mrGlove: FPGA-Based Data Glove for Heterogeneous Devices

Lee, Seong Mo; Jang, Ji Hoon; Park, Dae Young; Kim, Sang Don; Lee, Ju Seong; Kim, Seon Kyeong; Lee, Seung Eun

doi:10.1007/978-94-007-7262-5_40

Search citation statements

Order By: Relevance

Paper Sections

Select...

Introduction1

Citation Types

Supporting

Mentioning

Contrasting

Year Published

2015

Publication Types

Select...

Other2

Relationship

Self Cite1

Independent1

Authors

Journals

Cited by 2 publications

(1 citation statement)

References 2 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Pattern recognition techniques depending on movements of hand, arm, wrist and fingers have been proposed for interfacing between human and device such as computer, prosthetics, data glove, and robot [3]. In fact, on pattern recognition technique, classification for sEMGs between adjacent placements of the body is prone to be influenced by other biosignals, physical and physiological noise of muscles [1].…”

Section: Introductionmentioning

confidence: 99%

Design of an EMG signal recognition system for human-smartphone interface

Lee

Kim

Jang

et al. 2015

2015 International SoC Design Conference (ISOCC)

Self Cite

View full text Add to dashboard Cite

In this paper, we propose an EMG signal recognition system for human-smartphone interface. Proposed system provides user experience and interface to control a smartphone application, recognizing pattern of surface electromyography (sEMG) in real time. For classifying events according to transition of the sEMG, classification checks whether an event is active or not in accordance with algorithm to compare the threshold value of the sEMG signal. Proposed system is portable and is able to be integrated into the SoC thanks to a part of proposed system in the field programmable gate array (FPGA). We expect proposed system can be exploited in the entertainment field and wearable device market.

show abstract

Section: Introductionmentioning

confidence: 99%