Assessment of Dry Epidermal Electrodes for Long-Term Electromyography Measurements

Design, Fabrication and Evaluation of a Stretchable High-Density Electromyography Array

The adoption of high-density electrode systems for human-machine interfaces in real-life applications has been impeded by practical and technical challenges, including noise interference, motion artefacts and the lack of compact electrode interfaces. To overcome some of these challenges, we introduce a wearable and stretchable electromyography (EMG) array, and present its design, fabrication methodology, characterisation, and comprehensive evaluation. Our proposed solution comprises dry-electrodes on flexible printed circuit board (PCB) substrates, eliminating the need for time-consuming skin preparation. The proposed fabrication method allows the manufacturing of stretchable sleeves, with consistent and standardised coverage across subjects. We thoroughly tested our developed prototype, evaluating its potential for application in both research and real-world environments. The results of our study showed that the developed stretchable array matches or outperforms traditional EMG grids and holds promise in furthering the real-world translation of high-density EMG for human-machine interfaces.

How Do People with Limited Movement Personalize Upper-Body Gestures? Considerations for the Design of Personalized and Accessible Gesture Interfaces

Always-on, upper-body input from sensors like accelerometers, infrared cameras, and electromyography hold promise to enable accessible gesture input for people with upper-body motor impairments. When these sensors are distributed across the person's body, they can enable the use of varied body parts and gestures for device interaction. Personalized upper-body gestures that enable input from diverse body parts including the head, neck, shoulders, arms, hands and fingers and match the abilities of each user, could be useful for ensuring that gesture systems are accessible. In this work, we characterize the personalized gesture sets designed by 25 participants with upper-body motor impairments and develop design recommendations for upper-body personalized gesture interfaces. We found that the personalized gesture sets that participants designed were highly ability-specific. Even within a specific type of disability, there were significant differences in what muscles participants used to perform upper-body gestures, with some pre-dominantly using shoulder and upper-arm muscles, and others solely using their finger muscles. Eight percent of gestures that participants designed were with their head, neck, and shoulders, rather than their hands and fingers, demonstrating the importance of tracking the whole upper-body. To combat fatigue, participants performed 51% of gestures with their hands resting on or barely coming off of their armrest, highlighting the importance of using sensing mechanisms that are agnostic to the location and orientation of the body. Lastly, participants activated their muscles but did not visibly move during 10% of the gestures, demonstrating the need for using sensors that can sense muscle activations without movement. Both inertial measurement unit (IMU) and electromyography (EMG) wearable sensors proved to be promising sensors to differentiate between personalized gestures. Personalized upper-body gesture interfaces that take advantage of each person's abilities are critical for enabling accessible upper-body gestures for people with upper-body motor impairments.

Surface electromyography using dry polymeric electrodes

Conventional wet Ag/AgCl electrodes are widely used in electrocardiography, electromyography (EMG), and electroencephalography (EEG) and are considered the gold standard for biopotential measurements. However, these electrodes require substantial skin preparation, are single use, and cannot be used for continuous monitoring (>24 h). For these reasons, dry electrodes are preferable during surface electromyography (sEMG) due to their convenience, durability, and longevity. Dry conductive elastomers (CEs) combine conductivity, flexibility, and stretchability. In this study, CEs combining poly(3,4-ehtylenedioxythiophene):polystyrenesulfonate (PEDOT:PSS) in polyurethane are explored as dry, skin contacting EMG electrodes. This study compares these CE electrodes to commercial wet Ag/AgCl electrodes in five subjects, classifying four movements: open hand, fist, wrist extension, and wrist flexion. Classification accuracy is tested using a backpropagation artificial neural network. The control Ag/AgCl electrodes have a 98.7% classification accuracy, while the dry conductive elastomer electrodes have a classification accuracy of 99.5%. As a conclusion, PEDOT based dry CEs were shown to successfully function as on-skin electrodes for EMG recording, matching the performance of Ag/AgCl electrodes, while addressing the need for minimal skin prep, no gel, and wearable technology.

