Bioinspired iontronic synapse fibers for ultralow-power multiplexing neuromorphic sensorimotor textiles.

Artificial neuromorphic devices can emulate dendric integration, axonal parallel transmission, along with superior energy efficiency in facilitating efficient information processing, offering enormous potential for wearable electronics. However, integrating such circuits into textiles to achieve biomimetic information perception, processing, and control motion feedback remains a formidable challenge. Here, we engineer a quasi-solid-state iontronic synapse fiber (ISF) comprising photoresponsive TiO2, ion storage Co-MoS2, and an ion transport layer. The resulting ISF achieves inherent short-term synaptic plasticity, femtojoule-range energy consumption, and the ability to transduce chemical/optical signals. Multiple ISFs are interwoven into a synthetic neural fabric, allowing the simultaneous propagation of distinct optical signals for transmitting parallel information. Importantly, IFSs with multiple input electrodes exhibit spatiotemporal information integration. As a proof of concept, a textile-based multiplexing neuromorphic sensorimotor system is constructed to connect synaptic fibers with artificial fiber muscles, enabling preneuronal sensing information integration, parallel transmission, and postneuronal information output to control the coordinated motor of fiber muscles. The proposed fiber system holds enormous promise in wearable electronics, soft robotics, and biomedical engineering.

Skin-integrated systems for power efficient, programmable thermal sensations across large body areas.

Thermal sensations contribute to our ability to perceive and explore the physical world. Reproducing these sensations in a spatiotemporally programmable manner through wireless computer control could enhance virtual experiences beyond those supported by video, audio and, increasingly, haptic inputs. Flexible, lightweight and thin devices that deliver patterns of thermal stimulation across large areas of the skin at any location of the body are of great interest in this context. Applications range from those in gaming and remote socioemotional communications, to medical therapies and physical rehabilitation. Here, we present a set of ideas that form the foundations of a skin-integrated technology for power-efficient generation of thermal sensations across the skin, with real-time, closed-loop control. The systems exploit passive cooling mechanisms, actively switchable thermal barrier interfaces, thin resistive heaters and flexible electronics configured in a pixelated layout with wireless interfaces to portable devices, the internet and cloud data infrastructure. Systematic experimental studies and simulation results explore the essential mechanisms and guide the selection of optimized choices in design. Demonstration examples with human subjects feature active thermoregulation, virtual social interactions, and sensory expansion.

Closed-loop network of skin-interfaced wireless devices for quantifying vocal fatigue and providing user feedback.

Vocal fatigue is a measurable form of performance fatigue resulting from overuse of the voice and is characterized by negative vocal adaptation. Vocal dose refers to cumulative exposure of the vocal fold tissue to vibration. Professionals with high vocal demands, such as singers and teachers, are especially prone to vocal fatigue. Failure to adjust habits can lead to compensatory lapses in vocal technique and an increased risk of vocal fold injury. Quantifying and recording vocal dose to inform individuals about potential overuse is an important step toward mitigating vocal fatigue. Previous work establishes vocal dosimetry methods, that is, processes to quantify vocal fold vibration dose but with bulky, wired devices that are not amenable to continuous use during natural daily activities; these previously reported systems also provide limited mechanisms for real-time user feedback. This study introduces a soft, wireless, skin-conformal technology that gently mounts on the upper chest to capture vibratory responses associated with vocalization in a manner that is immune to ambient noises. Pairing with a separate, wirelessly linked device supports haptic feedback to the user based on quantitative thresholds in vocal usage. A machine learning-based approach enables precise vocal dosimetry from the recorded data, to support personalized, real-time quantitation and feedback. These systems have strong potential to guide healthy behaviors in vocal use.

Advancing Wearable Biosensors for Congenital Heart Disease: Patient and Clinician Perspectives: A Science Advisory From the American Heart Association.

Wearable biosensors (wearables) enable continual, noninvasive physiologic and behavioral monitoring at home for those with pediatric or congenital heart disease. Wearables allow patients to access their personal data and monitor their health. Despite substantial technologic advances in recent years, issues with hardware design, data analysis, and integration into the clinical workflow prevent wearables from reaching their potential in high-risk congenital heart disease populations. This science advisory reviews the use of wearables in patients with congenital heart disease, how to improve these technologies for clinicians and patients, and ethical and regulatory considerations. Challenges related to the use of wearables are common to every clinical setting, but specific topics for consideration in congenital heart disease are highlighted.

