Dry Electrodes Research Articles

Dry textile electrode for ambulatory monitoring after catheter ablation of atrial fibrillation: A pilot study of simultaneous comparison to the Holter electrocardiogram.

Background: Holter electrocardiogram (ECG) is the gold standard for ambulatory monitoring of atrial fibrillation (AF) but it is insufficient because of its limited recording time. A wearable ECG with a medical-grade dry textile electrode is a promising technology to remedy this limitation. This pilot study aimed to simultaneously compare the wearable and Holter ECGs for ambulatory monitoring in a clinical setting. Methods: This prospective observational study enrolled 18 patients who underwent AF ablation. One day after AF ablation, ambulatory ECG was obtained for three hours simultaneously using both the wearable and Holter ECG devices. Automatic ECG interpretations between devices were compared with correlation and agreement analyses. Results: Simultaneous ECG monitoring demonstrated a comparable analysis time and total heart beats between the two devices. Almost complete correlation and agreement were also demonstrated in all clinically relevant testing aspects except in R-wave amplitude (r = 0.743, p < .001). AF was detected in three patients. AF duration was the same in both ECG devices in two patients with continuous AF. In the remaining patient with intermittent AF, AF duration was shortened by 0.6% with the wearable ECG as compared to that with the Holter ECG. Conclusions: Simultaneous ECG comparison revealed a high consistency between the wearable and Holter ECG devices. The results of this study warrant further clinical studies for long-term monitoring of ambulatory ECG after AF ablation.

Embedded Machine Learning Using a Multi-Thread Algorithm on a Raspberry Pi Platform to Improve Prosthetic Hand Performance.

High accuracy and a real-time system are priorities in the development of a prosthetic hand. This study aimed to develop and evaluate a real-time embedded time-domain feature extraction and machine learning on a system on chip (SoC) Raspberry platform using a multi-thread algorithm to operate a prosthetic hand device. The contribution of this study is that the implementation of the multi-thread in the pattern recognition improves the accuracy and decreases the computation time in the SoC. In this study, ten healthy volunteers were involved. The EMG signal was collected by using two dry electrodes placed on the wrist flexor and wrist extensor muscles. To reduce the complexity, four time-domain features were applied to extract the EMG signal. Furthermore, these features were used as the input of the machine learning. The machine learning evaluated in this study were k-nearest neighbor (k-NN), Naive Bayes (NB), decision tree (DT), and support vector machine (SVM). In the SoC implementation, the data acquisition, feature extraction, machine learning, and motor control process were implemented using a multi-thread algorithm. After the evaluation, the result showed that the pairing of the MAV feature and machine learning DT resulted in higher accuracy among other combinations (98.41%) with a computation time of ~1 ms. The implementation of the multi-thread algorithm in the pattern recognition system resulted in significant impact on the time processing.

Development of a flexible dry electrode based MXene with low contact impedance for biopotential recording

The dry electrode for biopotential recording is urgently need in wearable health monitoring systems, brain-computer interface (BCI), and human–computer interaction (HCI). However, high contact impedances of the electrode and the skin and inadequate shape adaptability of the electrode are challenges for the dry electrode to record signals accurately. Here, we present a flexible dry electrode based on transferring MXene (Ti3C2Tx) ink on a flexible polyimide (PI) substrate for biopotential recording. The electrode exhibits low contact impedances and excellent flexibility to conform the skin well. In vivo biopotential recording demonstrated the flexible dry electrode can record electrocardiograms (ECG), electroencephalograms (EEG), and electrooculogram (EOG) as accurately as the standard electrode (Ag/AgCl electrode). Moreover, our electrode can record ECG accurately, even the subject is in motion. The flexible dry electrode is suitable for wearable biopotential recording and promising to be used in wearable health monitoring systems, BCI, and HCI.

Intrinsically Stretchable Block Copolymer Based on PEDOT:PSS for Improved Performance in Bioelectronic Applications.