A Preliminary Usability Study of Integrated Electronic Tattoo Surface Electromyography (sEMG) Sensors

Surface electromyography (sEMG) sensor measures the user's muscle activities by noninvasively placing electrodes on the surface of the user's skin. It has been widely used in monitoring various human movements. Recently a wearable and flexible epidermal sensor system called Electronic Tattoo (E-Tattoo) has been developed to enable intimate attachment of electrodes on the skin, improving long-term comfort. In order to make the E-Tattoo usable in monitoring muscle activities, it is always connected with a connector and signal processing blocks to collect and process the measured sEMG signals. We call it an integrated system. This paper investigates the usability of a prototype of the integrated system developed in the laboratory for monitoring muscle activities by testing its comfort with user experience surveys and comparing the quality of the sEMG signals by widely used performance metrics. Two typical movements, maximum voluntary isometric and non-isometric contractions, are considered for the experiments. Our preliminary results on five subjects demonstrate the effectiveness of the proposed integrated system. This system showed a comparable signal quality for these two movements as the commercial product with a much better comfort feeling from the user. It is also interesting to note that this prototype shows a much better signal-to-motion artifact ratio (SMR), which reflects the ability to measure muscle activities during active movements, compared with the commercial product, showing the potential of using this integrated system in monitoring sEMGs during active and dynamic movements.

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.

Electromyography Recordings Detect Muscle Activity Before Observable Contractions in Acute Stroke Care

OBJECTIVE

To evaluate muscle activity in the arms of adult stroke survivors with limited or no arm movement during acute care.

DESIGN

Prospective observational study.

SETTING

Acute care regional stroke center.

PARTICIPANTS

We recruited adults (N=21) who had a stroke within the previous 5 days who were admitted to a level 1 trauma hospital and had a National Institutes of Health Stroke Scale score >1 for arm function at the time of recruitment. A total of 21 adults (13 men, 8 women) with an average age of 60±15 years were recruited an average of 3±1 days after their stroke. Eleven (7 men, 4 women; age, 56±11y) had no observable or palpable arm muscle activity (Manual Muscle Test [MMT]=0) and 10 (6 men, 4 women; age, 64±1y) had detectable activity (MMT>0).

INTERVENTIONS

Dual mode sensors (electromyography and accelerometry) were placed on the anterior deltoid, biceps, triceps, wrist extensors, and wrist flexors of the impaired arm.

MAIN OUTCOME MEASURES

The number of muscle contractions, as well as average duration, amplitude, and co-contraction patterns were evaluated for each participant.

RESULTS

Muscle contractions were observed in all 5 muscles for all participants using electromyography (EMG) recordings. Contractions were easily identified from 30 minutes of monitoring for participants with an MMT >0, but up to 3 hours of monitoring was required for participants with an MMT=0 to detect contractions in all 5 muscles during standard care. Only the wrist extensors demonstrated significantly larger amplitude contractions for participants with an MMT>0 than those with an MMT=0. Co-contraction was rare, involving less than 10% of contractions. Co-contraction of 2 muscles most commonly aligned with the flexor synergy pattern commonly observed after stroke. For participants with an MMT=0, the number of contractions and maximum amplitude were moderately correlated with MMT scores at follow-up.

CONCLUSIONS

Muscle activity was detected with surface EMG recordings during standard acute care, even for individuals with no observable activity by clinical examination. Wearable sensors may be useful for monitoring early muscle activity and movement after stroke.