Electronic Skin: Opportunities and Challenges in Convergence with Machine Learning.

Recent advancements in soft electronic skin (e-skin) have led to the development of human-like devices that reproduce the skin's functions and physical attributes. These devices are being explored for applications in robotic prostheses as well as for collecting biopotentials for disease diagnosis and treatment, as exemplified by biomedical e-skins. More recently, machine learning (ML) has been utilized to enhance device control accuracy and data processing efficiency. The convergence of e-skin technologies with ML is promoting their translation into clinical practice, especially in healthcare. This review highlights the latest developments in ML-reinforced e-skin devices for robotic prostheses and biomedical instrumentations. We first describe technological breakthroughs in state-of-the-art e-skin devices, emphasizing technologies that achieve skin-like properties. We then introduce ML methods adopted for control optimization and pattern recognition, followed by practical applications that converge the two technologies. Lastly, we briefly discuss the challenges this interdisciplinary research encounters in its clinical and industrial transition.

Wearable Devices in Cardiovascular Medicine.

Wearable devices, such as smartwatches and activity trackers, are commonly used by patients in their everyday lives to manage their health and well-being. These devices collect and analyze long-term continuous data on measures of behavioral or physiologic function, which may provide clinicians with a more comprehensive view of a patients' health compared with the traditional sporadic measures captured by office visits and hospitalizations. Wearable devices have a wide range of potential clinical applications ranging from arrhythmia screening of high-risk individuals to remote management of chronic conditions such as heart failure or peripheral artery disease. As the use of wearable devices continues to grow, we must adopt a multifaceted approach with collaboration among all key stakeholders to effectively and safely integrate these technologies into routine clinical practice. In this Review, we summarize the features of wearable devices and associated machine learning techniques. We describe key research studies that illustrate the role of wearable devices in the screening and management of cardiovascular conditions and identify directions for future research. Last, we highlight the challenges that are currently hindering the widespread use of wearable devices in cardiovascular medicine and provide short- and long-term solutions to promote increased use of wearable devices in clinical care.

Motor network gamma oscillations in chronic home recordings predict dyskinesia in Parkinson's disease.

In Parkinson's disease, imbalances between 'antikinetic' and 'prokinetic' patterns of neuronal oscillatory activity are related to motor dysfunction. Invasive brain recordings from the motor network have suggested that medical or surgical therapy can promote a prokinetic state by inducing narrowband gamma rhythms (65-90 Hz). Excessive narrowband gamma in the motor cortex promotes dyskinesia in rodent models, but the relationship between narrowband gamma and dyskinesia in humans has not been well established. To assess this relationship, we used a sensing-enabled deep brain stimulator system, attached to both motor cortex and basal ganglia (subthalamic or pallidal) leads, paired with wearable devices that continuously tracked motor signs in the contralateral upper limbs. We recorded 984 h of multisite field potentials in 30 hemispheres of 16 subjects with Parkinson's disease (2/16 female, mean age 57 ± 12 years) while at home on usual antiparkinsonian medications. Recordings were done 2-4 weeks after implantation, prior to starting therapeutic stimulation. Narrowband gamma was detected in the precentral gyrus, subthalamic nucleus or both structures on at least one side of 92% of subjects with a clinical history of dyskinesia. Narrowband gamma was not detected in the globus pallidus. Narrowband gamma spectral power in both structures co-fluctuated similarly with contralateral wearable dyskinesia scores (mean correlation coefficient of ρ = 0.48 with a range of 0.12-0.82 for cortex, ρ = 0.53 with a range of 0.5-0.77 for subthalamic nucleus). Stratification analysis showed the correlations were not driven by outlier values, and narrowband gamma could distinguish 'on' periods with dyskinesia from 'on' periods without dyskinesia. Time lag comparisons confirmed that gamma oscillations herald dyskinesia onset without a time lag in either structure when using 2-min epochs. A linear model incorporating the three oscillatory bands (beta, theta/alpha and narrowband gamma) increased the predictive power of dyskinesia for several subject hemispheres. We further identified spectrally distinct oscillations in the low gamma range (40-60 Hz) in three subjects, but the relationship of low gamma oscillations to dyskinesia was variable. Our findings support the hypothesis that excessive oscillatory activity at 65-90 Hz in the motor network tracks with dyskinesia similarly across both structures, without a detectable time lag. This rhythm may serve as a promising control signal for closed-loop deep brain stimulation using either cortical or subthalamic detection.