The conductive polyelectrolyte complex poly(3,4-ethylenedioxythiophene):poly(styrenesulfonate) (PEDOT:PSS) is ubiquitous in research dealing with organic electronic devices (e.g., solar cells, wearable and implantable sensors, and electrochemical transistors). In many bioelectronic applications, the applicability of commercially available formulations of PEDOT:PSS (e.g., Clevios) is limited by its poor mechanical properties. Additives can be used to increase the compliance but pose a risk of leaching, which can result in device failure and increased toxicity (in biological settings). Thus, to increase the mechanical compliance of PEDOT:PSS without additives, we synthesized a library of intrinsically stretchable block copolymers. In particular, controlled radical polymerization using a reversible addition-fragmentation transfer process was used to generate block copolymers consisting of a block of PSS (of fixed length) appended to varying blocks of poly(poly(ethylene glycol) methyl ether acrylate) (PPEGMEA). These block copolymers (PSS(1)-b-PPEGMEA(x), where x ranges from 1 to 6) were used as scaffolds for oxidative polymerization of PEDOT. By increasing the lengths of the PPEGMEA segments on the PEDOT:[PSS(1)-b-PPEGMEA(1-6)] block copolymers, ("Block-1" to "Block-6"), or by blending these copolymers with PEDOT:PSS, the mechanical and electronic properties of the polymer can be tuned. Our results indicate that the polymer with the longest block of PPEGMEA, Block-6, had the highest fracture strain (75%) and lowest elastic modulus (9.7 MPa), though at the expense of conductivity (0.01 S cm-1). However, blending Block-6 with PEDOT:PSS to compensate for the insulating nature of the PPEGMEA resulted in increased conductivity [2.14 S cm-1 for Blend-6 (2:1)]. Finally, we showed that Block-6 outperforms a commercial formulation of PEDOT:PSS as a dry electrode for surface electromyography due to its favorable mechanical properties and better adhesion to skin.

Fructus Xanthii-Inspired Low Dynamic Noise Dry Bioelectrodes for Surface Monitoring of ECG.

The microstructured surfaces of bioelectrical dry electrodes are important aspects of dry electrode design. However, traditional surfaces for microstructured bioelectrical dry electrodes are costly to produce and require complex fabrication methods. In this study, a novel stacked-template method is proposed for the first time, rapidly producing microstructured dry electrodes at a low cost and with a large surface area. Three types of microstructured Ag/AgCl thermoplastic polyurethane (TPU) electrodes with a Fructus xanthii-inspired barb structure (FXbs) are prepared using this method; then, the dynamic friction, hair interference resistance, electrochemical, and electrocardiogram (ECG) signal acquisition performance of the electrodes are tested, and the dynamic noise characteristics of the electrodes are comprehensively evaluated with simulated instruments. Compared to the plate structure, the dynamic friction coefficient of the FXbs electrode improved by about 38.8%, exhibiting strong hair interference resistance. In addition, the FXbs electrode exhibits low dynamic noise and comparable performance to the wet electrode, in terms of signal acquisition, when it is tested using simulated instruments. Therefore, the prepared FXbs electrode increases the friction coefficient between the electrode and the skin, which effectively resolves issues related to dynamic noise in bioelectrical signals, making it suitable for dynamic measurements.

A Mass-Producible Washable Smart Garment with Embedded Textile EMG Electrodes for Control of Myoelectric Prostheses: A Pilot Study.

Electromyography (EMG) is the resulting electrical signal from muscle activity, commonly used as a proxy for users’ intent in voluntary control of prosthetic devices. EMG signals are recorded with gold standard Ag/AgCl gel electrodes, though there are limitations in continuous use applications, with potential skin irritations and discomfort. Alternative dry solid metallic electrodes also face long-term usability and comfort challenges due to their inflexible and non-breathable structures. This is critical when the anatomy of the targeted body region is variable (e.g., residual limbs of individuals with amputation), and conformal contact is essential. In this study, textile electrodes were developed, and their performance in recording EMG signals was compared to gel electrodes. Additionally, to assess the reusability and robustness of the textile electrodes, the effect of 30 consumer washes was investigated. Comparisons were made between the signal-to-noise ratio (SNR), with no statistically significant difference, and with the power spectral density (PSD), showing a high correlation. Subsequently, a fully textile sleeve was fabricated covering the forearm, with 14 textile electrodes. For three individuals, an artificial neural network model was trained, capturing the EMG of 7 distinct finger movements. The personalized models were then used to successfully control a myoelectric prosthetic hand.

