The demand for high-quality healthcare and well-being services is remarkably increasing due to the ageing global population and modern lifestyles. Recently, the integration of wearables and artificial intelligence (AI) has attracted extensive academic and technological attention for its powerful high-dimensional data processing of wearable biosensing networks. This work reviews the recent developments in AI-assisted wearable biosensing devices in disease diagnostics and fatigue monitoring demonstrating the trend towards personalised medicine with highly efficient, cost-effective, and accurate point-of-care diagnosis by finding hidden patterns in biosensing data and detecting abnormalities. The reliability of adaptive learning and synthetic data and data privacy still need further investigation to realise personalised medicine in the next decade. Due to the worldwide popularity of smartphones, they have been utilised for sensor readout, wireless data transfer, data processing and storage, result display, and cloud server communication leading to the development of smartphone-based biosensing systems. The recent advances have demonstrated a promising future for the healthcare system because of the increasing data processing power, transfer efficiency and storage capacity and diversifying functionalities.

Point‐of‐care (POC) has the capacity to support low‐cost, accurate and real‐time actionable diagnostic data. Microneedle sensors have received considerable attention as an emerging technique to evolve blood‐based diagnostics owing to their direct and painless access to a rich source of biomarkers from interstitial fluid. This review systematically summarizes the recent innovations in microneedle sensors with a particular focus on their utility in POC diagnostics and personalized medicine. The integration of various sensing techniques, mostly electrochemical and optical sensing, has been established in diverse architectures of “lab‐on‐a‐microneedle” platforms. Microneedle sensors with tailored geometries, mechanical flexibility, and biocompatibility are constructed with a variety of materials and fabrication methods. Microneedles categorized into four types: metals, inorganics, polymers, and hydrogels, have been elaborated with state‐of‐the‐art bioengineering strategies for minimally invasive, continuous, and multiplexed sensing. Microneedle sensors have been employed to detect a wide range of biomarkers from electrolytes, metabolites, polysaccharides, nucleic acids, proteins to drugs. Insightful perspectives are outlined from biofluid, microneedles, biosensors, POC devices, and theragnostic instruments, which depict a bright future of the upcoming personalized and intelligent health management.

Endocrine diseases are the fifth most common cause of death and have a considerable impact on society given that they induce long-term morbidity in patients. For many decades, the measurement of hormones has been of great interest since this can be used to diagnose a plethora of pathological conditions. As a result, the endocrine testing market has experienced exponential growth. Several techniques have been utilised for the detection of hormones; however, they are expensive, laborious and require specialist training. Conversely, lateral flow assays (LFAs) are cheap (<£1) and rapid (<5 min) devices. LFAs typically rely on biochemical interactions between antibodies and antigens to produce coloured signals proportional to analyte concentrations, which can be visually inspected. Given their simplicity, LFAs are now considered the most attractive point-of-care device in medicine. However, the measurement of hormones in biofluids using LFAs faces many challenges including (i) the necessity for sensitive detection methods, (ii) the need for multiplexed devices for the confirmation of a diagnosis, and (iii) difficulties in sample preparation and pre-concentration. As such, most hormone LFAs remain in the research phase, and the few that have been commercialised require further optimisation before they can be employed for routine use. This review summarises the basic principles underlying lateral flow technology and provides an overview of recent advances, challenges, and potential solutions for the detection of hormone biomarkers via LFAs. Finally, hormone LFA kits available on the market are presented, with a look towards future developments and trends in the field.

Continuous glucose monitors are crucial for diabetes management, but invasive sampling, signal drift and frequent calibrations restrict their widespread usage. Microneedle sensors are emerging as a minimally-invasive platform for real-time monitoring of clinical parameters in interstitial fluid. Herein, a painless and flexible microneedle sensing patch is constructed by a mechanically-strong microneedle base and a thin layer of fluorescent hydrogel sensor for on-site, accurate, and continuous glucose monitoring. The Förster resonance energy transfer (FRET)-based hydrogel sensors are fabricated by facile photopolymerizations of acryloylated FRET pairs and glucose-specific phenylboronic acid. The optimized hydrogel sensor enables quantification of glucose with reversibility, high selectivity, and signal stability against photobleaching. Poly (ethylene glycol diacrylate)-co-polyacrylamide hydrogel is utilized as the microneedle base, facilitating effective skin piercing and biofluid extraction. The integrated microneedle sensor patch displays a sensitivity of 0.029 mM^-1 in the (patho)physiological range, a low detection limit of 0.193 mM, and a response time of 7.7 min in human serum. Hypoglycemia, euglycemia and hyperglycemia are continuously monitored over 6 h simulated meal and rest activities in a porcine skin model. This microneedle sensor with high transdermal analytical performance offers a powerful tool for continuous diabetes monitoring at point-of-care settings.