Soft integrated electronics packaged with miniaturized modules for wireless power and data transfer are opening up new opportunities for long-term health monitoring and therapy.
Mobility impairment is common in people with multiple sclerosis (PwMS) and there is a need to assess mobility in remote settings. Here, we apply a novel wireless, skin-mounted, and conformal inertial ...sensor (BioStampRC, MC10 Inc.) to examine gait characteristics of PwMS under controlled conditions. We determine the accuracy and precision of BioStampRC in measuring gait kinematics by comparing to contemporary research-grade measurement devices.
A total of 45 PwMS, who presented with diverse walking impairment (Mild MS = 15, Moderate MS = 15, Severe MS = 15), and 15 healthy control subjects participated in the study. Participants completed a series of clinical walking tests. During the tests participants were instrumented with BioStampRC and MTx (Xsens, Inc.) sensors on their shanks, as well as an activity monitor GT3X (Actigraph, Inc.) on their non-dominant hip. Shank angular velocity was simultaneously measured with the inertial sensors. Step number and temporal gait parameters were calculated from the data recorded by each sensor. Visual inspection and the MTx served as the reference standards for computing the step number and temporal parameters, respectively. Accuracy (error) and precision (variance of error) was assessed based on absolute and relative metrics. Temporal parameters were compared across groups using ANOVA.
Mean accuracy±precision for the BioStampRC was 2±2 steps error for step number, 6±9ms error for stride time and 6±7ms error for step time (0.6-2.6% relative error). Swing time had the least accuracy±precision (25±19ms error, 5±4% relative error) among the parameters. GT3X had the least accuracy±precision (8±14% relative error) in step number estimate among the devices. Both MTx and BioStampRC detected significantly distinct gait characteristics between PwMS with different disability levels (p<0.01).
BioStampRC sensors accurately and precisely measure gait parameters in PwMS across diverse walking impairment levels and detected differences in gait characteristics by disability level in PwMS. This technology has the potential to provide granular monitoring of gait both inside and outside the clinic.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
Contemporary cardiac and heart rate monitoring devices capture physiological signals using optical and electrode-based sensors. However, these devices generally lack the form factor and mechanical ...flexibility necessary for use in ambulatory and home environments. Here, we report an ultrathin (~1 mm average thickness) and highly flexible wearable cardiac sensor (WiSP) designed to be minimal in cost (disposable), light weight (1.2 g), water resistant, and capable of wireless energy harvesting. Theoretical analyses of system-level bending mechanics show the advantages of WiSP's flexible electronics, soft encapsulation layers and bioadhesives, enabling intimate skin coupling. A clinical feasibility study conducted in atrial fibrillation patients demonstrates that the WiSP device effectively measures cardiac signals matching the Holter monitor, and is more comfortable. WiSP's physical attributes and performance results demonstrate its utility for monitoring cardiac signals during daily activity, exertion and sleep, with implications for home-based care.
The concentration of chloride in sweat remains the most robust biomarker for confirmatory diagnosis of cystic fibrosis (CF), a common life-shortening genetic disorder. Early diagnosis via ...quantitative assessment of sweat chloride allows prompt initiation of care and is critically important to extend life expectancy and improve quality of life. The collection and analysis of sweat using conventional wrist-strapped devices and iontophoresis can be cumbersome, particularly for infants with fragile skin, who often have insufficient sweat production. Here, we introduce a soft, epidermal microfluidic device ("sweat sticker") designed for the simple and rapid collection and analysis of sweat. Intimate, conformal coupling with the skin supports nearly perfect efficiency in sweat collection without leakage. Real-time image analysis of chloride reagents allows for quantitative assessment of chloride concentrations using a smartphone camera, without requiring extraction of sweat or external analysis. Clinical validation studies involving patients with CF and healthy subjects, across a spectrum of age groups, support clinical equivalence compared to existing device platforms in terms of accuracy and demonstrate meaningful reductions in rates of leakage. The wearable microfluidic technologies and smartphone-based analytics reported here establish the foundation for diagnosis of CF outside of clinical settings.
Noninvasive, in situ biochemical monitoring of physiological status, via the use of sweat, could enable new forms of health care diagnostics and personalized hydration strategies. Recent advances in ...sweat collection and sensing technologies offer powerful capabilities, but they are not effective for use in extreme situations such as aquatic or arid environments, because of unique challenges in eliminating interference/contamination from surrounding water, maintaining robust adhesion in the presence of viscous drag forces and/or vigorous motion, and preventing evaporation of collected sweat. This paper introduces materials and designs for waterproof, epidermal, microfluidic and electronic systems that adhere to the skin to enable capture, storage, and analysis of sweat, even while fully underwater. Field trials demonstrate the ability of these devices to collect quantitative in situ measurements of local sweat chloride concentration, local sweat loss (and sweat rate), and skin temperature during vigorous physical activity in controlled, indoor conditions and in open-ocean swimming.
