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Abstract Recent advancements in wearable photonic sensors have marked a transformative era in healthcare, enabling non‐invasive, real‐time, portable, and personalized medical monitoring. These sensors leverage the unique properties of light toward high‐performance sensing in form factors optimized for real‐world use. Their ability to offer solutions to a broad spectrum of medical challenges – from routine health monitoring to managing chronic conditions, inspires a rapidly growing translational market. This review explores the design and development of wearable photonic sensors toward various healthcare applications. The photonic sensing strategies that power these technologies are first presented, alongside a discussion of the factors that define optimal use‐cases for each approach. The means by which these mechanisms are integrated into wearable formats are then discussed, with considerations toward material selection for comfort and functionality, component fabrication, and power management. Recent developments in the space are detailed, accounting for both physical and chemical stimuli detection through various non‐invasive biofluids. Finally, a comprehensive situational overview identifies critical challenges toward translation, alongside promising solutions. Associated future outlooks detail emerging trends and mechanisms that stand to enable the integration of these technologies into mainstream healthcare practice, toward advancing personalized medicine and improving patient outcomes. 

Abstract Capabilities for continuous monitoring of pressures and temperatures at critical skin interfaces can help to guide care strategies that minimize the potential for pressure injuries in hospitalized patients or in individuals confined to the bed. This paper introduces a soft, skin-mountable class of sensor system for this purpose. The design includes a pressure-responsive element based on membrane deflection and a battery-free, wireless mode of operation capable of multi-site measurements at strategic locations across the body. Such devices yield continuous, simultaneous readings of pressure and temperature in a sequential readout scheme from a pair of primary antennas mounted under the bedding and connected to a wireless reader and a multiplexer located at the bedside. Experimental evaluation of the sensor and the complete system includes benchtop measurements and numerical simulations of the key features. Clinical trials involving two hemiplegic patients and a tetraplegic patient demonstrate the feasibility, functionality and long-term stability of this technology in operating hospital settings. 

Abstract Many measurements at the LHC require efficient identification of heavy-flavour jets, i.e. jets originating from bottom (b) or charm (c) quarks. An overview of the algorithms used to identify c jets is described and a novel method to calibrate them is presented. This new method adjusts the entire distributions of the outputs obtained when the algorithms are applied to jets of different flavours. It is based on an iterative approach exploiting three distinct control regions that are enriched with either b jets, c jets, or light-flavour and gluon jets. Results are presented in the form of correction factors evaluated using proton-proton collision data with an integrated luminosity of 41.5 fb -1 at  √s = 13 TeV, collected by the CMS experiment in 2017. The closure of the method is tested by applying the measured correction factors on simulated data sets and checking the agreement between the adjusted simulation and collision data. Furthermore, a validation is performed by testing the method on pseudodata, which emulate various mismodelling conditions. The calibrated results enable the use of the full distributions of heavy-flavour identification algorithm outputs, e.g. as inputs to machine-learning models. Thus, they are expected to increase the sensitivity of future physics analyses.