Logic-enabled textiles.

Textiles hold great promise as a soft yet durable material for building comfortable robotic wearables and assistive devices at low cost. Nevertheless, the development of smart wearables composed entirely of textiles has been hindered by the lack of a viable sheet-based logic architecture that can be implemented using conventional fabric materials and textile manufacturing processes. Here, we develop a fully textile platform for embedding pneumatic digital logic in wearable devices. Our logic-enabled textiles support combinational and sequential logic functions, onboard memory storage, user interaction, and direct interfacing with pneumatic actuators. In addition, they are designed to be lightweight, easily integrable into regular clothing, made using scalable fabrication techniques, and durable enough to withstand everyday use. We demonstrate a textile computer capable of input-driven digital logic for controlling untethered wearable robots that assist users with functional limitations. Our logic platform will facilitate the emergence of future wearables powered by embedded fluidic logic that fully leverage the innate advantages of their textile construction.

Therapy duration and improvement of ventricular function in de novo heart failure: the Heart Failure Optimization study.

BACKGROUND AND AIMS: In patients with de novo heart failure with reduced ejection fraction (HFrEF), improvement of left ventricular ejection fraction (LVEF) is expected to occur when started on guideline-recommended medical therapy. However, improvement may not be completed within 90 days. METHODS: Patients with HFrEF and LVEF ≤ 35% prescribed a wearable cardioverter-defibrillator between 2017 and 2022 from 68 sites were enrolled, starting with a registry phase for 3 months and followed by a study phase up to 1 year. The primary endpoints were LVEF improvement > 35% between Days 90 and 180 following guideline-recommended medical therapy initiation and the percentage of target dose reached at Days 90 and 180. RESULTS: A total of 598 patients with de novo HFrEF [59 years (interquartile range 51-68), 27% female] entered the study phase. During the first 180 days, a significant increase in dosage of beta-blockers, renin-angiotensin system inhibitors, and mineralocorticoid receptor antagonists was observed (P < .001). At Day 90, 46% [95% confidence interval (CI) 41%-50%] of study phase patients had LVEF improvement > 35%; 46% (95% CI 40%-52%) of those with persistently low LVEF at Day 90 had LVEF improvement > 35% by Day 180, increasing the total rate of improvement > 35% to 68% (95% CI 63%-72%). In 392 patients followed for 360 days, improvement > 35% was observed in 77% (95% CI 72%-81%) of the patients. Until Day 90, sustained ventricular tachyarrhythmias were observed in 24 wearable cardioverter-defibrillator carriers (1.8%). After 90 days, no sustained ventricular tachyarrhythmia occurred in wearable cardioverter-defibrillator carriers. CONCLUSIONS: Continuous optimization of guideline-recommended medical therapy for at least 180 days in HFrEF is associated with additional LVEF improvement > 35%, allowing for better decision-making regarding preventive implantable cardioverter-defibrillator therapy.

Prognostic value of ventricular arrhythmia in early post-infarction left ventricular dysfunction: the French nationwide WICD-MI study.

BACKGROUND AND AIMS: Prophylactic implantable cardioverter-defibrillators (ICDs) are not recommended until left ventricular ejection fraction (LVEF) has been reassessed 40 to 90 days after an acute myocardial infarction. In the current therapeutic era, the prognosis of sustained ventricular arrhythmias (VAs) occurring during this early post-infarction phase (i.e. within 3 months of hospital discharge) has not yet been specifically evaluated in post-myocardial infarction patients with impaired LVEF. Such was the aim of this retrospective study. METHODS: Data analysis was based on a nationwide registry of 1032 consecutive patients with LVEF ≤ 35% after acute myocardial infarction who were implanted with an ICD after being prescribed a wearable cardioverter-defibrillator (WCD) for a period of 3 months upon discharge from hospital after the index infarction. RESULTS: ICDs were implanted either because a sustained VA occurred while on WCD (VA+/WCD, n = 72) or because LVEF remained ≤35% at the end of the early post-infarction phase (VA-/WCD, n = 960). The median follow-up was 30.9 months. Sustained VAs occurred within 1 year after ICD implantation in 22.2% and 3.5% of VA+/WCD and VA-/WCD patients, respectively (P < .0001). The adjusted multivariable analysis showed that sustained VAs while on WCD independently predicted recurrence of sustained VAs at 1 year (adjusted hazard ratio [HR] 6.91; 95% confidence interval [CI] 3.73-12.81; P < .0001) and at the end of follow-up (adjusted HR 3.86; 95% CI 2.37-6.30; P < .0001) as well as 1-year mortality (adjusted HR 2.86; 95% CI 1.28-6.39; P = .012). CONCLUSIONS: In patients with LVEF ≤ 35%, sustained VA during the early post-infarction phase is predictive of recurrent sustained VAs and 1-year mortality.