Nutrients play critical roles in maintaining core physiological functions and in preventing diseases. Technologies for delivering these nutrients and for monitoring their concentrations can help to ...ensure proper nutritional balance. Eccrine sweat is a potentially attractive class of biofluid for monitoring purposes due to the ability to capture sweat easily and noninvasively from nearly any region of the body using skin‐integrated microfluidic technologies. Here, a miniaturized system of this type is presented that allows simple, rapid colorimetric assessments of the concentrations of multiple essential nutrients in sweat, simultaneously and without any supporting electronics – vitamin C, calcium, zinc, and iron. A transdermal patch integrated directly with the microfluidics supports passive, sustained delivery of these species to the body throughout a period of wear. Comparisons of measurement results to those from traditional lab analysis methods demonstrate the accuracy and reliability of this platform. On‐body tests with human subjects reveal correlations between the time dynamics of concentrations of these nutrients in sweat and those of the corresponding concentrations in blood. Studies conducted before and after consuming certain foods and beverages highlight practical capabilities in monitoring nutritional balance, with strong potential to serve as a basis for guiding personalized dietary choices.
This paper introduces a soft, skin‐interfaced microfluidic system that enables nutrient analysis in sweat and delivery of vitamins to the body. Accurate colorimetric sensors can quantify the concentrations of nutrients in sweat, and a transdermal patch integrated directly with the microfluidics supports passive, sustained delivery of nutrients to the body throughout a period of wear.
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.
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.
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.
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.
Gait speed is a powerful clinical marker for mobility impairment in patients suffering from neurological disorders. However, assessment of gait speed in coordination with delivery of comprehensive ...care is usually constrained to clinical environments and is often limited due to mounting demands on the availability of trained clinical staff. These limitations in assessment design could give rise to poor ecological validity and limited ability to tailor interventions to individual patients. Recent advances in wearable sensor technologies have fostered the development of new methods for monitoring parameters that characterize mobility impairment, such as gait speed, outside the clinic, and therefore address many of the limitations associated with clinical assessments. However, these methods are often validated using normal gait patterns; and extending their utility to subjects with gait impairments continues to be a challenge. In this paper, we present a machine learning method for estimating gait speed using a configurable array of skin-mounted, conformal accelerometers. We establish the accuracy of this technique on treadmill walking data from subjects with normal gait patterns and subjects with multiple sclerosis-induced gait impairments. For subjects with normal gait, the best performing model systematically overestimates speed by only 0.01 m/s, detects changes in speed to within less than 1%, and achieves a root-mean-square-error of 0.12 m/s. Extending these models trained on normal gait to subjects with gait impairments yields only minor changes in model performance. For example, for subjects with gait impairments, the best performing model systematically overestimates speed by 0.01 m/s, quantifies changes in speed to within 1%, and achieves a root-mean-square-error of 0.14 m/s. Additional analyses demonstrate that there is no correlation between gait speed estimation error and impairment severity, and that the estimated speeds maintain the clinical significance of ground truth speed in this population. These results support the use of wearable accelerometer arrays for estimating walking speed in normal subjects and their extension to MS patient cohorts with gait impairment.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
This paper presents materials and core/shell architectures that provide optimized mechanical properties in packages for stretchable electronic systems. Detailed experimental and theoretical studies ...quantitatively connect the geometries and elastic properties of the constituent materials to the overall mechanical responses of the integrated systems, with a focus on interfacial stresses, effective modulus, and maximum extent of elongation. Specific results include core/shell designs that lead to peak values of the shear and normal stresses on the skin that remain less than 10 kPa even for applied strains of up to 20%, thereby inducing minimal somatosensory perception of the device on the human skin. Additional, strain‐limiting mesh structures embedded in the shell improve mechanical robustness by protecting the active components from strains that would otherwise exceed the fracture point. Demonstrations in precommercial stretchable electronic systems illustrate the utility of these concepts.
Human skin‐like core/shell material structure is presented for use in wearable, stretchable electronic systems. Here, an ultralow‐modulus elastomer (core) with a thin enclosure (shell) serves to minimize interface stresses and mechanical constraints on natural motions, with ability to strain‐isolate the electronics. Demonstration examples exploit emerging commercial classes of stretchable electronic system to wirelessly monitor a subject's motion and body temperature during exercise.
Proper healing of incised skin is critical to the natural processes of tissue repair. Concepts in flexible silicon electronics enable integration of actuators, sensors and a variety of semiconductor ...devices onto thin strips of plastic or biopolymers, to yield ‘instrumented’ suture threads for monitoring and accelerating the wound healing in this context. Bifacial systems of this type demonstrate various classes of functionality, in live animal models. Detailed modelling of the mechanics reveals stress and strain distributions in such applications, to support design strategies for robust operation.
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