Acquisition of Surface EMG Using Flexible and Low-Profile Electrodes for Lower Extremity Neuroprosthetic Control

For persons with lower extremity (LE) amputation, acquisition of surface electromyography (sEMG) from within the prosthetic socket remains a significant challenge due to the dynamic loads experienced during the gait cycle. However, these signals are critical for both understanding the clinical effects of LE amputation and determining the desired control trajectories of active LE prostheses. Current solutions for collecting within-socket sEMG are generally (i) incompatible with a subject's prescribed prosthetic socket and liners, (ii) uncomfortable, and (iii) expensive. This study presents an alternative within-socket sEMG acquisition paradigm using a novel flexible and low-profile electrode. First, the practical performance of this Sub-Liner Interface for Prosthetics (SLIP) electrode is compared to that of commercial Ag/AgCl electrodes within a cohort of subjects without amputation. Then, the corresponding SLIP electrode sEMG acquisition paradigm is implemented in a single subject with unilateral transtibial amputation performing unconstrained movements and walking on level ground. Finally, a quantitative questionnaire characterizes subjective comfort for SLIP electrode and commercial Ag/AgCl electrode instrumentation setups. Quantitative analyses suggest comparable signal qualities between SLIP and Ag/AgCl electrodes while qualitative analyses suggest the feasibility of using the SLIP electrode for real-time sEMG data collection from load-bearing, ambulatory subjects with LE amputation.

Time Evolution of the Skin-Electrode Interface Impedance under Different Skin Treatments

A low and stable impedance at the skin-electrode interface is key to high-fidelity acquisition of biosignals, both acutely and in the long term. However, recording quality is highly variable due to the complex nature of human skin. Here, we present an experimental and modeling framework to investigate the interfacial impedance behavior, and describe how skin interventions affect its stability over time. To illustrate this approach, we report experimental measurements on the skin-electrode impedance using pre-gelled, clinical-grade electrodes in healthy human subjects recorded over 24 h following four skin treatments: (i) mechanical abrasion, (ii) chemical exfoliation, (iii) microporation, and (iv) no treatment. In the immediate post-treatment period, mechanical abrasion yields the lowest initial impedance, whereas the other treatments provide modest improvement compared to untreated skin. After 24 h, however, the impedance becomes more uniform across all groups (<20 kΩ at 10 Hz). The impedance data are fitted with an equivalent circuit model of the complete skin-electrode interface, clearly identifying skin-level versus electrode-level contributions to the overall impedance. Using this model, we systematically investigate how time and treatment affect the impedance response, and show that removal of the superficial epidermal layers is essential to achieving a low, long-term stable interface impedance.

Functional Fibers and Fabrics for Soft Robotics, Wearables, and Human-Robot Interface

Soft robotics inspired by the movement of living organisms, with excellent adaptability and accuracy for accomplishing tasks, are highly desirable for efficient operations and safe interactions with human. With the emerging wearable electronics, higher tactility and skin affinity are pursued for safe and user-friendly human-robot interactions. Fabrics interlocked by fibers perform traditional static functions such as warming, protection, and fashion. Recently, dynamic fibers and fabrics are favorable to deliver active stimulus responses such as sensing and actuating abilities for soft-robots and wearables. First, the responsive mechanisms of fiber/fabric actuators and their performances under various external stimuli are reviewed. Fiber/yarn-based artificial muscles for soft-robots manipulation and assistance in human motion are discussed, as well as smart clothes for improving human perception. Second, the geometric designs, fabrications, mechanisms, and functions of fibers/fabrics for sensing and energy harvesting from the human body and environments are summarized. Effective integration between the electronic components with garments, human skin, and living organisms is illustrated, presenting multifunctional platforms with self-powered potential for human-robot interactions and biomedicine. Lastly, the relationships between robotic/wearable fibers/fabrics and the external stimuli, together with the challenges and possible routes for revolutionizing the robotic fibers/fabrics and wearables in this new era are proposed.

