Recognition of handwriting from electromyography.

Published

Journal Article

Handwriting--one of the most important developments in human culture--is also a methodological tool in several scientific disciplines, most importantly handwriting recognition methods, graphology and medical diagnostics. Previous studies have relied largely on the analyses of handwritten traces or kinematic analysis of handwriting; whereas electromyographic (EMG) signals associated with handwriting have received little attention. Here we show for the first time, a method in which EMG signals generated by hand and forearm muscles during handwriting activity are reliably translated into both algorithm-generated handwriting traces and font characters using decoding algorithms. Our results demonstrate the feasibility of recreating handwriting solely from EMG signals - the finding that can be utilized in computer peripherals and myoelectric prosthetic devices. Moreover, this approach may provide a rapid and sensitive method for diagnosing a variety of neurogenerative diseases before other symptoms become clear.

Full Text

Cited Authors

  • Linderman, M; Lebedev, MA; Erlichman, JS

Published Date

  • January 2009

Published In

Volume / Issue

  • 4 / 8

Start / End Page

  • e6791 -

PubMed ID

  • 19707562

Pubmed Central ID

  • 19707562

Electronic International Standard Serial Number (EISSN)

  • 1932-6203

International Standard Serial Number (ISSN)

  • 1932-6203

Digital Object Identifier (DOI)

  • 10.1371/journal.pone.0006791

Language

  • eng