MovAlyzeR


MovAlyzeR is a software package for handwriting movement analysis for research and professional applications. Handwriting movements are recorded using a digitizing tablet connected to a computer. MovAlyzeR is used in many different fields ranging from research in kinesiology, psychology, education, geriatrics, neurology, psychiatry, occupational therapy, forensic document examination or questioned document examination, computer science, to educational demonstrations or student projects in these fields.

Features

MovAlyzeR can be customized for many different pen-movement tests, including goal-directed movements, drawing and handwriting up to a full page of text. It can also process scanned handwriting images for use in, e.g., forensic document examination. Immediately after each trial, consistency with the required pen-movement task is verified so that the user can decide to correct or redo a trial. MovAlyzeR can generate animated audiovisual stimuli which can be edited using its Stimulus Editor.
MovAlyzeRx has the same capability as MovAlyzeR except altering a test. It is designed for medical professionals. The user interface is as simple as possible. No left-clicks are required. The screen layout can be customized. To start testing, just type the patient or participant code.
ScriptAlyzeR handwriting analysis software, is a sub-package of MovAlyzeR excluding visual stimuli and sub-movement analysis.
GripAlyzeR is another flavor of MovAlyzeR for bi-manual force coordination using dedicated hardware: Two grip-force units connected via a magnet of programmable force.

History

The original code of the software was the result of many years of research in handwriting movements. At the core of the software, the signal analysis algorithms that are used have been developed since 1976 when Dr. Hans-Leo Teulings conducted research into the development of handwriting motor control in children in comparison to children with developmental disorders at the Department of Experimental Psychology at the University of Nijmegen, in The Netherlands. The department became part of the Nijmegen Institute for Cognition and Information and eventually the Centre for Cognition at the Radboud University Nijmegen.
These signal analysis algorithms were originally coded in Fortran on Digital's PDP11/34 laboratory computers with 54kB of memory. The algorithms use a complex Fast Fourier Transform to transform both the x and y signals into frequency domain. This allows low-pass filtering and differentiation with zero-phase and ripple free filtering of both x and y signals simultaneously.
The software was expanded and transcribed into plain C during the European ESPRIT projects: P419 "Image and Movement Understanding -- IMU" on Cursive-script recognition and ESPRIT project P5204 "Pen And Paper Input Recognition Using Script – PAPYRUS.
The software was developed further at the Motor Control Laboratory of Arizona State University, USA for research on Parkinson's disease and aging.
In 1997, NeuroScript was founded by Dr. Hans-Leo Teulings and Prof. George Stelmach as a result of a National Institutes of Health Small Business and Innovation Research Phase I grant to conduct a feasibility study into the feasibility of a general purpose handwriting movement analysis system for research.
In 1999, an SBIR Phase II grant was awarded to NeuroScript. The aim was to develop this system into a usable product. The result: the MovAlyzeR software was born - named, designed and implemented by Gregory M. Baker who joined NeuroScript in 1999.
In 2002, NeuroScript received an SBIR Phase II grant. This enabled NeuroScript to generalize MovAlyzeR for bi-manual force coordination: GripAlyzeR. Instead of x and y movement components and axial pen pressure, GripAlyzeR used left and right grip forces and a lift force.
In 2002 NeuroScript received another Phase II grant. MovAlyzeR was expanded with interactive and animated audio-visual stimuli and sub-movement analysis.
In 2006, a Phase II grant was awarded. MovAlyzeR was tested in several major clinics where hundreds of patients were tested for movement side effects due to schizophrenia medication in addition to conventional clinical evaluation. Results demonstrated that MovAlyzeR measurements were more sensitive for dosage and medication type than the conventional clinical evaluations.

Versions

Comparable software

CSWIN by Science and Motion, OASIS by KikoSoft, Pullman Spiral Acquisition and Analysis by Lafayette, NeuroSkill by Verifax, COMpet by University of Haifa, MedDraw by Universities of Kent and Rouen.