Introduction of a sEMG Sensor System for Autonomous Use by Inexperienced Users

Wearable devices play an increasing role in the rehabilitation of patients with movement disorders. Although information about muscular activation is highly interesting, no approach exists that allows reliable collection of this information when the sensor is applied autonomously by the patient. This paper aims to demonstrate the proof-of-principle of an innovative sEMG sensor system, which can be used intuitively by patients while detecting their muscular activation with sufficient accuracy. The sEMG sensor system utilizes a multichannel approach based on 16 sEMG leads arranged circularly around the limb. Its design enables a stable contact between the skin surface and the system's dry electrodes, fulfills the SENIAM recommendations regarding the electrode size and inter-electrode distance and facilitates a high temporal resolution. The proof-of-principle was demonstrated by elbow flexion/extension movements of 10 subjects, proving that it has root mean square values and a signal-to-noise ratio comparable to commercial systems based on pre-gelled electrodes. Furthermore, it can be easily placed and removed by patients with reduced arm function and without detailed knowledge about the exact positioning of the sEMG electrodes. With its features, the demonstration of the sEMG sensor system's proof-of-principle positions it as a wearable device that has the potential to monitor muscular activation in home and community settings.

Muscle Activity After Stroke: Perspectives on Deploying Surface Electromyography in Acute Care

After a stroke, clinicians and patients struggle to determine if and when muscle activity and movement will return. Surface electromyography (EMG) provides a non-invasive window into the nervous system that can be used to monitor muscle activity, but is rarely used in acute care. In this perspective paper, we share our experiences deploying EMG in the clinic to monitor stroke survivors. Our experiences have demonstrated that deploying EMG in acute care is both feasible and useful. We found that current technology can be used to comfortably and non-obtrusively monitor muscle activity, even for patients with no detectable muscle activity by traditional clinical assessments. Monitoring with EMG may help clinicians quantify muscle activity, track recovery, and inform rehabilitation. With further research, we perceive opportunities in using EMG to inform prognosis, enable biofeedback training, and provide metrics necessary for supporting and justifying care. To leverage these opportunities, we have identified important technical challenges and clinical barriers that need to be addressed. Affordable wireless EMG system that can provide high-quality data with comfortable, secure interfaces that can be worn for extended periods are needed. Data from these systems need to be quickly and automatically processed to create round-ready results that can be easily interpreted and used by the clinical team. We believe these challenges can be addressed by integrating and improving current methods and technology. Deploying EMG in the clinic can open new pathways to understanding and improving muscle activity and recovery for individuals with neurologic injury in acute care and beyond.

Dry Epidermal Electrodes Can Provide Long-Term High Fidelity Electromyography for Limited Dynamic Lower Limb Movements

Due to the limitations of standard wet Silver/Silver Chloride (Ag/AgCl) hydrogel electrodes and the growing demand for long-term high fidelity surface electromyography (EMG) recording, dry epidermal electrodes are of great interest. Evaluating the usability and signal fidelity of dry epidermal electrodes could help determine the extent of potential applications using EMG electrodes. We collected EMG signals over eight days from the right rectus femoris of seven subjects using single-use dry epidermal electrodes and traditional Ag/AgCl electrodes while covered and uncovered during dynamic movements (leg extension, sit-to-stand, and treadmill walking at 0.75 m/s and 1.30 m/s). We quantified signal fidelity using signal-to-noise ratio (SNR); signal-to-motion ratio (SMR); and a metric we previously developed, the Signal Quality Index, which considers that better EMG signal quality requires both good signal-to-noise ratio and good signal-to-motion ratio. Wear patterns over the eight days degraded EMG signal quality. Uncovered epidermal electrodes that remained intact and maintained good adhesion to the skin had signal-to-noise ratios, signal-to-motion ratios, and Signal Quality Index values that were above the acceptable thresholds for limited dynamic lower limb movements (leg extension and sit-to-stand). This indicated that dry epidermal electrodes could provide good signal quality across all subjects for five days for these movements. For walking, the signal-to-noise ratios of the uncovered epidermal electrodes were still above the acceptable threshold, but signal-to-motion ratios and the Signal Quality Index values were far below the acceptable thresholds. The signal quality of the epidermal electrodes that showed no visible wear was stable over five days. As expected, covering the epidermal electrodes improved signal quality, but only for limited dynamic lower limb movements. Overall, single-use dry epidermal electrodes were able to maintain high signal quality for long-term EMG recording during limited dynamic lower limb movements, but further improvement is needed to reduce motion artifacts for whole body dynamic movements such as walking.

