A Simple, Inexpensive, Wearable Glove with Hybrid Resistive‐Pressure Sensors for Computational Sensing, Proprioception, and Task Identification. (17th June 2020)

• Record Type: Journal Article
• Authors: Hughes, Josie; Spielberg, Andrew; Chounlakone, Mark; Chang, Gloria; Matusik, Wojciech; Rus, Daniela
• Is Part Of: Advanced intelligent systems. Volume 2:Number 6(2020)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2020-06-17
• Subjects: Artificial intelligence -- Periodicals; Robotics -- Periodicals; Control theory -- Periodicals; 006.3
• DOI: 10.1002/aisy.202070061
• Languages: English
• ISSNs: 2640-4567

Abstract

Abstract : 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 2000002, Andrew Spielberg and co‐workers show object, stiffness, and handwritten letter classification, as well as temperature, force, hand pose, and heart rate estimation.