Soft, skin-interfaced microfluidic systems with integrated immunoassays, fluorometric sensors, and impedance measurement capabilities.

Soft microfluidic systems that capture, store, and perform biomarker analysis of microliter volumes of sweat, in situ, as it emerges from the surface of the skin, represent an emerging class of wearable technology with powerful capabilities that complement those of traditional biophysical sensing devices. Recent work establishes applications in the real-time characterization of sweat dynamics and sweat chemistry in the context of sports performance and healthcare diagnostics. This paper presents a collection of advances in biochemical sensors and microfluidic designs that support multimodal operation in the monitoring of physiological signatures directly correlated to physical and mental stresses. These wireless, battery-free, skin-interfaced devices combine lateral flow immunoassays for cortisol, fluorometric assays for glucose and ascorbic acid (vitamin C), and digital tracking of skin galvanic responses. Systematic benchtop evaluations and field studies on human subjects highlight the key features of this platform for the continuous, noninvasive monitoring of biochemical and biophysical correlates of the stress state.

Sweating Rate and Sweat Chloride Concentration of Elite Male Basketball Players Measured With a Wearable Microfluidic Device Versus the Standard Absorbent Patch Method.

The purpose of this study was to compare a wearable microfluidic device and standard absorbent patch in measuring local sweating rate (LSR) and sweat chloride concentration ([Cl-]) in elite basketball players. Participants were 53 male basketball players (25 ± 3 years, 92.2 ± 10.4 kg) in the National Basketball Association's development league. Players were tested during a moderate-intensity, coach-led practice (98 ± 30 min, 21.0 ± 1.2 °C). From the right ventral forearm, sweat was collected using an absorbent patch (3M Tegaderm™ + Pad). Subsequently, LSR and local sweat [Cl-] were determined via gravimetry and ion chromatography. From the left ventral forearm, LSR and local sweat [Cl-] were measured using a wearable microfluidic device and associated smartphone application-based algorithms. Whole-body sweating rate (WBSR) was determined from pre- to postexercise change in body mass corrected for fluid/food intake (ad libitum), urine loss, and estimated respiratory water and metabolic mass loss. The WBSR values predicted by the algorithms in the smartphone application were also recorded. There were no differences between the absorbent patch and microfluidic patch for LSR (1.25 ± 0.91 mg·cm-2·min-1 vs. 1.14 ±0.78 mg·cm-2·min-1, p = .34) or local sweat [Cl-] (30.6 ± 17.3 mmol/L vs. 29.6 ± 19.4 mmol/L, p = .55). There was no difference between measured and predicted WBSR (0.97 ± 0.41 L/hr vs. 0.89 ± 0.35 L/hr, p = .22; 95% limits of agreement = 0.61 L/hr). The wearable microfluidic device provides similar LSR, local sweat [Cl-], and WBSR results compared with standard field-based methods in elite male basketball players during moderate-intensity practices.

Age-related degradation of tectorial membrane dynamics with loss of CEACAM16.

Studies of genetic disorders of sensorineural hearing loss have been instrumental in delineating mechanisms that underlie the remarkable sensitivity and selectivity that are hallmarks of mammalian hearing. For example, genetic modifications of TECTA and TECTB, which are principal proteins that comprise the tectorial membrane (TM), have been shown to alter auditory thresholds and frequency tuning in ways that can be understood in terms of changes in the mechanical properties of the TM. Here, we investigate effects of genetic modification targeting CEACAM16, a third important TM protein. Loss of CEACAM16 has been recently shown to lead to progressive reductions in sensitivity. Whereas age-related hearing losses have previously been linked to changes in sensory receptor cells, the role of the TM in progressive hearing loss is largely unknown. Here, we show that TM stiffness and viscosity are significantly reduced in adult mice that lack functional CEACAM16 relative to age-matched wild-type controls. By contrast, these same mechanical properties of TMs from juvenile mice that lack functional CEACAM16 are more similar to those of wild-type mice. Thus, changes in hearing phenotype align with changes in TM material properties and can be understood in terms of the same TM wave properties that were previously used to characterize modifications of TECTA and TECTB. These results demonstrate that CEACAM16 is essential for maintaining TM mechanical and wave properties, which in turn are necessary for sustaining the remarkable sensitivity and selectivity of mammalian hearing with increasing age.

Bio-Integrated Wearable Systems: A Comprehensive Review.

