Source: Ecole Polytechnique Federale de Lausanne
Summary: Researchers have developed a software program that can analyze these children’s writing disabilities and their causes with unparalleled precision.
Writing is an essential skill for schoolchildren, but it requires an adroit combination of careful concentration, well-developed motor skills, and good language comprehension – something that not all children possess. Trouble learning how to write, called dysgraphia, affects some 10% of schoolchildren. This learning disability is often associated with dyslexia and can appear in children to varying degrees, with causes that can differ from one child to the next. A team of researchers at EPFL’s Computer-Human Interaction in Learning and Instruction Laboratory (CHILI) has developed software that enables doctors to make highly detailed, personalized assessments of this disability and to accurately identify the letters and numbers that are most difficult and are thus the most discriminative. The study findings were published in the journal Nature Digital Medicine.
The test developed at EPFL, called Tegami, which is run using a tablet computer, represents a major step forward in terms of analytical precision and accuracy of input. It was developed from a database of writing samples from 300 children, around 25% of whom suffered from dysgraphia. The program was able to detect the learning disability 98% of the time. The big advantage of Tegami is that it can help pinpoint the cause of a child’s dysgraphia because it analyzes no fewer than 53 different characteristics of a child’s writing, which are measured up to 200 times per second. These characteristics include the angle of the pen, the amount of pressure the child applies to the tablet, how fast the child writes and any changes in that speed, whether the child’s hand trembles and if so, with what frequency, and which letters or characters are most discriminative.
The EPFL researchers are now working with psychomotor therapists and speech therapists to outline remedial measures; for example, if a child shows too much variation in the pressure he puts on his pen, his doctor can prescribe motor-skill exercises.
More Information: Thibault Asselborn et al, “Automated human-level diagnosis of dysgraphia using a consumer tablet”, npj Digital Medicine (2018). DOI: 10.1038/s41746-018-0049-x