A gel-free Ti3C2Tx-based electrode array for high-density, high-resolution surface electromyography

Wearable sensors for surface electromyography (EMG) are composed of single- to few-channel large-area contacts, which exhibit high interfacial impedance and require conductive gels or adhesives to record high-fidelity signals. These devices are also limited in their ability to record activation across large muscle groups due to poor spatial coverage. To address these challenges, we have developed a novel high-density EMG array based on titanium carbide (Ti3C2Tx) MXene encapsulated in parylene-C. Ti3C2Tx is a two-dimensional nanomaterial with excellent electrical, electrochemical, and mechanical properties, which forms colloidally stable aqueous dispersions, enabling safe, scalable solutions-processing. Leveraging the excellent combination of metallic conductivity, high pseudocapacitance, and ease of processability of Ti3C2Tx MXene, we demonstrate the fabrication of gel-free, high-density EMG arrays which are ~8 μm thick, feature 16 recording channels, and are highly skin-conformable. The impedance of Ti3C2Tx electrodes in contact with human skin is 100-1000x lower than the impedance of commercially-available electrodes which require conductive gels to be effective. Furthermore, our arrays can record high-fidelity, low-noise EMG, and can resolve muscle activation with improved spatiotemporal resolution and sensitivity compared to conventional gelled electrodes. Overall, our results establish Ti3C2Tx-based bioelectronic interfaces as a powerful platform technology for high-resolution, non-invasive wearable sensing technologies.

An On-Skin Electrode with Anti-Epidermal-Surface-Lipid Function Based on a Zwitterionic Polymer Brush

On-skin flexible devices provide a noninvasive approach for continuous and real-time acquisition of biological signals from the skin, which is essential for future chronic disease diagnosis and smart health monitoring. Great progress has been achieved in flexible devices to resolve the mechanical mismatching between conventional rigid devices and human skin. However, common materials used for flexible devices including silicon-based elastomers and various metals exhibit no resistance to epidermal surface lipids (skin oil and grease), which restricts the long-term and household usability. Herein, an on-skin electrode with anti-epidermal-surface-lipid function is reported, which is based on the grafting of a zwitterionic poly(2-methacryl-oyloxyethyl, methacryloyl-oxyethyl, or meth-acryloyloxyethyl phosphorylcholine) (PMPC) brush on top of gold-coated poly(dimethylsiloxane) (Au/PDMS). Such an electrode allows the skin-lipids-fouled surface to be cleaned by simple water rinsing owing to the superhydrophilic zwitterionic groups. As a proof-of-concept, the PMPC-Au/PDMS electrodes are employed for both electrocardiography (ECG) and electromyography (EMG) recording. The electrodes are able to maintain stable skin-electrode impedance and good signal-to noise ratio (SNR) by water rinsing alone. This work provides a material-based solution to improve the long-term reusability of on-skin electronics and offers a unique prospective on developing next generation wearable healthcare devices.

Decoding Intent With Control Theory: Comparing Muscle Versus Manual Interface Performance

Manual device interaction requires precise coordination which may be difficult for users with motor impairments. Muscle interfaces provide alternative interaction methods that may enhance performance, but have not yet been evaluated for simple (eg. mouse tracking) and complex (eg. driving) continuous tasks. Control theory enables us to probe continuous task performance by separating user input into intent and error correction to quantify how motor impairments impact device interaction. We compared the effectiveness of a manual versus a muscle interface for eleven users without and three users with motor impairments performing continuous tasks. Both user groups preferred and performed better with the muscle versus the manual interface for the complex continuous task. These results suggest muscle interfaces and algorithms that can detect and augment user intent may be especially useful for future design of interfaces for continuous tasks.