Bio-integrated wearable systems can measure a broad range of biophysical, biochemical, and environmental signals to provide critical insights into overall health status and to quantify human performance. Recent advances in material science, chemical analysis techniques, device designs, and assembly methods form the foundations for a uniquely differentiated type of wearable technology, characterized by noninvasive, intimate integration with the soft, curved, time-dynamic surfaces of the body. This review summarizes the latest advances in this emerging field of "bio-integrated" technologies in a comprehensive manner that connects fundamental developments in chemistry, material science, and engineering with sensing technologies that have the potential for widespread deployment and societal benefit in human health care. An introduction to the chemistries and materials for the active components of these systems contextualizes essential design considerations for sensors and associated platforms that appear in following sections. The subsequent content highlights the most advanced biosensors, classified according to their ability to capture biophysical, biochemical, and environmental information. Additional sections feature schemes for electrically powering these sensors and strategies for achieving fully integrated, wireless systems. The review concludes with an overview of key remaining challenges and a summary of opportunities where advances in materials chemistry will be critically important for continued progress.

Recent progress, challenges, and opportunities for wearable biochemical sensors for sweat analysis.

Sweat is a promising, yet relatively unexplored biofluid containing biochemical information that offers broad insights into the underlying dynamic metabolic activity of the human body. The rich composition of electrolytes, metabolites, hormones, proteins, nucleic acids, micronutrients, and exogenous agents found in sweat dynamically vary in response to the state of health, stress, and diet. Emerging classes of skin-interfaced wearable sensors offer powerful capabilities for the real-time, continuous analysis of sweat produced by the eccrine glands in a manner suitable for use in athletics, consumer wellness, military, and healthcare industries. This perspective examines the rapid and continuous progress of wearable sweat sensors through the most advanced embodiments that address the fundamental challenges currently restricting widespread deployment. It concludes with a discussion of efforts to expand the overall utility of wearable sweat sensors and opportunities for commercialization, in which advances in biochemical sensor technologies will be critically important.

Relation between blood pressure and pulse wave velocity for human arteries.

Continuous monitoring of blood pressure, an essential measure of health status, typically requires complex, costly, and invasive techniques that can expose patients to risks of complications. Continuous, cuffless, and noninvasive blood pressure monitoring methods that correlate measured pulse wave velocity (PWV) to the blood pressure via the Moens-Korteweg (MK) and Hughes Equations, offer promising alternatives. The MK Equation, however, involves two assumptions that do not hold for human arteries, and the Hughes Equation is empirical, without any theoretical basis. The results presented here establish a relation between the blood pressure P and PWV that does not rely on the Hughes Equation nor on the assumptions used in the MK Equation. This relation degenerates to the MK Equation under extremely low blood pressures, and it accurately captures the results of in vitro experiments using artificial blood vessels at comparatively high pressures. For human arteries, which are well characterized by the Fung hyperelastic model, a simple formula between P and PWV is established within the range of human blood pressures. This formula is validated by literature data as well as by experiments on human subjects, with applicability in the determination of blood pressure from PWV in continuous, cuffless, and noninvasive blood pressure monitoring systems.

Motion microscopy for visualizing and quantifying small motions.

Although the human visual system is remarkable at perceiving and interpreting motions, it has limited sensitivity, and we cannot see motions that are smaller than some threshold. Although difficult to visualize, tiny motions below this threshold are important and can reveal physical mechanisms, or be precursors to large motions in the case of mechanical failure. Here, we present a "motion microscope," a computational tool that quantifies tiny motions in videos and then visualizes them by producing a new video in which the motions are made large enough to see. Three scientific visualizations are shown, spanning macroscopic to nanoscopic length scales. They are the resonant vibrations of a bridge demonstrating simultaneous spatial and temporal modal analysis, micrometer vibrations of a metamaterial demonstrating wave propagation through an elastic matrix with embedded resonating units, and nanometer motions of an extracellular tissue found in the inner ear demonstrating a mechanism of frequency separation in hearing. In these instances, the motion microscope uncovers hidden dynamics over a variety of length scales, leading to the discovery of previously unknown phenomena.

Role of data measurement characteristics in the accurate detection of Parkinson's disease symptoms using wearable sensors.