Characterization of Ag/AgCl Dry Electrodes for Wearable Electrophysiological Sensing

With the rising need for on-body biometric sensing, the development of wearable electrophysiological sensors has been faster than ever. Surface electrodes placed on the skin need to be robust in order to measure biopotentials from the body reliably and comfortable for extended wearability. The electrical stability of nonpolarizable silver/silver chloride (Ag/AgCl) and its low-cost, commercial production have made these electrodes ubiquitous health sensors in the clinical environment, where wet gels and long wires are accommodated by patient immobility. However, smaller, dry electrodes with wireless acquisition are essential for truly wearable, continuous health sensing. Currently, techniques for the robust fabrication of custom Ag/AgCl electrodes are lacking. Here, we present three methods for the fabrication of Ag/AgCl electrodes: oxidizing Ag in a chlorine solution, electroplating Ag, and curing Ag/AgCl ink. Each of these methods is then used to create three different electrode shapes for wearable application. Bench-top and on-body evaluation of the electrode techniques was achieved by electrochemical impedance spectroscopy (EIS), calculation of variance in electrocardiogram (ECG) measurements, and analysis of auditory steady-state response (ASSR) measurement. Microstructures produced on the electrode by each fabrication technique were also investigated with scanning electron microscopy (SEM) and energy-dispersive X-ray spectroscopy (EDX). The custom Ag/AgCl electrodes were found to be efficient in comparison with standard, commercial Ag/AgCl wet electrodes across all three of our presented techniques, with Ag/AgCl ink shown to be the better out of the three in bench-top and biometric recordings.

Об опыте разработки мобильного комплекса для регистрации электрической активности головного мозга на базе технологии сухих электродов

The technology of creating a mobile complex for registration of the brain electrical activity, for recording an electroencephalographic signal with one channel, is considered. Previously, technological problems associated with insufficient sensitivity and selectivity in the sense of signal-to-noise ratio did not allow the use of electroencephalographic activity recording systems based on the so-called dry electrodes in practical applications. At the same time, even with a small number of leads, such signals, when recorded, for example, from the visual cortex localized in the occipital region of the brain can be extremely informative in the context of the operator activity analysis and other types of human activity, in which arbitrary control of attention plays an essential role. This paper considers the experience of creating a mobile autonomous complex for recording such signals for the tasks of monitoring the characteristics of the operator's activities in scientific applications. The design features of such a device, created based on Node MCU technology, which is gaining wide distribution in embedded systems, proprietary narrowband amplifiers of the electric signal and dry electrodes created by industry in the last decade, are described. Some examples of practical application of such a complex are given. The most promising directions for the development of technology are discussed.

PEDOT: PSS treated cotton-based textile dry electrode for ECG sensing

Reliable extraction of physiological signals from human skin is essential information for health monitoring, preventive care, and treatment. Wearable bioelectronics advancements that are directly placed on the epidermis surface offer a promising future biopotential sensing option. Wearable health-monitoring systems should be comfortable, stigma-free, and capable of producing high-quality data. Wearable textile electrodes for biopotential sensing are a promising candidate for long-term health monitoring to overcome the drawbacks of wet and metal electrodes. This work proposes a cotton-based textile dry electrode for ECG monitoring via the treatment of prepared conductive ink by Poly(3,4-ethylenedioxythiophene) (PEDOT): Poly (styrene sulfonate) (PSS) and DMSO. These electrodes give excellent quality ECG signals without any skin irritation. The ECG is monitored by a portable self-designed low-cost Arduino-based device and validated by a standard ECG monitoring system. The electrode offers high skin compatibility and good signal quality, which are prominent features for cardiorespiratory monitoring.

A Survey on EEG-Based Solutions for Emotion Recognition With a Low Number of Channels

The market uptake of Brain-Computer Interface technologies for clinical and non-clinical applications is attracting the scientific world towards the development of daily-life wearable systems. Beyond the use of dry electrodes and wireless technology, reducing the number of channels is crucial to enhance the ergonomics of devices. This paper presents a review of the studies exploiting a number of channels less than 16 for electroencephalographic (EEG) based-emotion recognition. The main findings of this review concern: (i) the criteria to select the most promising scalp areas for EEG acquisitions; (ii) the attention to prior neurophysiological knowledge; and (iii) the convergences among different studies with respect to preferable areas of the scalp for signal acquisition. Three main approaches emerge for channel selection: data-driven, prior knowledge-based, and based on commercially-available wearable solutions. The most spread is the data-driven, but the neurophysiology of emotions is rarely taken into account. Furthermore, commercial EEG devices usually do not provide electrodes purposefully chosen to assess emotions. Considerable convergences emerge for some electrodes: Fp1, Fp2, F3 and F4 resulted the most informative channels for the valence dimension, according to both data-driven and neurophysiological prior knowledge approaches. The P3 and P4 resulted in being significant for the arousal dimension.

