Mechanoacoustic sensing of physiological processes and body motions via a soft wireless device placed at the suprasternal notch
By KunHyuck Lee, Xiaoyue Ni, Jong Yoon Lee, Hany M Arafa, David J Pe, Shuai Xu, Raudel Avila, M. Irie, JooHee Lee, Ryder Easterlin and 22 more. Nature Biomedical Engineering, 2019
311 citations recorded by the source corpus.
Skin-mounted soft electronics that incorporate high-bandwidth triaxial accelerometers can capture broad classes of physiologically relevant information, including mechano-acoustic signatures of underlying body processes (such as those measured by a stethoscope) and precision kinematics of core-body motions. Here, we describe a wireless device designed to be conformally placed on the suprasternal notch for the continuous measurement of mechano-acoustic signals, from subtle vibrations of the skin at accelerations of around 10−3 m s−2 to large motions of the entire body at about 10 m s−2, and at frequencies up to around 800 Hz. Because the measurements are a complex superposition of signals that arise from locomotion, body orientation, swallowing, respiration, cardiac activity, vocal-fold vibrations and other sources, we exploited frequency-domain analysis and machine learning to obtain—from human subjects during natural daily activities and exercise—real-time recordings of heart rate, respiration rate, energy intensity and other essential vital signs, as well as talking time and cadence, swallow counts and patterns, and other unconventional biomarkers. We also used the device in sleep laboratories and validated the measurements using polysomnography. A wireless device designed to be conformally placed on the suprasternal notch can continuously provide real-time information of essential vital signs as well as talking time, swallow counts and sleep patterns.
Subfields: Biomedical Engineering, Cognitive Neuroscience
View Paper: https://www.semanticscholar.org/paper/1d6ccee4e47ac40de8db57f5c97cf10121bb4414
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Citations in the corpus
- Artificial Intelligence Meets Flexible Sensors: Emerging Smart Flexible Sensing Systems Driven by Machine Learning and Artificial Synapses (2023, methodology): “Rogers et al . have implemented mechanical acoustic sensing of body movements and physiological processes by designing a wearable wireless device and combining it with a hidden Markov model algorithm for data analysis and processing [126].”