Robust and Environmentally Friendly MXene-Based Electronic Skin Enabling the Three Essential Functions of Natural Skin: Perception, Protection, and Thermoregulation.

The development of electronic skin (e-skin) emulating the human skin's three essential functions (perception, protection, and thermoregulation) has great potential for human-machine interfaces and intelligent robotics. However, existing studies mainly focus on perception. This study presents a novel, eco-friendly, mechanically robust e-skin replicating human skin's three essential functions. The e-skin is composed of Ti3C2Tx MXene, polypyrrole, and bacterial cellulose nanofibers, where the MXene nanoflakes form the matrix, the bacterial cellulose nanofibers act as the filler, and the polypyrrole serves as a conductive "cross-linker". This design allows customization of the electrical conductivity, microarchitecture, and mechanical properties, integrating sensing (perception), EMI shielding (protection), and thermal management (thermoregulation). The optimal e-skin can effectively sense various motions (including minuscule artery pulses), achieve an EMI shielding efficiency of 63.32 dB at 78 µm thickness, and regulate temperature up to 129 °C in 30 s at 2.4 V, demonstrating its potential for smart robotics in complex scenarios.

Jellyfish-like Gold Nanowires as FlexoSERS Sensors for Sweat Analysis.

We introduce the FlexoSERS sensor, which is notable for its high stretchability, sensitivity, and patternability. Featuring a hierarchically oriented jellyfish-like architecture constructed from stretchable gold nanowires, this sensor provides an ultrasensitive SERS signal even under 50% strain, with an enhancement factor (EF) of 3.3 × 1010. Impressively, this heightened performance remains consistently robust across 2,500 stretch-release cycles. The integration of nanowires with 3D-printed hydrogel enables a customizable FlexoSERS sensor, facilitating localized sweat collection and detection. The FlexoSERS sensor successfully detects and quantifies uric acid (UA) in both artificial and human sweat and functions as a pH sensor with repeatability and sensitivity across a pH range of 4.2-7.8, enabling real-time sweat monitoring during exercise. In summary, the rational architectural design, scalable fabrication process, and hydrogel integration collectively position this nanowire-based FlexoSERS sensor as a highly promising platform for customizable wearable sweat diagnostics.

Wood Cell Wall Nanoengineering toward Anisotropic, Strong, and Flexible Cellulosic Hydrogel Sensors.

Achieving highly ionic conductive hydrogels from natural wood remains challenging owing to their insufficient surface area and low number of active sites on the cell wall. This study proposes a viable strategy to design a strong and anisotropic wood-based hydrogel through cell wall nanoengineering. By manipulating the microstructure of the wood cell wall, a flexible cellulosic hydrogel is achieved through Schiff base bonding via the polyacrylamide and cellulose molecular chains. This results in excellent flexibility and mechanical properties of the wood hydrogel with tensile strengths of 22.3 and 6.1 MPa in the longitudinal and transverse directions, respectively. Moreover, confining aqueous salt electrolytes within the porous structure gives anisotropic ionic conductivities (19.5 and 6.02 S/m in the longitudinal and transverse directions, respectively). The wood-based hydrogel sensor has a favorable sensitivity and a stable working performance at a low temperature of -25 °C in monitoring human motions, thereby demonstrating great potential applications in wearable sensor devices.

Stretchable and Breathable Electroluminescent Displays Based on Ultrathin Nanocomposite Designs.

