (LFP) electrode could retain 91% state of health after 250 cycles compared to a standard wet LFP electrode, which retained 93% state of health. It should be possible to use this method in a high throughput, heated calendaring roller setup to efficiently produce dry electrodes for Li-ion batteries.

MotiMove: Multi‐purpose transcutaneous functional electrical stimulator

AbstractMotiMove is a battery‐powered general‐purpose transcutaneous functional electrical stimulator (tFES) that comes out of more than 40‐year academic research at the University of Belgrade, Serbia. MotiMove can be used for therapeutic intervention, clinical research, and support of fitness training in different application modes (cycling, rowing, grasping, walking, and exercising). Unlike other commercially available tFES devices, it allows real‐time open or closed‐loop control of stimulation parameters to 8 separate current sources from a multitude of sensors. Recent studies with MotiMove in healthy people and people with motor diseases have shown the applicability of the MotiMove stimulator for different users in various environments. Future development will focus on FES clothes with dry interface electrodes and integrated sensors that combined with MotiMove will make a compact easy‐donning testbed for real‐time FES control algorithms.

Effect of Muscle Fatigue on Heart Signal on Physical Activity with Electromyogram and Electrocardiogram (EMG Parameter ) Monitoring Signals

Physical activity is an activity of body movement by utilizing skeletal muscles that is carried out daily. One form of physical activity is an exercise that aims to improve health and fitness. Parameters related to health and fitness are heart and muscle activity. Strong and prolonged muscle contractions result in muscle fatigue. To measure muscle fatigue, the authors used electromyographic (EMG) signals through monitoring changes in muscle electrical activity. This study aims to make a tool to detect the effect of muscle fatigue on cardiac signals on physical activity. This research method uses Fast Fourier Transform (FFT) with one group pre-test-post-test research design. The independent variable is the EMG signal when doing plank activities, while the dependent variable is the result of monitoring the EMG signal. To get more detailed measurement results, the authors use MPF, MDF and MNF and perform a T-test. The test results showed a significant value (pValue <0.05) in the pre-test and post-test. The Pearson correlation test got a value of 0.628 which indicates there is a strong relationship between exercise frequency and plank duration. When the respondent experiences muscle fatigue, the heart signal is affected by noise movement artifacts that appear when doing the plank. It is concluded that the tools in this study can be used properly. To overcome noise in the EMG signal, it is recommended to use dry electrodes and high-quality components. To improve the ability to transmit data, it is recommended to use a Raspberry microcontroller.

Multi‐Electrode Printed Bioelectronic Patches for Long‐Term Electrophysiological Monitoring

AbstractA novel architecture of materials and fabrication techniques is proposed that serves as a universal method for implementation of thin‐film biostickers for high resolution electrophysiological monitoring. Unlike the existing wearable patches, the presented solution can be worn for several days, and is not affected by daily routines such as physical exercise or taking bath. A printable biphasic liquid metal silver composite is used, both as the electrical interconnects and the electrodes. This allows combining advantages of dry electrodes, i.e., printability and non‐smearing behavior, with benefits of wet electrodes, i.e., high‐quality signal. A human subject study showed that these biphasic printed electrodes benefit from a lower electrode‐skin impedance compared to clinical grade Ag/AgCl electrodes. Digital printing enables autonomous fabrication of biostickers that are taylor‐made for each user and each application. A universal miniaturized electronic system for biopotential acquisition and wireless communication is develpoed, and demonstrated multiple biopotential acquisition cases, including electrocardiography, electroencephalography, electromyography, and electrooculography.

Strenuous exercise-tolerance stretchable dry electrodes for continuous multi-channel electrophysiological monitoring

Electrophysiological monitoring under strenuous exercise by using stretchable dry electrodes is vital for healthcare monitoring, prosthetic control, human−machine interfaces and other biomedical applications. However, the existing dry electrodes are not applicable to the strenuous exercise situation that always involves both fast moving and profuse sweating. Herein, we present a nano-thick porous stretchable dry electrode system with high stretchability and water permeability. The system attaches conformably to the skin and stretches with it under Van der Waals forces even at sweating conditions, allowing the detection of electromyogram when moving with an acceleration of 10 g at a sweating rate of 2.8 mg cm−2 min−1. It is also capable of acquiring electrocardiogram and electroencephalogram signals. The strategy proposed would enable the biomedical studies and related applications with the requirement of stably recording electrophysiological signals under strenuous exercise scenarios.

