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Device Uses Handwriting to Detect Neurological Disorders
To help detect neurodegenerative diseases, researchers have built a system that records signals from hand muscles during handwriting.
Credit: Michael Linderman, Department of Neuroethics, Norconnect Inc.

This Research in Action article was provided to LiveScience in partnership with the National Science Foundation.

Each year, more than 50,000 Americans are diagnosed with Parkinson's disease, a degenerative disorder that attacks the central nervous system, causing tremors, rigidity, slowness of movement and loss of balance. Detecting it can be difficult, however, especially in early stages. Now, to detect and study neurodegenerative diseases such as Parkinson's, researchers have built a system that records signals from hand muscles during handwriting.

Motor neurons transmit electrical signals to muscles to make them contract. Electromyography (EMG) is a process that records and graphs such electrical activity to yield information about the condition of a subject's muscles and the nerve cells that control them. In the new detection system, a test subject attaches EMG surface electrodes to his or her hand and wears a glove to hold the electrodes in place. The subject then writes on a tablet, repeating simple, stereotyped hand movements that involve two basic motor components: firmly holding a pen by the fingers and moving the hand and the fingers to produce written text. The results are collected from both the tablet and the surface EMG electrodes.

An analytical program generates the result of muscle activity during this controlled set of movements and finds essential differences in the writing and writing behavior of patients with Parkinson's disease and older healthy control subjects. Thus a clinician would be able to detect and study neurodegenerative diseases such as Parkinson's.

The system developers included National Science Foundation-funded engineers at Norconnect, Inc., led by Norconnect chief scientist Michael Linderman.

Mark Latash, a professor of kinesiology at Penn State University who is not part of the research group, said the project appears to be a promising approach to helping physicians identify biomarkers of early Parkinson's disease.

Hans-Leo Teulings, CEO of NeuroScript, LLC in Temple, Az., an internationally renowned scientist and an author of an industry standard handwriting analysis device called MovAlyzeR, said the method of EMG analysis developed by Linderman will make the handwriting paradigm a valuable model and an object of scientific research similar to reflexes. Teulings did not participate in this research, but closely followed its progress for several years.

The new methodology for identifying Parkinson's disease biomarkers was published in several academic papers available on PLoS ONE (Public Library of Science) and was presented by Linderman at the 2013 Alzheimer's and Parkinson's disease conference in Florence, Italy.

Emerging bio-medical devices acquire and process large amounts of data, said Boris Murmann, an associate professor in the Department of Electrical Engineering at Stanford University. At the same time, they must typically operate from a battery. Therefore, design and optimization for low-energy consumption has become a major theme in these applications and the industry as a whole. Linderman provided an opportunity for students to conduct research in this important area, Murmann said.

Linderman collaborated with many U.S. universities and one high school, Ogdensburg Free Academy in Ogdensburg, N.Y. The pilot project and medical trials were conducted at Claxton-Hepburn Medical Center, Ogdensburg, N.Y. and Dartmouth-Hitchcock Medical Center, Lebanon, N.H.

Read further: Recognition of Handwriting from Electromyography

Editor's Note: Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author and do not necessarily reflect the views of the National Science Foundation. See the Research in Action archive.