Stretchable electroluminescent devices represent an emerging optoelectronic technology for future wearables. However, their typical construction on sub-millimeter-thick elastomers has limited moisture permeability, leading to discomfort during long-term skin attachment. Although breathable textile displays may partially address this issue, they often have distinct visual appearances with discrete emissions from fibers or fiber junctions. This study introduces a convenient procedure to create stretchable, permeable displays with continuous luminous patterns. The design utilizes ultrathin nanocomposite devices embedded in a porous elastomeric microfoam to achieve high moisture permeability. These displays also exhibit excellent deformability, low-voltage operation, and excellent durability. Additionally, the device is decorated with fluorinated silica nanoparticles to achieve self-cleaning and washable capabilities. The practical implementation of these nanocomposite devices is demonstrated by creating an epidermal counter display that allows intimate integration with the human body. These developments provide an effective design of stretchable and breathable displays for comfortable wearing.

Patterned Gold Nanoparticle Superlattice Film for Wearable Sweat Sensors.

Nanoparticle superlattices are beneficial in terms of providing strong and uniform signals in analysis owing to their closely packed uniform structures. However, nanoparticle superlattices are prone to cracking during physical activities because of stress concentrations, which hinders their detection performance and limits their analytical applications. In this work, template printing methods were used in this study to prepare a patterned gold nanoparticle (AuNP) superlattice film. By adjustment of the size of the AuNP superlattice domain below the critical size of fracture, the mechanical stability of the AuNP superlattice domain is improved. Thus, long-term sustainable high-performance signal output is achieved. The patterned AuNP superlattice film was used to construct a wearable sweat sensor based on surface-enhanced Raman scattering (SERS). The designed sensor showed promise for long-term reliable use in actual scenarios in terms of recommending water replenishment, monitoring hydration states, and tracking the intensity of activity.

HEROIC: a platform for remote collection of electroencephalographic data using consumer-grade brain wearables.

The growing number of portable consumer-grade electroencephalography (EEG) wearables offers potential to track brain activity and neurological disease in real-world environments. However, accompanying open software tools to standardize custom recordings and help guide independent operation by users is lacking. To address this gap, we developed HEROIC, an open-source software that allows participants to remotely collect advanced EEG data without the aid of an expert technician. The aim of HEROIC is to provide an open software platform that can be coupled with consumer grade wearables to record EEG data during customized neurocognitive tasks outside of traditional research environments. This article contains a description of HEROIC's implementation, how it can be used by researchers and a proof-of-concept demonstration highlighting the potential for HEROIC to be used as a scalable and low-cost EEG data collection tool. Specifically, we used HEROIC to guide healthy participants through standardized neurocognitive tasks and captured complex brain data including event-related potentials (ERPs) and powerband changes in participants' homes. Our results demonstrate HEROIC's capability to generate data precisely synchronized to presented stimuli, using a low-cost, remote protocol without reliance on an expert operator to administer sessions. Together, our software and its capabilities provide the first democratized and scalable platform for large-scale remote and longitudinal analysis of brain health and disease.

Unrevealing the connection between real sample analysis and analytical method. The case of cytokines.

Cytokines are compounds that belong to a special class of signaling biomolecules that are responsible for several functions in the human body, being involved in cell growth, inflammatory, and neoplastic processes. Thus, they represent valuable biomarkers for diagnosing and drug therapy monitoring certain medical conditions. Because cytokines are secreted in the human body, they can be detected in both conventional samples, such as blood or urine, but also in samples less used in medical practice such as sweat or saliva. As the importance of cytokines was identified, various analytical methods for their determination in biological fluids were reported. The gold standard in cytokine detection is considered the enzyme-linked immunosorbent assay method and the most recent ones have been considered and compared in this study. It is known that the conventional methods are accompanied by a few disadvantages that new methods of analysis, especially electrochemical sensors, are trying to overcome. Electrochemical sensors proved to be suited for the elaboration of integrated, portable, and wearable sensing devices, which could also facilitate cytokines determination in medical practice.

Differential components of bradykinesia in Parkinson's disease revealed by deep brain stimulation.

