Non‐Invasive Sweat‐Based Tracking of L‐Dopa Pharmacokinetic Profiles Following an Oral Tablet Administration

The challenges and promise of sweat sensing

The potential of monitoring biomarkers in sweat for health-related applications has spurred rapid growth in the field of wearable sweat sensors over the past decade. Some of the key challenges have been addressed, including measuring sweat-secretion rate and collecting sufficient sample volumes for real-time, continuous molecular analysis without intense exercise. However, except for assessment of cystic fibrosis and regional nerve function, the ability to accurately measure analytes of interest and their physiological relevance to health metrics remain to be determined. Although sweat is not a crystal ball into every aspect of human health, we expect sweat measurements to continue making inroads into niche applications involving active sweating, such as hydration monitoring for athletes and physical laborers and later for medical and casual health monitoring of relevant drugs and hormones.

An Amperometric Biosensor Based on a Bilayer of Electrodeposited Graphene Oxide and Co-Crosslinked Tyrosinase for L-Dopa Detection in Untreated Human Plasma

L-Dopa, a bioactive compound naturally occurring in some Leguminosae plants, is the most effective symptomatic drug treatment for Parkinson's disease. During disease progression, fluctuations in L-DOPA plasma levels occur, causing motor complications. Sensing devices capable of rapidly monitoring drug levels would allow adjusting L-Dopa dosing, improving therapeutic outcomes. A novel amperometric biosensor for L-Dopa detection is described, based on tyrosinase co-crosslinked onto a graphene oxide layer produced through electrodeposition. Careful optimization of the enzyme immobilization procedure permitted to improve the long-term stability while substantially shortening and simplifying the biosensor fabrication. The effectiveness of the immobilization protocol combined with the enhanced performances of electrodeposited graphene oxide allowed to achieve high sensitivity, wide linear range, and a detection limit of 0.84 μM, suitable for L-Dopa detection within its therapeutic window. Interference from endogenous compounds, tested at concentrations levels typically found in drug-treated patients, was not significant. Ascorbic acid exhibited a tyrosinase inhibitory behavior and was therefore rejected from the enzymatic layer by casting an outer Nafion membrane. The proposed device was applied for L-Dopa detection in human plasma, showing good recoveries.

Soft Electronics for Health Monitoring Assisted by Machine Learning

Due to the development of the novel materials, the past two decades have witnessed the rapid advances of soft electronics. The soft electronics have huge potential in the physical sign monitoring and health care. One of the important advantages of soft electronics is forming good interface with skin, which can increase the user scale and improve the signal quality. Therefore, it is easy to build the specific dataset, which is important to improve the performance of machine learning algorithm. At the same time, with the assistance of machine learning algorithm, the soft electronics have become more and more intelligent to realize real-time analysis and diagnosis. The soft electronics and machining learning algorithms complement each other very well. It is indubitable that the soft electronics will bring us to a healthier and more intelligent world in the near future. Therefore, in this review, we will give a careful introduction about the new soft material, physiological signal detected by soft devices, and the soft devices assisted by machine learning algorithm. Some soft materials will be discussed such as two-dimensional material, carbon nanotube, nanowire, nanomesh, and hydrogel. Then, soft sensors will be discussed according to the physiological signal types (pulse, respiration, human motion, intraocular pressure, phonation, etc.). After that, the soft electronics assisted by various algorithms will be reviewed, including some classical algorithms and powerful neural network algorithms. Especially, the soft device assisted by neural network will be introduced carefully. Finally, the outlook, challenge, and conclusion of soft system powered by machine learning algorithm will be discussed.

Non-invasive monitoring of interstitial fluid lactate through an epidermal iontophoretic device

The development of a non-invasive sensing technology that allows collection of interstitial fluid (ISF) lactate and its subsequent analysis without exertion requirement, could enable lactate monitoring from rested individuals. Here, we describe a wearable, soft epidermal adhesive patch that integrates a reverse iontophoretic (RI) system, and an amperometric lactate biosensor placed on the anodic electrode with a porous hydrogel reservoir, for simultaneous ISF lactate extraction and quantification via electrochemical sensing, respectively. The iontophoretic system includes agarose hydrogels for preventing skin electrocution, while a porous polyvinyl alcohol-based hydrogel facilitates the effective transport of lactate from skin to the biosensor. The flexible skin-worn device tested on healthy individuals at rest showed rapid lactate collection from the ISF after 10 min of reverse iontophoresis with no evidence of discomfort or irritation to the skin. Detailed characterization of the enzymatic biosensor before and during on-body trials along with relevant control experiments confirmed the efficient extraction and selective detection of ISF lactate. Such an epidermal technology represents the first demonstration of an all-in-one platform that integrates non-invasive collection and subsequent analysis of lactate from iontophoretically extracted ISF toward point-of-care operation.

