Akademska digitalna zbirka SLovenije - logo
E-resources
Full text
Peer reviewed
  • Multifunctional Wearable Sy...
    Hong, Yongseok Joseph; Lee, Hyunjae; Kim, Jaemin; Lee, Minha; Choi, Hyung Jin; Hyeon, Taeghwan; Kim, Dae‐Hyeong

    Advanced functional materials, November 21, 2018, Volume: 28, Issue: 47
    Journal Article

    Wearable bioelectronic technologies have made significant progresses in personalized health management through non‐invasive monitoring of health indicators. However, current wearable systems cannot measure biochemical information and physiological signals simultaneously, which limits integrated data analysis and their widespread clinical applications. Here, an integrated multifunctional wearable health management system composed of a disposable sweat‐based glucose sensing strip and a wearable smart band is reported. The integrated system with control software electrochemically analyzes sweat glucose levels and continuously monitors vital signs (i.e., heart rate, blood oxygen saturation level, and physical activity). Different sweat collecting sites and sweat generation methods are tested in short‐ and long‐term studies with multiple human subjects by using the developed wearable system, leading to optimized protocols for health monitoring. By combining sweat glucose data and physiological monitoring data, pre‐ and post‐exercise blood glucose levels and blood glucose changes resulting from physical activities are reliably estimated, providing key information for preventing hypoglycemic shock during intense exercise. The integrated wearable system offers a novel comprehensive personalized health management strategy through combined analysis of key metabolic and physiological health indicators. An integrated multifunctional wearable health monitoring system that consists of a disposable sweat‐based glucose sensing strip and a wearable smart band is developed for pre‐/post‐exercise glucose‐level estimation and comprehensive personalized health management. Multiple short‐term human studies under various conditions are performed, and optimized protocols for the integrated system to perform accurate and user‐friendly sweat‐based metabolic data analysis are reported.