Design of Dry and Long-Lasting Electrodes for ECG

Humans and animals both generate bioelectric signals through their tissues in static and active forms. These signals could be used to check the different physiological conditions of the body. Electrocardiogram (ECG) is one of the signals produced by the heart. ECG helps to monitor the health of the heart such as heart rate, contraction of heart muscles, and blood circulation. Abnormality in these parameters can cause serious cardiovascular diseases. Thus, monitoring of ECG helps to early diagnose cardiovascular diseases. To measure these signals electrodes or sensors are used. There are several types of electrodes are developed to measure heart bioelectric signals, but they are not very efficient, consume more power, and can harm the skin. The focus of this research was to design new and more efficient dry electrodes. For this purpose, ECG noise was simulated in MATLAB and the main schematic diagram was designed. Suitable components of the electrode were selected according to the desired output. The circuit was designed through Proteus software and printed on PCB sticker paper. The evaluation result revealed that our designed ECG dry electrodes were more efficient than traditional gel-based ECG electrodes. Newly designed electrodes displayed less noise impedance and did not harm the skin of the patients. These dry electrodes can be used in hospitals to monitor ECG.

Comparison of Heart Rate Monitoring Accuracy between Chest Strap and Vest during Physical Training and Implications on Training Decisions

Heart rate (HR) and heart rate variability (HRV) based physiological metrics such as Excess Post-exercise Oxygen Consumption (EPOC), Energy Expenditure (EE), and Training Impulse (TRIMP) are widely utilized in coaching to monitor and optimize an athlete’s training load. Chest straps, and recently also dry electrodes integrated to special sports vests, are used to monitor HR during sports. Mechanical design, placement of electrodes, and ergonomics of the sensor affect the measured signal quality and artefacts. To evaluate the impact of the sensor mechanical design on the accuracy of the HR/HRV and further on to estimation of EPOC, EE, and TRIMP, we recorded HR and HRV from a chest strap and a vest with the same ECG sensor during supervised exercise protocol. A 3-lead clinical Holter ECG was used as a reference. Twenty-five healthy subjects (six females) participated. Mean absolute percentage error (MAPE) for HR was 0.76% with chest strap and 3.32% with vest. MAPE was 1.70% vs. 6.73% for EE, 0.38% vs. 8.99% for TRIMP and 3.90% vs. 54.15% for EPOC with chest strap and vest, respectively. Results suggest superior accuracy of chest strap over vest for HR and physiological metrics monitoring during sports.

State of the Art of Non-Invasive Electrode Materials for Brain-Computer Interface.

The brain–computer interface (BCI) has emerged in recent years and has attracted great attention. As an indispensable part of the BCI signal acquisition system, brain electrodes have a great influence on the quality of the signal, which determines the final effect. Due to the special usage scenario of brain electrodes, some specific properties are required for them. In this study, we review the development of three major types of EEG electrodes from the perspective of material selection and structural design, including dry electrodes, wet electrodes, and semi-dry electrodes. Additionally, we provide a reference for the current chaotic performance evaluation of EEG electrodes in some aspects such as electrochemical performance, stability, and so on. Moreover, the challenges and future expectations for EEG electrodes are analyzed.

Review on the wearable health-care monitoring system with robust motion artifacts reduction techniques

PurposeWearables are gaining prominence in the health-care industry and their use is growing. The elderly and other patients can use these wearables to monitor their vitals at home and have them sent to their doctors for feedback. Many studies are being conducted to improve wearable health-care monitoring systems to obtain clinically relevant diagnoses. The accuracy of this system is limited by several challenges, such as motion artifacts (MA), power line interference, false detection and acquiring vitals using dry electrodes. This paper aims to focus on wearable health-care monitoring systems in the literature and provides the effect of MA on the wearable system. Also presents the problems faced while tracking the vitals of users.Design/methodology/approachMA is a major concern and certainly needs to be suppressed. An analysis of the causes and effects of MA on wearable monitoring systems is conducted. Also, a study from the literature on motion artifact detection and reduction is carried out and presented here. The benefits of a machine learning algorithm in a wearable monitoring system are also presented. Finally, distinct applications of the wearable monitoring system have been explored.FindingsAccording to the study reduction of MA and multiple sensor data fusion increases the accuracy of wearable monitoring systems.Originality/valueThis study also presents the outlines of design modification of dry/non-contact electrodes to minimize the MA. Also, discussed few approaches to design an efficient wearable health-care monitoring system.

