Continuous real-time detection and management of comprehensive mental states using wireless soft multifunctional bioelectronics.

Journal: Biosensors & bioelectronics
Published Date:

Abstract

Quantitatively measuring human mental states that profoundly affect cognition, behavior, and recovery would revolutionize personalized digital healthcare. Detecting fatigue, stress, and sleep is particularly important due to their interdependence: persistent fatigue can induce cognitive stress, while chronic stress impairs sleep quality, creating a harmful feedback loop. Here, we introduce a wireless, soft, multifunctional bioelectronic system offering the continuous real-time detection and management of comprehensive mental states. The all-in-one wearable device, mounted on the forehead, measures clinical-grade brain and cardiorespiratory signals. This membrane biopatch is imperceptible, flexible, and reusable, providing ultimate user comfort while detecting high-fidelity electroencephalogram, electrooculogram, pulse rate, and blood oxygen saturation. A set of in vivo studies with human subjects demonstrates that the soft device has great skin-conformal contact and minimized motion artifacts, capturing clinical-quality data with different activities, even during sleep. The developed signal processing methods and deep-learning algorithms offer automated, real-time classification of driving drowsiness, stress conditions, and sleep quality. The bioelectronics platforms in this study have the potential to revolutionize digital healthcare, particularly personalized medicine and at-home health monitoring.

Authors

  • Hodam Kim
    Department of Biomedical Engineering, Hanyang University, Seoul 04763, Korea.
  • Hojoong Kim
  • Yoon Jae Lee
    Wearable Intelligent Systems and Healthcare Center, Institute for Matter and Systems, Georgia Institute of Technology, Atlanta, GA 30332, USA; School of Electrical and Computer Engineering, Georgia Institute of Technology, Atlanta, GA 30332, USA.
  • Hoon Yi
  • Youngjin Kwon
    Wearable Intelligent Systems and Healthcare Center, Institute for Matter and Systems, Georgia Institute of Technology, Atlanta, GA 30332, USA; George W. Woodruff School of Mechanical Engineering, Georgia Institute of Technology, Atlanta, GA 30332, USA.
  • Yunuo Huang
    Wearable Intelligent Systems and Healthcare Center (WISH Center) at the Institute for Matter and Systems, Georgia Institute of Technology, Atlanta, GA, 30332, USA.
  • Lynn Marie Trotti
    Emory University, Atlanta, GA, United States.
  • Yun Soung Kim
    BioMedical Engineering and Imaging Institute, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA; Department of Diagnostic, Molecular and Interventional Radiology, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA.
  • Woon-Hong Yeo
    George W. Woodruff School of Mechanical Engineering, Institute for Electronics and Nanotechnology, Georgia Institute of Technology, Atlanta, Georgia 30332, United States.