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A deep-learned skin sensor decoding the epicentral human motions
- Source :
- Nature Communications, Vol 11, Iss 1, Pp 1-8 (2020), Nature Communications
- Publication Year :
- 2020
- Publisher :
- Nature Publishing Group, 2020.
-
Abstract
- State monitoring of the complex system needs a large number of sensors. Especially, studies in soft electronics aim to attain complete measurement of the body, mapping various stimulations like temperature, electrophysiological signals, and mechanical strains. However, conventional approach requires many sensor networks that cover the entire curvilinear surfaces of the target area. We introduce a new measuring system, a novel electronic skin integrated with a deep neural network that captures dynamic motions from a distance without creating a sensor network. The device detects minute deformations from the unique laser-induced crack structures. A single skin sensor decodes the complex motion of five finger motions in real-time, and the rapid situation learning (RSL) ensures stable operation regardless of its position on the wrist. The sensor is also capable of extracting gait motions from pelvis. This technology is expected to provide a turning point in health-monitoring, motion tracking, and soft robotics.<br />Real-time monitoring human motions normally demands connecting a large number of sensors in a complicated network. To make it simpler, Kim et al. decode the motion of fingers using a flexible sensor attached on wrist that measures skin deformation with the help of a deep-learning architecture.
- Subjects :
- Materials for devices
Decodes
Silver
Computer science
Science
Soft robotics
Electronic skin
ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION
Metal Nanoparticles
General Physics and Astronomy
Biosensing Techniques
02 engineering and technology
010402 general chemistry
01 natural sciences
Article
General Biochemistry, Genetics and Molecular Biology
Motion
Wearable Electronic Devices
Gait (human)
Match moving
Position (vector)
Humans
Computer vision
lcsh:Science
Sensors and probes
ComputingMethodologies_COMPUTERGRAPHICS
Multidisciplinary
biology
Artificial neural network
Sensors
business.industry
Temperature
General Chemistry
Wrist
021001 nanoscience & nanotechnology
biology.organism_classification
Mechanical engineering
0104 chemical sciences
lcsh:Q
Artificial intelligence
0210 nano-technology
business
Wireless sensor network
Subjects
Details
- Language :
- English
- ISSN :
- 20411723
- Volume :
- 11
- Issue :
- 1
- Database :
- OpenAIRE
- Journal :
- Nature Communications
- Accession number :
- edsair.doi.dedup.....05d2d287d24495e95027ece672daee99