AtAwAR Translate: Attention-Aware Language Translation Application in Augmented Reality for Mobile Phones.

As lightweight, low-cost EEG headsets emerge, the feasibility of consumer-oriented brain–computer interfaces (BCI) increases. The combination of portable smartphones and easy-to-use EEG dry electrode headbands offers intriguing new applications and methods of human–computer interaction. In previous research, augmented reality (AR) scenarios have been identified to profit from additional user state information—such as that provided by a BCI. In this work, we implemented a system that integrates user attentional state awareness into a smartphone application for an AR written language translator. The attentional state of the user is classified in terms of internally and externally directed attention by using the Muse 2 electroencephalography headband with four frontal electrodes. The classification results are used to adapt the behavior of the translation app, which uses the smartphone’s camera to display translated text as augmented reality elements. We present the first mobile BCI system that uses a smartphone and a low-cost EEG device with few electrodes to provide attention awareness to an AR application. Our case study with 12 participants did not fully support the assumption that the BCI improves usability. However, we are able to show that the classification accuracy and ease of setup are promising paths toward mobile consumer-oriented BCI usage. For future studies, other use cases, applications, and adaptations will be tested for this setup to explore the usability.

Stretchable and Self-Adhesive PEDOT:PSS Blend with High Sweat Tolerance as Conformal Biopotential Dry Electrodes.

Dry epidermal electrodes that can always form conformal contact with skin can be used for continuous long-term biopotential monitoring, which can provide vital information for disease diagnosis and rehabilitation. But, this application has been limited by the poor contact of dry electrodes on wet skin. Herein, we report a biocompatible fully organic dry electrode that can form conformal contact with both dry and wet skin even during physical movement. The dry electrodes are prepared by drop casting an aqueous solution consisting of poly(3,4-ethylenedioxythiophene):polystyrenesulfonate (PEDOT:PSS), poly(vinyl alcohol) (PVA), tannic acid (TA), and ethylene glycol (EG). The electrodes can exhibit a conductivity of 122 S cm-1 and a mechanical stretchability of 54%. Moreover, they are self-adhesive to not only dry skin but also wet skin. As a result, they can exhibit a lower contact impedance to skin than commercial Ag/AgCl gel electrodes on both dry and sweat skins. They can be used as dry epidermal electrodes to accurately detect biopotential signals including electrocardiogram (ECG) and electromyogram (EMG) on both dry and wet skins for the users at rest or during physical movement. This is the first time to demonstrate dry epidermal electrodes self-adhesive to wet skin for accurate biopotential detection.

A PDMS-based microneedle array electrode for long-term ECG recording.

To acquire high-quality electrocardiogram (ECG) signals, traditional Ag/AgCl wet electrodes used together with conductive gel can effectively reduce electrode-skin interface impedance (EII) in a short term. However, their weaknesses of poor flexibility and instability can no longer meet the long-term monitoring requirements of intelligent wearable devices. Owing to the flexible dry electrode without conductive gel, it is a good choice to solve the critical problem on drying-out of conductive gel. Therefore, we develop a flexible microneedle array electrode (FMAE) based on polydimethylsiloxane (PDMS) substrate, which obtains reliable bioelectrical signals by way of penetrating into the stratum corneum (SC) of the skin. The fabrication process, including silicon mold, twice PDMS shape-transferring and encapsulation, has advantages of low cost, repeatable production and good biocompatibility. Afterwards, by comparing the performance with different electrodes, impedance test results indicate that the impedance of FMAE are smaller and more stable, and ECG tests in long term and at resting/jogging states also verify that FMAE can obtain durable, stable and reliable signals. In conclusion, FMAE is promising in long-term ECG monitoring.