Bradykinesia is a term describing several manifestations of movement disruption caused by Parkinson's disease (PD), including movement slowing, amplitude reduction, and gradual decrease of speed and amplitude over multiple repetitions of the same movement. Deep brain stimulation (DBS) of the subthalamic nucleus (STN) improves bradykinesia in patients with PD. We examined the effect of DBS on specific components of bradykinesia when applied at two locations within the STN, using signal processing techniques to identify the time course of amplitude and frequency of repeated hand pronation-supination movements performed by participants with and without PD. Stimulation at either location increased movement amplitude, increased frequency, and decreased variability, though not to the range observed in the control group. Amplitude and frequency showed decrement within trials, which was similar in PD and control groups and did not change with DBS. Decrement across trials, by contrast, differed between PD and control groups, and was reduced by stimulation. We conclude that DBS improves specific aspects of movement that are disrupted by PD, whereas it does not affect short-term decrement that could reflect muscular fatigue.NEW & NOTEWORTHY In this study, we examined different components of bradykinesia in patients with Parkinson's disease (PD). We identified different components through signal processing techniques and their response to deep brain stimulation (DBS). We found that some components of bradykinesia respond to stimulation, whereas others do not. This knowledge advances our understanding of brain mechanisms that control movement speed and amplitude.

Joint associations of diet and physical activity with incident type 2 diabetes and hypertension: an analysis of 144,288 UK Biobank participants.

BACKGROUND: Studies examining the joint associations of lifestyle exposures can reveal novel synergistic and joint effects, but no study has examined the joint association of diet and physical activity (PA) with type 2 diabetes (T2D) and hypertension. The aim of this study is to examine the joint associations of PA and diet with incidence of type T2D and hypertension, as a combined outcome and separately in a large sample of UK adults. METHODS: This prospective cohort study included 144,288 UK Biobank participants aged 40-69. Moderate to vigorous PA (MVPA) was measured using the International Physical Activity Questionnaire and a wrist accelerometer. We categorised PA and diet indicators (diet quality score (DQS) and energy intake (EI)) based on tertiles and derived joint PA and diet variables. Outcome was major cardiometabolic disease incidence (combination of T2D and hypertension). RESULTS: A total of 14,003(7.1%) participants developed T2D, 28,075(19.2%) developed hypertension, and 30,529(21.2%) developed T2D or hypertension over a mean follow-up of 10.9(3.7) years. Participants with middle and high self-reported MVPA levels had lower risk of major cardiometabolic disease regardless of diet, e.g. among high DQS group, hazard ratios in middle and high MVPA group were 0.90 (95%CI:0.86-0.94), and 0.88(95%CI:0.84-0.92), respectively. Participants with jointly high device-measured MVPA and high DQS levels had lower major cardiometabolic disease risk (HR: 0.84, 95%CI:0.71-0.99). The equivalent joint device-measured MVPA and EI exposure analyses showed no clear pattern of associations with the outcomes. CONCLUSION: Higher PA is an important component in cardiometabolic disease prevention across all diet quality and total EI groups. The observed lack of association between diet health outcomes may stem from a lower DQS.

The Use of Wearable Devices in Oncology Patients: A Systematic Review.

INTRODUCTION: The aim of this systematic review was to summarize the current literature on wearable technologies in oncology patients for the purpose of prognostication, treatment monitoring, and rehabilitation planning. METHODS: A search was conducted in Medline ALL, Cochrane Central Register of Controlled Trials, Embase, Emcare, CINAHL, Scopus, and Web of Science, up until February 2022. Articles were included if they reported on consumer grade and/or non-commercial wearable devices in the setting of either prognostication, treatment monitoring or rehabilitation. RESULTS: We found 199 studies reporting on 18 513 patients suitable for inclusion. One hundred and eleven studies used wearable device data primarily for the purposes of rehabilitation, 68 for treatment monitoring, and 20 for prognostication. The most commonly-reported brands of wearable devices were ActiGraph (71 studies; 36%), Fitbit (37 studies; 19%), Garmin (13 studies; 7%), and ActivPAL (11 studies; 6%). Daily minutes of physical activity were measured in 121 studies (61%), and daily step counts were measured in 93 studies (47%). Adherence was reported in 86 studies, and ranged from 40% to 100%; of these, 63 (74%) reported adherence in excess of 80%. CONCLUSION: Wearable devices may provide valuable data for the purposes of treatment monitoring, prognostication, and rehabilitation. Future studies should investigate live-time monitoring of collected data, which may facilitate directed interventions.