Open AccessA Simple, Inexpensive, Wearable Glove with Hybrid Resistive‐Pressure Sensors for Computational Sensing, Proprioception, and Task Identification
Author(s) -
Hughes Josie,
Spielberg Andrew,
Chounlakone Mark,
Chang Gloria,
Matusik Wojciech,
Rus Daniela
Publication year - 2020
Publication title -
advanced intelligent systems
Language(s) - English
Resource type - Journals
ISSN - 2640-4567
DOI - 10.1002/aisy.202070061
Subject(s) - resistive touchscreen , wearable computer , computer science , task (project management) , identification (biology) , pressure sensor , artificial intelligence , wearable technology , computer vision , pattern recognition (psychology) , engineering , embedded system , mechanical engineering , botany , systems engineering , biology
Wearable Gloves Using fluidic and resistive sensor inputs, MemGlove collects data which is then routed through MLP and LSTM neural networks to produce outputs reflecting the state of the user and the environment. In article number 22 , Andrew Spielberg and co‐workers show object, stiffness, and handwritten letter classification, as well as temperature, force, hand pose, and heart rate estimation.