BACKGROUND: Parkinson's disease (PD) is a progressive neurological disease, with characteristic motor symptoms such as tremor and bradykinesia. There is a growing interest to continuously monitor these and other symptoms through body-worn sensor technology. However, limited battery life and memory capacity hinder the potential for continuous, long-term monitoring with these devices. There is little information available on the relative value of adding sensors, increasing sampling rate, or computing complex signal features, all of which may improve accuracy of symptom detection at the expense of computational resources. Here we build on a previous study to investigate the relationship between data measurement characteristics and accuracy when using wearable sensor data to classify tremor and bradykinesia in patients with PD. METHODS: Thirteen individuals with PD wore a flexible, skin-mounted sensor (collecting tri-axial accelerometer and gyroscope data) and a commercial smart watch (collecting tri-axial accelerometer data) on their predominantly affected hand. The participants performed a series of standardized motor tasks, during which a clinician scored the severity of tremor and bradykinesia in that limb. Machine learning models were trained on scored data to classify tremor and bradykinesia. Model performance was compared when using different types of sensors (accelerometer and/or gyroscope), different data sampling rates (up to 62.5 Hz), and different categories of pre-engineered features (up to 148 features). Performance was also compared between the flexible sensor and smart watch for each analysis. RESULTS: First, there was no effect of device type for classifying tremor symptoms (p > 0.34), but bradykinesia models incorporating gyroscope data performed slightly better (up to 0.05 AUROC) than other models (p = 0.01). Second, model performance decreased with sampling frequency (p < 0.001) for tremor, but not bradykinesia (p > 0.47). Finally, model performance for both symptoms was maintained after substantially reducing the feature set. CONCLUSIONS: Our findings demonstrate the ability to simplify measurement characteristics from body-worn sensors while maintaining performance in PD symptom detection. Understanding the trade-off between model performance and data resolution is crucial to design efficient, accurate wearable sensing systems. This approach may improve the feasibility of long-term, continuous, and real-time monitoring of PD symptoms by reducing computational burden on wearable devices.

Nanoscale Poroelasticity of the Tectorial Membrane Determines Hair Bundle Deflections.

Stereociliary imprints in the tectorial membrane (TM) have been taken as evidence that outer hair cells are sensitive to shearing displacements of the TM, which plays a key role in shaping cochlear sensitivity and frequency selectivity via resonance and traveling wave mechanisms. However, the TM is highly hydrated (97% water by weight), suggesting that the TM may be flexible even at the level of single hair cells. Here we show that nanoscale oscillatory displacements of microscale spherical probes in contact with the TM are resisted by frequency-dependent forces that are in phase with TM displacement at low and high frequencies, but are in phase with TM velocity at transition frequencies. The phase lead can be as much as a quarter of a cycle, thereby contributing to frequency selectivity and stability of cochlear amplification.

Counting Bites With Bits: Expert Workshop Addressing Calorie and Macronutrient Intake Monitoring.

BACKGROUND: Conventional diet assessment approaches such as the 24-hour self-reported recall are burdensome, suffer from recall bias, and are inaccurate in estimating energy intake. Wearable sensor technology, coupled with advanced algorithms, is increasingly showing promise in its ability to capture behaviors that provide useful information for estimating calorie and macronutrient intake. OBJECTIVE: This paper aimed to summarize current technological approaches to monitoring energy intake on the basis of expert opinion from a workshop panel and to make recommendations to advance technology and algorithms to improve estimation of energy expenditure. METHODS: A 1-day invitational workshop sponsored by the National Science Foundation was held at Northwestern University. A total of 30 participants, including population health researchers, engineers, and intervention developers, from 6 universities and the National Institutes of Health participated in a panel discussing the state of evidence with regard to monitoring calorie intake and eating behaviors. RESULTS: Calorie monitoring using technological approaches can be characterized into 3 domains: (1) image-based sensing (eg, wearable and smartphone-based cameras combined with machine learning algorithms); (2) eating action unit (EAU) sensors (eg, to measure feeding gesture and chewing rate); and (3) biochemical measures (eg, serum and plasma metabolite concentrations). We discussed how each domain functions, provided examples of promising solutions, and highlighted potential challenges and opportunities in each domain. Image-based sensor research requires improved ground truth (context and known information about the foods), accurate food image segmentation and recognition algorithms, and reliable methods of estimating portion size. EAU-based domain research is limited by the understanding of when their systems (device and inference algorithm) succeed and fail, need for privacy-protecting methods of capturing ground truth, and uncertainty in food categorization. Although an exciting novel technology, the challenges of biochemical sensing range from a lack of adaptability to environmental effects (eg, temperature change) and mechanical impact, instability of wearable sensor performance over time, and single-use design. CONCLUSIONS: Conventional approaches to calorie monitoring rely predominantly on self-reports. These approaches can gain contextual information from image-based and EAU-based domains that can map automatically captured food images to a food database and detect proxies that correlate with food volume and caloric intake. Although the continued development of advanced machine learning techniques will advance the accuracy of such wearables, biochemical sensing provides an electrochemical analysis of sweat using soft bioelectronics on human skin, enabling noninvasive measures of chemical compounds that provide insight into the digestive and endocrine systems. Future computing-based researchers should focus on reducing the burden of wearable sensors, aligning data across multiple devices, automating methods of data annotation, increasing rigor in studying system acceptability, increasing battery lifetime, and rigorously testing validity of the measure. Such research requires moving promising technological solutions from the controlled laboratory setting to the field.