Patient-based experiences with the use of an ambulatory electromyographic device for the assessment of masticatory muscle activity during sleep

Background

It is important to know how easy or difficult it is to use an ambulatory electromyographic (EMG) device for sleep bruxism assessment, and how this might affect its future utilisation.

Objective

To explore the experience of individuals using an EMG device that pairs with a smartphone app, in order to detect factors that could facilitate and/or hamper its utilisation in future scientific research.

Methods

Fifteen adults were recruited in the Orofacial Pain and Dysfunction Clinic of the Academic Centre for Dentistry Amsterdam (ACTA). Overnight recordings were performed in the home setting during one week. Time investment, feelings and thoughts, encountered difficulties and reasons for not using the device were assessed in a diary through open‐ended questions and 5‐point Likert scales. Content analysis of textual data was performed, and descriptives of quantitative data were calculated.

Results

Time investment was low (mean 10.2 minutes in the clinic, and 1.9 minutes per recording at home). Quantitative data showed an overall good experience (median of 4). Qualitative diary data showed that the desire to gain insight into one's masticatory muscle activity formed the main motivation to use the device. Device detachment and difficulty in using the app were the most prominent negative experiences.

Conclusion

The EMG device was well accepted for multiple overnight recordings. Curiosity for gaining insight into muscle activity was the most important factor that facilitated its use, and the app addressed this need. Device detachment and difficulties in using the app were the main factors that hampered its use.

Advanced technologies for intuitive control and sensation of prosthetics

The Department of Defense, Department of Veterans Affairs and National Institutes of Health have invested significantly in advancing prosthetic technologies over the past 25 years, with the overall intent to improve the function, participation and quality of life of Service Members, Veterans, and all United States Citizens living with limb loss. These investments have contributed to substantial advancements in the control and sensory perception of prosthetic devices over the past decade. While control of motorized prosthetic devices through the use of electromyography has been widely available since the 1980s, this technology is not intuitive. Additionally, these systems do not provide stimulation for sensory perception. Recent research has made significant advancement not only in the intuitive use of electromyography for control but also in the ability to provide relevant meaningful perceptions through various stimulation approaches. While much of this previous work has traditionally focused on those with upper extremity amputation, new developments include advanced bidirectional neuroprostheses that are applicable to both the upper and lower limb amputation. The goal of this review is to examine the state-of-the-science in the areas of intuitive control and sensation of prosthetic devices and to discuss areas of exploration for the future. Current research and development efforts in external systems, implanted systems, surgical approaches, and regenerative approaches will be explored.

putEMG-A Surface Electromyography Hand Gesture Recognition Dataset

In this paper, we present a putEMG dataset intended for the evaluation of hand gesture recognition methods based on sEMG signal. The dataset was acquired for 44 able-bodied subjects and include 8 gestures (3 full hand gestures, 4 pinches and idle). It consists of uninterrupted recordings of 24 sEMG channels from the subject's forearm, RGB video stream and depth camera images used for hand motion tracking. Moreover, exemplary processing scripts are also published. The putEMG dataset is available under a Creative Commons Attribution-NonCommercial 4.0 International (CC BY-NC 4.0). The dataset was validated regarding sEMG amplitudes and gesture recognition performance. The classification was performed using state-of-the-art classifiers and feature sets. An accuracy of 90% was achieved for SVM classifier utilising RMS feature and for LDA classifier using Hudgin's and Du's feature sets. Analysis of performance for particular gestures showed that LDA/Du combination has significantly higher accuracy for full hand gestures, while SVM/RMS performs better for pinch gestures. The presented dataset can be used as a benchmark for various classification methods, the evaluation of electrode localisation concepts, or the development of classification methods invariant to user-specific features or electrode displacement.

