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Abstract Lithium is a drug widely employed for the treatment of bipolar disorder owing to its high efficacy in mood management and suicide prevention. However, this efficacy is often undermined by misdosing and nonadherence, and diligent drug monitoring is required during treatment. Standard lithium monitoring involves invasive blood collections and laboratory analysis with low time granularity. Recent advances in sensor technology have enabled the development of personalized drug‐monitoring devices that analyze biomarker information noninvasively. Herein, based on the fact that the analyte partition onto the fingertip with a high flux, a touch‐based noninvasive monitoring modality for managing lithium pharmacotherapy is devised. The system is built based on a thin organohydrogel‐mounted lithium ion‐selective electrode (TOH‐ISE). The TOH coating provides a stable environment for sensing. Through the utilization of a water/glycerol bi‐solvent matrix, the gel exhibits dehydration‐resist properties, rendering a controlled micro‐environment for ISE conditioning, and subsequently minimizing signal drift. To illustrate the clinical application of the solution, the system is tested on a subject prescribed lithium. The system successfully detected the increase in circulating drug levels following medication intake. Collectively, the results indicate the devised solution is capable to facilitate lithium adherence monitoring and has broader potential for optimizing lithium pharmacotherapy. 

Abstract Active biofluid management is central to the realization of wearable bioanalytical platforms that are poised to autonomously provide frequent, real-time, and accurate measures of biomarkers in epidermally-retrievable biofluids (e.g., sweat). Accordingly, here, a programmable epidermal microfluidic valving system is devised, which is capable of biofluid sampling, routing, and compartmentalization for biomarker analysis. At its core, the system is a network of individually-addressable microheater-controlled thermo-responsive hydrogel valves, augmented with a pressure regulation mechanism to accommodate pressure built-up, when interfacing sweat glands. The active biofluid control achieved by this system is harnessed to create unprecedented wearable bioanalytical capabilities at both the sensor level (decoupling the confounding influence of flow rate variability on sensor response) and the system level (facilitating context-based sensor selection/protection). Through integration with a wireless flexible printed circuit board and seamless bilateral communication with consumer electronics (e.g., smartwatch), contextually-relevant (scheduled/on-demand) on-body biomarker data acquisition/display was achieved. 

The awareness of individuals’ biological status is critical for creating interactive and adaptive environments that can actively assist the users to achieve optimal outcomes. Accordingly, specialized human–machine interfaces—equipped with bioperception and interpretation capabilities—are required. To this end, we devised a multimodal cryptographic bio-human–machine interface (CB-HMI), which seamlessly translates the user’s touch-based entries into encrypted biochemical, biophysical, and biometric indices. As its central component, the CB-HMI features thin hydrogel-coated chemical sensors and inference algorithms to noninvasively and inconspicuously acquire biochemical indices such as circulating molecules that partition onto the skin (here, ethanol and acetaminophen). Additionally, the CB-HMI hosts physical sensors and associated algorithms to simultaneously acquire the user’s heart rate, blood oxygen level, and fingerprint minutiae pattern. Supported by human subject studies, we demonstrated the CB-HMI’s capability in terms of acquiring physiologically relevant readouts of target bioindices, as well as user-identifying and biometrically encrypting/decrypting these indices in situ (leveraging the fingerprint feature). By upgrading the common surrounding objects with the CB-HMI, we created interactive solutions for driving safety and medication use. Specifically, we demonstrated a vehicle-activation system and a medication-dispensing system, where the integrated CB-HMI uniquely enabled user bioauthentication (on the basis of the user’s biological state and identity) prior to rendering the intended services. Harnessing the levels of bioperception achieved by the CB-HMI and other intelligent HMIs, we can equip our surroundings with a comprehensive and deep awareness of individuals’ psychophysiological state and needs. 

Wearable sweat analysis possesses significant potential for transforming personalized and precision medicine, by capturing the longitudinal profiles of a broad spectrum of biomarker molecules that are informative of our body’s dynamic chemistry. However, the lack of established physiological criteria to provide personalized feedback, based on sweat biomarker readings, has prevented the translation of wearable sweat-based bioanalytical technologies into health and wellness monitoring applications. Accordingly, scalable sweat sampling tools are required to facilitate large-scale and longitudinal clinical studies focusing on interpreting sweat biomarker readings. However, conventional sweat induction-collection tools are bulky and require multi-step and manual operations. Accordingly, here, we devise a sweat sampling patch, which can be deployed for autonomous diurnal sweat induction-collection. The core of this patch is an addressable array of miniaturized and coupled iontophoresis/microfluidic interfaces that can be activated on- demand or at scheduled time-points to induce/collect sufficient sweat samples for analysis. The iontophoresis interface was designed following an introduced design space centering on sufficient sweat secretory agonist delivery at safe current levels. The microfluidic interface was fabricated following a simple, rapid, and low-cost fabrication scheme. To achieve autonomous operation, these interfaces were extended into an array format and coupled with a custom-developed flexible and wireless circuit board. To inform utility, periodically induced/collected sweat samples of an individual were analyzed in relation to meal intake.