Me-Doped Ti-Me Intermetallic Thin Films Used for Dry Biopotential Electrodes: A Comparative Case Study.

In a new era for digital health, dry electrodes for biopotential measurement enable the monitoring of essential vital functions outside of specialized healthcare centers. In this paper, a new type of nanostructured titanium-based thin film is proposed, revealing improved biopotential sensing performance and overcoming several of the limitations of conventional gel-based electrodes such as reusability, durability, biocompatibility, and comfort. The thin films were deposited on stainless steel (SS) discs and polyurethane (PU) substrates to be used as dry electrodes, for non-invasive monitoring of body surface biopotentials. Four different Ti–Me (Me = Al, Cu, Ag, or Au) metallic binary systems were prepared by magnetron sputtering. The morphology of the resulting Ti–Me systems was found to be dependent on the chemical composition of the films, specifically on the type and amount of Me. The existence of crystalline intermetallic phases or glassy amorphous structures also revealed a strong influence on the morphological features developed by the different systems. The electrodes were tested in an in-vivo study on 20 volunteers during sports activity, allowing study of the application-specific characteristics of the dry electrodes, based on Ti–Me intermetallic thin films, and evaluation of the impact of the electrode–skin impedance on biopotential sensing. The electrode–skin impedance results support the reusability and the high degree of reliability of the Ti–Me dry electrodes. The Ti–Al films revealed the least performance as biopotential electrodes, while the Ti–Au system provided excellent results very close to the Ag/AgCl reference electrodes.

From fabric to smart T-shirt: fine tuning an improved robust system to detect arrhythmia

Wearable electrocardiogram (ECG) systems should be comfortable, non-stigmatizing, and capable of producing high-quality data. Many different designs of wearable textile ECG systems have recently emerged. Some of them are not considered to be smart garments, whereas most of the others present only the electronic side of the system. Our research work introduces a comprehensive study for an improved single-lead ECG smart shirt to identify automatically premature ventricular contraction as a common form of arrhythmia. For artifact-free results, Marvelous Designer is implemented to design our optimized relaxed slim fit shirt. In addition, a weft-knitted fabric of 80% nylon–20% spandex is used to manufacture the outer part of the shirt. Moreover, lightweight and small size electronic components are integrated to the outer part via low-resistance dry textile electrodes and 100% cotton fabric as an inner layer for easy transmission of weak ECG signals.

Non-invasive on-skin sensors for brain machine interfaces with epitaxial graphene

Objective. Brain–machine interfaces are key components for the development of hands-free, brain-controlled devices. Electroencephalogram (EEG) electrodes are particularly attractive for harvesting the neural signals in a non-invasive fashion. Approach. Here, we explore the use of epitaxial graphene (EG) grown on silicon carbide on silicon for detecting the EEG signals with high sensitivity. Main results and significance. This dry and non-invasive approach exhibits a markedly improved skin contact impedance when benchmarked to commercial dry electrodes, as well as superior robustness, allowing prolonged and repeated use also in a highly saline environment. In addition, we report the newly observed phenomenon of surface conditioning of the EG electrodes. The prolonged contact of the EG with the skin electrolytes functionalize the grain boundaries of the graphene, leading to the formation of a thin surface film of water through physisorption and consequently reducing its contact impedance more than three-fold. This effect is primed in highly saline environments, and could be also further tailored as pre-conditioning to enhance the performance and reliability of the EG sensors.

Applying Noncontact Sensing Technology in the Customized Product Design of Smart Clothes Based on Anthropometry.