An Individualized Multi-Modal Approach for Detection of Medication "Off" Episodes in Parkinson's Disease via Wearable Sensors

The primary treatment for Parkinson's disease (PD) is supplementation of levodopa (L-dopa). With disease progression, people may experience motor and non-motor fluctuations, whereby the PD symptoms return before the next dose of medication. Paradoxically, in order to prevent wearing-off, one must take the next dose while still feeling well, as the upcoming off episodes can be unpredictable. Waiting until feeling wearing-off and then taking the next dose of medication is a sub-optimal strategy, as the medication can take up to an hour to be absorbed. Ultimately, early detection of wearing-off before people are consciously aware would be ideal. Towards this goal, we examined whether or not a wearable sensor recording autonomic nervous system (ANS) activity could be used to predict wearing-off in people on L-dopa. We had PD subjects on L-dopa record a diary of their on/off status over 24 hours while wearing a wearable sensor (E4 wristband^®) that recorded ANS dynamics, including electrodermal activity (EDA), heart rate (HR), blood volume pulse (BVP), and skin temperature (TEMP). A joint empirical mode decomposition (EMD) / regression analysis was used to predict wearing-off (WO) time. When we used individually specific models assessed with cross-validation, we obtained > 90% correlation between the original OFF state logged by the patients and the reconstructed signal. However, a pooled model using the same combination of ASR measures across subjects was not statistically significant. This proof-of-principle study suggests that ANS dynamics can be used to assess the on/off phenomenon in people with PD taking L-dopa, but must be individually calibrated. More work is required to determine if individual wearing-off detection can take place before people become consciously aware of it.

Self-Testing of Ketone Bodies, along with Glucose, Using Touch-Based Sweat Analysis

β-Hydroxybutyrate (HB) is one of the main physiological ketone bodies that play key roles in human health and wellness. Besides their important role in diabetes ketoacidosis, ketone bodies are currently receiving tremendous attention for personal nutrition in connection to the growing popularity of oral ketone supplements. Accordingly, there are urgent needs for developing a rapid, simple, and low-cost device for frequent onsite measurements of β-hydroxybutyrate (HB), one of the main physiological ketone bodies. However, real-time profiling of dynamically changing HB concentrations is challenging and still limited to laboratory settings or to painful and invasive measurements (e.g., a commercial blood ketone meter). Herein, we address the critical need for pain-free frequent HB measurements in decentralized settings and report on a reliable noninvasive, simple, and rapid touch-based sweat HB testing and on its ability to track dynamic HB changes in secreted fingertip sweat, following the intake of commercial ketone supplements. The new touch-based HB detection method relies on an instantaneous collection of the fingertip sweat at rest on a porous poly(vinyl alcohol) (PVA) hydrogel that transports the sweat to a biocatalytic layer, composed of the β-hydroxybutyrate dehydrogenase (HBD) enzyme and its nicotinamide adenine dinucleotide (NAD⁺) cofactor, covering the modified screen-printed carbon working electrode. As a result, the sweat HB can be measured rapidly by the mediated oxidation reaction of the nicotinamide adenine dinucleotide (NADH) product. A personalized HB dose-response relationship is demonstrated within a group of healthy human subjects taking commercial ketone supplements, along with a correlation between the sweat and capillary blood HB levels. Furthermore, a dual disposable biosensing device, consisting of neighboring ketone and glucose enzyme electrodes on a single-strip substrate, has been developed toward the simultaneous touch-based detection of dynamically changing sweat HB and glucose levels, following the intake of ketone and glucose drinks.

Wearable soft electrochemical microfluidic device integrated with iontophoresis for sweat biosensing

A soft and flexible wearable sweat epidermal microfluidic device capable of simultaneously stimulating, collecting, and electrochemically analyzing sweat is demonstrated. The device represents the first system integrating an iontophoretic pilocarpine delivery system around the inlet channels of epidermal polydimethylsiloxane (PDMS) microfluidic device for sweat collection and analysis. The freshly generated sweat is naturally pumped into the fluidic inlet without the need of exercising. Soft skin-mounted systems, incorporating non-invasive, on-demand sweat sampling/analysis interfaces for tracking target biomarkers, are in urgent need. Existing skin conformal microfluidic-based sensors for continuous monitoring of target sweat biomarkers rely on assays during intense physical exercising. This work demonstrates the first example of combining sweat stimulation, through transdermal pilocarpine delivery, with sample collection through a microfluidic channel for real-time electrochemical monitoring of sweat glucose, in a fully integrated soft and flexible multiplexed device which eliminates the need of exercising. The on-body operational performance and layout of the device were optimized considering the fluid dynamics and evaluated for detecting sweat glucose in several volunteers. Furthermore, the microfluidic monitoring device was integrated with a real-time wireless data transmission system using a flexible electronic board PCB conformal with the body. The new microfluidic platform paves the way to real-time non-invasive monitoring of biomarkers in stimulated sweat samples for diverse healthcare and wellness applications.