Augmenting Clinical Outcome Measures of Gait and Balance with a Single Inertial Sensor in Age-Ranged Healthy Adults.

Gait and balance impairments are linked with reduced mobility and increased risk of falling. Wearable sensing technologies, such as inertial measurement units (IMUs), may augment clinical assessments by providing continuous, high-resolution data. This study tested and validated the utility of a single IMU to quantify gait and balance features during routine clinical outcome tests, and evaluated changes in sensor-derived measurements with age, sex, height, and weight. Age-ranged, healthy individuals (N = 49, 20-70 years) wore a lower back IMU during the 10 m walk test (10MWT), Timed Up and Go (TUG), and Berg Balance Scale (BBS). Spatiotemporal gait parameters computed from the sensor data were validated against gold standard measures, demonstrating excellent agreement for stance time, step time, gait velocity, and step count (intraclass correlation (ICC) > 0.90). There was good agreement for swing time (ICC = 0.78) and moderate agreement for step length (ICC = 0.68). A total of 184 features were calculated from the acceleration and angular velocity signals across these tests, 36 of which had significant correlations with age. This approach was also demonstrated for an individual with stroke, providing higher resolution information about balance, gait, and mobility than the clinical test scores alone. Leveraging mobility data from wireless, wearable sensors can help clinicians and patients more objectively pinpoint impairments, track progression, and set personalized goals during and after rehabilitation.

Soft, Skin-Interfaced Microfluidic Systems with Wireless, Battery-Free Electronics for Digital, Real-Time Tracking of Sweat Loss and Electrolyte Composition.

Sweat excretion is a dynamic physiological process that varies with body position, activity level, environmental factors, and health status. Conventional means for measuring the properties of sweat yield accurate results but their requirements for sampling and analytics do not allow for use in the field. Emerging wearable devices offer significant advantages over existing approaches, but each has significant drawbacks associated with bulk and weight, inability to quantify volumetric sweat rate and loss, robustness, and/or inadequate accuracy in biochemical analysis. This paper presents a thin, miniaturized, skin-interfaced microfluidic technology that includes a reusable, battery-free electronics module for measuring sweat conductivity and rate in real-time using wireless power from and data communication to electronic devices with capabilities in near field communications (NFC), including most smartphones. The platform exploits ultrathin electrodes integrated within a collection of microchannels as interfaces to circuits that leverage NFC protocols. The resulting capabilities are complementary to those of previously reported colorimetric strategies. Systematic studies of these combined microfluidic/electronic systems, accurate correlations of measurements performed with them to those of laboratory standard instrumentation, and field tests on human subjects exercising and at rest establish the key operational features and their utility in sweat analytics.

Longitudinal spread of mechanical excitation through tectorial membrane traveling waves.

The mammalian inner ear separates sounds by their frequency content, and this separation underlies important properties of human hearing, including our ability to understand speech in noisy environments. Studies of genetic disorders of hearing have demonstrated a link between frequency selectivity and wave properties of the tectorial membrane (TM). To understand these wave properties better, we developed chemical manipulations that systematically and reversibly alter TM stiffness and viscosity. Using microfabricated shear probes, we show that (i) reducing pH reduces TM stiffness with little change in TM viscosity and (ii) adding PEG increases TM viscosity with little change in TM stiffness. By applying these manipulations in measurements of TM waves, we show that TM wave speed is determined primarily by stiffness at low frequencies and by viscosity at high frequencies. Both TM viscosity and stiffness affect the longitudinal spread of mechanical excitation through the TM over a broad range of frequencies. Increasing TM viscosity or decreasing stiffness reduces longitudinal spread of mechanical excitation, thereby coupling a smaller range of best frequencies and sharpening tuning. In contrast, increasing viscous loss or decreasing stiffness would tend to broaden tuning in resonance-based TM models. Thus, TM wave and resonance mechanisms are fundamentally different in the way they control frequency selectivity.

Geometric Requirements for Tectorial Membrane Traveling Waves in the Presence of Cochlear Loads.

