.png){kind=icon}
Return
Machine Learning-Enabled Tactile Sensor Design for Dynamic Touch Decoding
.png){kind=icon}
OA
AI
DOI：10.1002/advs.202303949.png)
.png){kind=icon}
Original request for help.png){kind=icon}
Share.png){kind=icon}
Save
Abstract
En 中文
Skin-like flexible sensors play vital roles in healthcare and human-machine interactions. However, general goals focus on pursuing intrinsic static and dynamic performance of skin-like sensors themselves accompanied with diverse trial-and-error attempts. Such a forward strategy almost isolates the design of sensors from resulting applications. Here, a machine learning (ML)-guided design of flexible tactile sensor system is reported, enabling a high classification accuracy (& AP;99.58%) of tactile perception in six dynamic touch modalities. Different from the intuition-driven sensor design, such ML-guided performance optimization is realized by introducing a support vector machine-based ML algorithm along with specific statistical criteria for fabrication parameters selection to excavate features deeply concealed in raw sensing data. This inverse design merges the statistical learning criteria into the design phase of sensing hardware, bridging the gap between the device structures and algorithms. Using the optimized tactile sensor, the high-quality recognizable signals in handwriting applications are obtained. Besides, with the additional data processing, a robot hand assembled with the sensor is able to complete real-time touch-decoding of an 11-digit braille phone number with high accuracy. A data-driven strategy of a flexible triboelectric nanogenerator-based tactile sensor and machine learning co-designed system is proposed to optimize the classification accuracy of output signals from six contact modalities. Via extracting the subtle signals from the raw data by machine learning algorithms, this system is able to dynamically decode an 11-digit multi-point braille numbers.image
Keywords:
human-machine interactions
laser-induced graphene
machine learning
tactile sensor
touch decoding
Journal
IF:
14.1
Papers:
1.8W
Citations:
11.5W
Organization
Cited Papers
ShareSaveBioinspired flexible piezoresistive sensor for high-sensitivity detection of broad pressure range
PREAI
ShareSaveRecent Progress in Flexible Tactile Sensors for Human-Interactive Systems: From Sensors to Advanced Applications.png)
ADVANCED MATERIALS
ADVANCED MATERIALSIF26.8
PREAI
ShareSaveUltra-Sensitive, Deformable, and Transparent Triboelectric Tactile Sensor Based on Micro-Pyramid Patterned Ionic Hydrogel for Interactive Human-Machine InterfacesADVANCED SCIENCE
OAAI
ADVANCED SCIENCEIF14.1
OAAIShareSaveGesture recognition using a bioinspired learning architecture that integrates visual data with somatosensory data from stretchable sensorsNATURE ELECTRONICS
NATURE ELECTRONICSIF40.9
PREAI
ShareSaveShareSave
View more