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 (hence Rx). 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 (KUN), in The Netherlands. The department became part of the Nijmegen Institute for Cognition and Information (NICI) and eventually the Centre for Cognition at the Radboud University Nijmegen (RU).
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 (FFT) 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 (Teulings & Maarse, 1984).
The software was expanded and transcribed into plain C during the European ESPRIT projects: P419 "Image and Movement Understanding -- IMU" on Cursive-script recognition (1985–1988) and ESPRIT project P5204 "Pen And Paper Input Recognition Using Script – PAPYRUS (1991–1992).
The software was developed further at the Motor Control Laboratory of Arizona State University, USA (1993–1997) for research on Parkinson's disease and aging.
In 1997, NeuroScript was founded by Dr. Hans-Leo Teulings and Prof. George Stelmach (who has since retired) as a result of a National Institutes of Health (NIH) Small Business and Innovation Research (SBIR) Phase I grant (R43 RR11683: Analysis system for fine motor control) 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 (R44 RR11683 Analysis system for fine motor control). 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 (R44 NS39212 Force measurement and analysis system). 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 (R44 NS38793: Optimization software for goal-directed movements). MovAlyzeR was expanded with interactive and animated audio-visual stimuli and sub-movement analysis.
In 2006, a Phase II grant was awarded (R44 MH073192: Movement Analysis to Monitor Medication). 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 (SAEPS - Simpson-Angus Scale for Extrapyramidal Symptoms and parkinsonism, AIMS – Abnormal Involuntary Movement Scale for tardive dyskinesia, BARS – Barnes Akathisia Rating Scale). Results demonstrated that MovAlyzeR measurements were more sensitive for dosage and medication type than the conventional clinical evaluations.
The putamen is a round structure located at the base of the forebrain (telencephalon). The putamen and caudate nucleus together form the dorsal striatum. It is also one of the structures that compose the basal nuclei. Through various pathways, the putamen is connected to the substantia nigra, the globus pallidus, the claustrum, and the thalamus, in addition to many regions of the cerebral cortex. A primary function of the putamen is to regulate movements at various stages and influence various types of learning. It employs GABA, acetylcholine, and enkephalin to perform its functions. The putamen also plays a role in degenerative neurological disorders, such as Parkinson's disease.
Optical character recognition or optical character reader (OCR) is the electronic or mechanical conversion of images of typed, handwritten or printed text into machine-encoded text, whether from a scanned document, a photo of a document, a scene-photo or from subtitle text superimposed on an image.
Penmanship is the technique of writing with the hand using a writing instrument. Today, this is most commonly done with a pen, or pencil, but throughout history has included many different implements. The various generic and formal historical styles of writing are called "hands" while an individual's style of penmanship is referred to as "handwriting".
Handwriting recognition (HWR), also known as handwritten text recognition (HTR), is the ability of a computer to receive and interpret intelligible handwritten input from sources such as paper documents, photographs, touch-screens and other devices. The image of the written text may be sensed "off line" from a piece of paper by optical scanning or intelligent word recognition. Alternatively, the movements of the pen tip may be sensed "on line", for example by a pen-based computer screen surface, a generally easier task as there are more clues available. A handwriting recognition system handles formatting, performs correct segmentation into characters, and finds the most plausible words.
Handwriting is the writing done with a writing instrument, such as a pen or pencil, in the hand. Handwriting includes both printing and cursive styles and is separate from formal calligraphy or typeface. Because each person's handwriting is unique and different, it can be used to verify a document's writer. The deterioration of a person's handwriting is also a symptom or result of several different diseases. The inability to produce clear and coherent handwriting is also known as dysgraphia.
In psychology, the Stroop effect is the delay in reaction time between congruent and incongruent stimuli.
Dysgraphia is a learning disability of written expression, that affects the ability to write, primarily handwriting, but also coherence. It is a specific learning disability (SLD) as well as a transcription disability, meaning that it is a writing disorder associated with impaired handwriting, orthographic coding and finger sequencing. It often overlaps with other learning disabilities and neurodevelopmental disorders such as speech impairment, attention deficit hyperactivity disorder (ADHD) or developmental coordination disorder (DCD).
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Graphonomics is the interdisciplinary field directed towards the scientific analysis of the handwriting process, product, and other graphic skills.,
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Handwriting movement analysis is the study and analysis of the movements involved in handwriting and drawing. It forms an important part of graphonomics, which became established after the "International Workshop on Handwriting Movement Analysis" in 1982 in Nijmegen, The Netherlands. It would become the first of a continuing series of International Graphonomics Conferences. The first graphonomics milestone was Thomassen, Keuss, Van Galen, Grootveld (1983).
Neuroscience of free will, a part of neurophilosophy, is the study of topics related to free will using neuroscience, and the analysis of how findings from such studies may impact the free will debate.
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Brain connectivity estimators represent patterns of links in the brain. Connectivity can be considered at different levels of the brain's organisation: from neurons, to neural assemblies and brain structures. Brain connectivity involves different concepts such as: neuroanatomical or structural connectivity, functional connectivity and effective connectivity.
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