Bio-Integrated Wearable Systems: A Comprehensive Review.

By Tyler R. Ray, Jungil Choi, Amay J. Bandodkar, Siddharth R. Krishnan, P. Gutruf, L. Tian, Roozbeh Ghaffari, John A. Rogers. Chemical Reviews, 2019

1,087 citations recorded by the source corpus.

Bio-integrated wearable systems can measure a broad range of biophysical, biochemical, and environmental signals to provide critical insights into overall health status and to quantify human performance. Recent advances in material science, chemical analysis techniques, device designs, and assembly methods form the foundations for a uniquely differentiated type of wearable technology, characterized by noninvasive, intimate integration with the soft, curved, time-dynamic surfaces of the body. This review summarizes the latest advances in this emerging field of "bio-integrated" technologies in a comprehensive manner that connects fundamental developments in chemistry, material science, and engineering with sensing technologies that have the potential for widespread deployment and societal benefit in human health care. An introduction to the chemistries and materials for the active components of these systems contextualizes essential design considerations for sensors and associated platforms that appear in following sections. The subsequent content highlights the most advanced biosensors, classified according to their ability to capture biophysical, biochemical, and environmental information. Additional sections feature schemes for electrically powering these sensors and strategies for achieving fully integrated, wireless systems. The review concludes with an overview of key remaining challenges and a summary of opportunities where advances in materials chemistry will be critically important for continued progress.

Subfields: Biomedical Engineering, Cognitive Neuroscience, Polymers and Plastics

View Paper: https://www.semanticscholar.org/paper/79921243ea8903950b99c6bd744953eeda12db76

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Citations in the corpus

The Emergence of AI-Based Wearable Sensors for Digital Health Technology: A Review (2023, background): “The working mechanism consists of either contact-mode or sliding-mode [104].”
Digital health for aging populations (2023, neutral): “1b) 4,5 .”
Progress in wearable electronics/photonics—Moving toward the era of artificial intelligence and internet of things (2020, background): “In addition, deep learning as a new subfield of machine learning provides an efficient way to adaptively learn representative features from collected raw signals especially on unsupervised and incremental learning, which has made great achievements in image processing, speech recognition, human acti”