Disease diagnosis and monitoring using conventional healthcare services is typically expensive and has limited accuracy. Wearable health technology based on flexible electronics has gained tremendous attention in recent years for monitoring patient health owing to attractive features, such as lower medical costs, quick access to patient health data, ability to operate and transmit data in harsh environments, storage at room temperature, non-invasive implementation, mass scaling, etc. This technology provides an opportunity for disease pre-diagnosis and immediate therapy. Wearable sensors have opened a new area of personalized health monitoring by accurately measuring physical states and biochemical signals. Despite the progress to date in the development of wearable sensors, there are still several limitations in the accuracy of the data collected, precise disease diagnosis, and early treatment. This necessitates advances in applied materials and structures and using artificial intelligence (AI)-enabled wearable sensors to extract target signals for accurate clinical decision-making and efficient medical care. In this paper, we review two significant aspects of smart wearable sensors. First, we offer an overview of the most recent progress in improving wearable sensor performance for physical, chemical, and biosensors, focusing on materials, structural configurations, and transduction mechanisms. Next, we review the use of AI technology in combination with wearable technology for big data processing, self-learning, power-efficiency, real-time data acquisition and processing, and personalized health for an intelligent sensing platform. Finally, we present the challenges and future opportunities associated with smart wearable sensors.

This article presents the free and forced vibration characteristics of an FGPM beam under thermo-electro-mechanical loads using the higher-order shear deformation beam theory. The beam properties are assumed to vary through the thickness direction following the power law distribution in terms of the volume fractions of the constituent materials. The governing equations of motion are derived using Hamilton’s principle. The resulting system of differential equations of vibration is solved using the finite element method. The effects of boundary conditions, material composition, slenderness ratio, mechanical, thermal and electric loading, and transverse shear deformation on natural frequencies and transient response are investigated.

The main object of this study was to use a geometric morphometric approach to quantify the left-right symmetry of talus bones.

This review highlights advances in capillary microfluidic wearables enabling power-free, continuous biofluid monitoring and biosensing, with emphasis on fluidic architectures, analyte detection, and pathways for clinical translation.