Ambulatory cardiac bio-signals: From mirage to clinical reality through a decade of progress

BACKGROUND

Health monitoring is shifting towards continuous, ambulatory and clinically comparable wearable devices. Telemedicine and remote diagnosis could harness the capability of mobile cardiac health information, as the technology on bio-physical signal monitoring has improved significantly.

OBJECTIVES

The purpose of this review article is (1) to systematically assess the viability of ambulatory electrocardiography (ECG), (2) to provide a systems level understanding of a broad spectrum of wearable heart signal monitoring approaches and (3) to identify areas of improvement in the existing technology needed to attain clinical grade diagnosis.

RESULTS

Based on the included literature, we have identified (1) that the developments in ECG monitoring through wearable devices are reaching feasibility, and are capable of delivering diagnostic and prognostic information, (2) that reliable sensing is the major bottleneck in the entire process of ambulatory monitoring, (3) that there is a strong need for artificial intelligence and machine learning techniques to parse and infer the biosignals and (4) that aspects of wearer comfort has largely been ignored in the prevailing developments, which can become a key factor for consumer acceptance.

CONCLUSIONS

Cardiac health information is crucial for diagnosis and prevention of several disease onsets. Mobile and continuous monitoring can aid avoiding risks involved with acute symptoms. The health information obtained through continuous monitoring can serve as the BigData of heart signals, and can facilitate new treatment methods and devise effective health policies.

Long-Term Modeling and Monitoring of Neuromusculoskeletal System Performance Using Tattoo-Like EMG Sensors

This paper introduces stretchable, long-term wearable, tattoo-like dry surface electrodes for highly repeatable electromyography (EMG). The tattoo-like sensors are hair thin, skin compliant and can be laminated on human skin just like a temporary transfer tattoo, which enables multi-day noninvasive but intimate contact with the skin even under severe skin deformation. The new electrodes were used to facilitate a system-based approach to tracking of long-term fatiguing and recovery processes in a human neuromusculoskeletal (NMS) system, which was based on establishing an autoregressive moving average model with exogenous inputs (ARMAX model) relating signatures extracted from the surface electromyogram (sEMG) signals collected using the tattoo-like sensors, and the corresponding hand grip force (HGF) serving as the model output. Performance degradation of the relevant NMS system was evaluated by tracking the evolution of the errors of the ARMAX model established using the data corresponding to the rested (fresh) state of any given subject. Results from several exercise sessions clearly showed repeated patterns of fatiguing and resting, with a notable point that these patterns could now be quantified via dynamic models relating the relevant muscle signatures and NMS outputs.

An analytic model of two-level compressive buckling with applications in the assembly of free-standing 3D mesostructures

Recently developed methods for mechanically-guided assembly exploit stress release in prestretched elastomeric substrates to guide the controlled formation of complex three-dimensional (3D) mesostructures in advanced functional materials and integrated electronic devices. The techniques of interfacial photopolymerization allow for realization of such 3D mesostructures in free-standing forms, separated from their elastomeric substrate, via formation of an integrated base layer. Theoretical models for the complex modes of deformation associated with this scheme are essential in the optimal design of the process parameters. Here, we present an analytic finite-deformation model of an isolated double-ribbon structure to describe the buckling process and morphology change of the assembled mesostructures upon removal of the substrate. As validated by finite element analyses (FEA), this analytic model can accurately predict the profiles of the double-ribbon structure with a range of different design parameters. We further illustrate the extension of this model to the analyses of 3D mesostructures with different geometries. Inspired by analytic results for flexible base structures, combined experimental results and numerical simulations demonstrate that mechanical interactions between the two different layers can be leveraged to achieve hierarchical assembly of 3D mesostructures. These findings could be useful in further advances in designs of free-standing 3D mesostructures based on mechanically-guided assembly.