Electrocardiograms (ECGs) provide important information for diagnosing cardiovascular diseases. In clinical practice, the conventional Ag/AgCl electrode is generally used; however, it is not suitable for long-term ECG measurement because of the risk of allergic reactions on the skin and the dying issue of electrolytic gels. In previous studies, several dry electrodes have been proposed to address these issues. However, most dry electrodes, which are the mode of conductive materials, have to contact the skin well and are easily affected by motion artifacts in daily life. In the smart clothes developed in this study, a noncontact electrode was used to assess the biopotential across the clothes to prevent skin irritation and discomfort. Moreover, a three-dimensional parametric model based on anthropometric data was built, and the technique of customized product design was introduced into the smart clothes development process to reduce the influence of motion artifacts. The experimental results show that the proposed smart clothes can maintain a good ECG signal quality stably under motion from different activities.

A high-density 256-channel cap for dry electroencephalography.

High‐density electroencephalography (HD‐EEG) is currently limited to laboratory environments since state‐of‐the‐art electrode caps require skilled staff and extensive preparation. We propose and evaluate a 256‐channel cap with dry multipin electrodes for HD‐EEG. We describe the designs of the dry electrodes made from polyurethane and coated with Ag/AgCl. We compare in a study with 30 volunteers the novel dry HD‐EEG cap to a conventional gel‐based cap for electrode‐skin impedances, resting state EEG, and visual evoked potentials (VEP). We perform wearing tests with eight electrodes mimicking cap applications on real human and artificial skin. Average impedances below 900 kΩ for 252 out of 256 dry electrodes enables recording with state‐of‐the‐art EEG amplifiers. For the dry EEG cap, we obtained a channel reliability of 84% and a reduction of the preparation time of 69%. After exclusion of an average of 16% (dry) and 3% (gel‐based) bad channels, resting state EEG, alpha activity, and pattern reversal VEP can be recorded with less than 5% significant differences in all compared signal characteristics metrics. Volunteers reported wearing comfort of 3.6 ± 1.5 and 4.0 ± 1.8 for the dry and 2.5 ± 1.0 and 3.0 ± 1.1 for the gel‐based cap prior and after the EEG recordings, respectively (scale 1–10). Wearing tests indicated that up to 3,200 applications are possible for the dry electrodes. The 256‐channel HD‐EEG dry electrode cap overcomes the principal limitations of HD‐EEG regarding preparation complexity and allows rapid application by not medically trained persons, enabling new use cases for HD‐EEG.

Abstract 11481: Non-Invasive Electrocardiographic Mapping of the Human Heart Through a Novel 'Cardiac Magnetic Resonance-Electrocardiographic Imaging' Solution for High Throughput Use

Background: Electrocardiographic imaging (ECGI) non-invasively maps the heart’s electrical activity through multiple leads on the body surface. Cardiologists need a safe, quick, affordable and re-usable ECGI method to apply to patients undergoing cardiovascular magnetic resonance (CMR), but current solutions are not suitable for high-throughput use. We developed a CMR-ECGI vest for high-throughput use and report the first in vivo results. Methods: We designed and fabricated the CMR-ECGI vest from cotton, containing 256 square (2x2cm) dry textile electrodes each tagged with a localisation marker ( Fig 1 ). Body surface potentials were recorded and co-registered with heart-torso geometries obtained from CMR ( Fig 2 ). Epicardial unipolar potentials were reconstructed using state-of-the-art ECGI algorithms (YR Lab) and local activation and repolarization times were computed using standard methods. Results: Ten healthy volunteers with normal resting ECGs were recruited (34±10years; 60% male). A recumbent 5-minute ECGI recording was performed (preparation time ~15 minutes for montage and doffing). 3 Tesla CMR provided baseline parameters (left ventricular ejection fraction [LVEF] 75±5%, right ventricular [RV] EF 57±5%, native T1 1275±23ms, T2 42±1ms) and showed no clinically significant late gadolinium enhancement. ECGI showed that the sites of earliest and latest activation were the basal RV ( Fig 3A ) and basal-lateral LV respectively ( Fig 3B ). Total duration of epicardial activation and repolarization was 73.3±8.9ms and 195±35.2ms, respectively. These epicardial activation patterns in health are in line with previously described ECGI data. Conclusions: We have developed a re-usable and high-throughput CMR-ECGI solution that is safe and well-tolerated in vivo . This technology is now available for large-scale clinical research use to provide deeper insights into the pathophysiology of arrhythmogenesis, through seamless integration with CMR.