Epidermal mechano-acoustic sensing electronics for cardiovascular diagnostics and human-machine interfaces
Author(s) -
Yuhao Liu,
James J. S. Norton,
Raza Qazi,
Zhanan Zou,
Kaitlyn R. Ammann,
Hank Liu,
Lingqing Yan,
Phat Tran,
KyungIn Jang,
Jung Woo Lee,
Douglas Zhang,
K. Kilian,
Sung Hee Jung,
Timothy Bretl,
Jianliang Xiao,
Marvin J. Slepian,
Yonggang Huang,
JaeWoong Jeong,
John A. Rogers
Publication year - 2016
Publication title -
science advances
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 5.928
H-Index - 146
ISSN - 2375-2548
DOI - 10.1126/sciadv.1601185
Subject(s) - electronics , computer science , human–computer interaction , electrical engineering , engineering
Physiological mechano-acoustic signals, often with frequencies and intensities that are beyond those associated with the audible range, provide information of great clinical utility. Stethoscopes and digital accelerometers in conventional packages can capture some relevant data, but neither is suitable for use in a continuous, wearable mode, and both have shortcomings associated with mechanical transduction of signals through the skin. We report a soft, conformal class of device configured specifically for mechano-acoustic recording from the skin, capable of being used on nearly any part of the body, in forms that maximize detectable signals and allow for multimodal operation, such as electrophysiological recording. Experimental and computational studies highlight the key roles of low effective modulus and low areal mass density for effective operation in this type of measurement mode on the skin. Demonstrations involving seismocardiography and heart murmur detection in a series of cardiac patients illustrate utility in advanced clinical diagnostics. Monitoring of pump thrombosis in ventricular assist devices provides an example in characterization of mechanical implants. Speech recognition and human-machine interfaces represent additional demonstrated applications. These and other possibilities suggest broad-ranging uses for soft, skin-integrated digital technologies that can capture human body acoustics
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