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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http://dx.doi.org/10.1126/sciadv.1601185 | DOI Listing |
Front Robot AI
December 2024
School of Food Science and Environmental Health, Technological University Dublin, Dublin, Ireland.
Collaborative intelligence (CI) involves human-machine interactions and is deemed safety-critical because their reliable interactions are crucial in preventing severe injuries and environmental damage. As these applications become increasingly data-driven, the reliability of CI applications depends on the quality of data, shaping the system's ability to interpret and respond in diverse and often unpredictable environments. In this regard, it is important to adhere to data quality standards and guidelines, thus facilitating the advancement of these collaborative systems in industry.
View Article and Find Full Text PDFACS Appl Mater Interfaces
December 2024
National Engineering Lab of Special Display Technology, Special Display and Imaging Technology Innovation Center of Anhui Province, Academy of Optoelectronic Technology, Hefei University of Technology, Hefei 230009, China.
Flexible sensors mimic the sensing ability of human skin, and have unique flexibility and adaptability, allowing users to interact with intelligent systems in a more natural and intimate way. To overcome the issues of low sensitivity and limited operating range of flexible strain sensors, this study presents a highly innovative preparation method to develop a conductive elastomeric sensor with a cracked thin film by combining polydimethylsiloxane (PDMS) with multiwalled carbon nanotubes (MCNT). This novel design significantly increases both the sensitivity and operating range of the sensor (strain range 0-50%; the maximum tensile sensitivity of this sensor reaches 4.
View Article and Find Full Text PDFAcc Chem Res
December 2024
Tarpo Department of Chemistry, Purdue University, West Lafayette, Indiana 47907, United States.
ConspectusOrganic mixed ionic electronic conductors (OMIECs) represent an exciting and emerging class of materials that have recently revitalized the field of organic semiconductors. OMIECs are particularly attractive because they allow both ionic and electronic transport while retaining the inherent benefits of organic semiconducting materials such as mechanical conformability and biocompatibility. These combined properties make the OMIECs ideal for applications in bioelectronics, energy storage, neuromorphic computing, and electrochemical transistors for sensing.
View Article and Find Full Text PDFBiosens Bioelectron
December 2024
Key Laboratory of Bionic Engineering (Ministry of Education), Jilin University, Changchun, Jilin, 130022, China; The National Key Laboratory of Automotive Chassis Integration and Bionics (ACIB), College of Biological and Agricultural Engineering, Jilin University, Changchun, 130022, China; Institute of Structured and Architected Materials, Liaoning Academy of Materials, Shenyang, 110167, China.
Flexible pressure sensor is a crucial component of tactile sensors and plays an integral role in numerous significant fields. Despite the considerable effort put forth, how to further improve sensitivity with ingenious yet easy-to-manufacture structures and apply them to emerging fields such as structure/materials recognition, human motion monitoring, and human-machine interaction remains a challenge. Here, we develop a highly sensitive flexible capacitive pressure sensor featuring a structured electrode layer with embedded microcracks and a dielectric layer with micro-convex structures, which are combined with an iontronic interface.
View Article and Find Full Text PDFJ Neural Eng
December 2024
West China Hospital of Sichuan University, No.37 Guoxue Alley, Wuhou District, Chengdu City, Sichuan Province, Chengdu, Sichuan, 610041, CHINA.
Objective: Brain-computer interface(BCI) is leveraged by artificial intelligence in EEG signal decoding, which makes it possible to become a new means of human-machine interaction. However, the performance of current EEG decoding methods is still insufficient for clinical applications because of inadequate EEG information extraction and limited computational resources in hospitals. This paper introduces a hybrid network that employs a Transformer with modified locally linear embedding and sliding window convolution for EEG decoding.
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