Recent studies suggest that wave motions of the tectorial membrane (TM) play a critical role in determining the frequency selectivity of hearing. However, frequency tuning is also thought to be limited by viscous loss in subtectorial fluid. Here, we analyze effects of this loss and other cochlear loads on TM traveling waves. Using a viscoelastic model, we demonstrate that hair bundle stiffness has little effect on TM traveling waves calculated with physiological parameters, that the limbal attachment can cause small (<20%) increases in TM wavelength, and that viscous loss in the subtectorial fluid can cause small (<20%) decreases in TM wave decay constants. However, effects of viscous loss in the subtectorial fluid are significantly increased if TM thickness is decreased. In contrast, increasing TM thickness above its physiological range has little effect on the wave, suggesting that the TM is just thick enough to maximize the spatial extent of the TM traveling wave.

Conformal piezoelectric energy harvesting and storage from motions of the heart, lung, and diaphragm.

Here, we report advanced materials and devices that enable high-efficiency mechanical-to-electrical energy conversion from the natural contractile and relaxation motions of the heart, lung, and diaphragm, demonstrated in several different animal models, each of which has organs with sizes that approach human scales. A cointegrated collection of such energy-harvesting elements with rectifiers and microbatteries provides an entire flexible system, capable of viable integration with the beating heart via medical sutures and operation with efficiencies of ∼2%. Additional experiments, computational models, and results in multilayer configurations capture the key behaviors, illuminate essential design aspects, and offer sufficient power outputs for operation of pacemakers, with or without battery assist.

Tectorial Membrane Traveling Waves Underlie Sharp Auditory Tuning in Humans.

Our ability to understand speech requires neural tuning with high frequency resolution, but the peripheral mechanisms underlying sharp tuning in humans remain unclear. Sharp tuning in genetically modified mice has been attributed to decreases in spread of excitation of tectorial membrane traveling waves. Here we show that the spread of excitation of tectorial membrane waves is similar in humans and mice, although the mechanical excitation spans fewer frequencies in humans-suggesting a possible mechanism for sharper tuning.

Ferromagnetic, folded electrode composite as a soft interface to the skin for long-term electrophysiological recording.

This paper introduces a class of ferromagnetic, folded, soft composite material for skin-interfaced electrodes with releasable interfaces to stretchable, wireless electronic measurement systems. These electrodes establish intimate, adhesive contacts to the skin, in dimensionally stable formats compatible with multiple days of continuous operation, with several key advantages over conventional hydrogel based alternatives. The reported studies focus on aspects ranging from ferromagnetic and mechanical behavior of the materials systems, to electrical properties associated with their skin interface, to system-level integration for advanced electrophysiological monitoring applications. The work combines experimental measurement and theoretical modeling to establish the key design considerations. These concepts have potential uses across a diverse set of skin-integrated electronic technologies.

Conformal piezoelectric systems for clinical and experimental characterization of soft tissue biomechanics.

Mechanical assessment of soft biological tissues and organs has broad relevance in clinical diagnosis and treatment of disease. Existing characterization methods are invasive, lack microscale spatial resolution, and are tailored only for specific regions of the body under quasi-static conditions. Here, we develop conformal and piezoelectric devices that enable in vivo measurements of soft tissue viscoelasticity in the near-surface regions of the epidermis. These systems achieve conformal contact with the underlying complex topography and texture of the targeted skin, as well as other organ surfaces, under both quasi-static and dynamic conditions. Experimental and theoretical characterization of the responses of piezoelectric actuator-sensor pairs laminated on a variety of soft biological tissues and organ systems in animal models provide information on the operation of the devices. Studies on human subjects establish the clinical significance of these devices for rapid and non-invasive characterization of skin mechanical properties.

Electrokinetic properties of the mammalian tectorial membrane.

The tectorial membrane (TM) clearly plays a mechanical role in stimulating cochlear sensory receptors, but the presence of fixed charge in TM constituents suggests that electromechanical properties also may be important. Here, we measure the fixed charge density of the TM and show that this density of fixed charge is sufficient to affect mechanical properties and to generate electrokinetic motions. In particular, alternating currents applied to the middle and marginal zones of isolated TM segments evoke motions at audio frequencies (1-1,000 Hz). Electrically evoked motions are nanometer scaled (∼5-900 nm), decrease with increasing stimulus frequency, and scale linearly over a broad range of electric field amplitudes (0.05-20 kV/m). These findings show that the mammalian TM is highly charged and suggest the importance of a unique TM electrokinetic mechanism.

Epidermal electronics with advanced capabilities in near-field communication.

Epidermal electronics with advanced capabilities in near field communications (NFC) are presented. The systems include stretchable coils and thinned NFC chips on thin, low modulus stretchable adhesives, to allow seamless, conformal contact with the skin and simultaneous capabilities for wireless interfaces to any standard, NFC-enabled smartphone, even under extreme deformation and after/during normal daily activities.