TY - JOUR
T1 - Motor Assessment With the STEGA iPad App to Measure Handwriting in Children
AU - Philip, Benjamin A.
AU - Li, Fuhai
AU - Hawkins-Chernof, Elizabeth
AU - Chen, Ling
AU - Swamidass, Victoria
AU - Zwir, Igor
N1 - Funding Information:
We thank Madeline Thompson and Setsu Uzume for their help with data collection. This study was funded by the Eunice Kennedy Shriver National Institute of Child Health and Human Development (R41-HD097833). The Research Electronic Data Capture system was funded by the National Center for Advancing Translational Sciences (UL1-TR000448). The content is solely the responsibility of the authors and does not necessarily represent the official view of the National Institutes of Health.
Funding Information:
funded by the Eunice Kennedy Shriver National Institute of Child Health and Human Development (R41-HD097833). The Research Electronic Data Capture system was funded by the National Center for Advancing Translational Sciences (UL1-TR000448). The content is solely the responsibility of the authors and does not necessarily represent the official view of the National Institutes of Health.
Publisher Copyright:
© 2023 American Occupational Therapy Association, Inc. All rights reserved.
PY - 2023/5
Y1 - 2023/5
N2 - IMPORTANCE: Handwriting and the fine motor control (hand and fingers) underlying it are key indicators of numerous motor disorders, especially among children. However, current assessment methods are expensive, slow, and subjective, leading to a lack of knowledge about the relationship between handwriting and motor control.OBJECTIVE: To develop and validate the iPad precision drawing app Standardized Tracing Evaluation and Grapheme Assessment (STEGA) to enable rapid quantitative assessment of fine motor control and handwriting.DESIGN: Cross-sectional, single-arm observational study.SETTING: Academic research institution.PARTICIPANTS: Fifty-seven typically developing right-handed children ages 9 to 12 yr with knowledge of cursive.OUTCOMES AND MEASURES: Predicted quality, measured as the correlation between handwriting letter legibility (Evaluation Tool of Children's Handwriting-Cursive [ETCH-C]) and predicted legibility (calculated from STEGA's 120 Hz, nine-variable data).RESULTS: STEGA successfully predicted handwriting (r2 = .437, p < .001) using a support vector regression method. Angular error was the most important aspect of STEGA performance. STEGA was much faster to administer than the ETCH-C (M = 6.7 min, SD = 1.3, versus M = 19.7 min, SD = 5.2).CONCLUSIONS AND RELEVANCE: Assessment of motor control (and especially pen direction control) may provide a meaningful, objective way to assess handwriting. Future studies are needed to validate STEGA with a wider age range, but the initial results indicate that STEGA can provide the first rapid, quantitative, high-resolution, telehealth-capable assessment of the motor control that underpins handwriting. What This Article Adds: The ability to control pen direction may be the most important motor skill for successful handwriting. STEGA may provide the first criterion standard for the fine motor control skills that underpin handwriting, suitable for rehabilitation research and practice.
AB - IMPORTANCE: Handwriting and the fine motor control (hand and fingers) underlying it are key indicators of numerous motor disorders, especially among children. However, current assessment methods are expensive, slow, and subjective, leading to a lack of knowledge about the relationship between handwriting and motor control.OBJECTIVE: To develop and validate the iPad precision drawing app Standardized Tracing Evaluation and Grapheme Assessment (STEGA) to enable rapid quantitative assessment of fine motor control and handwriting.DESIGN: Cross-sectional, single-arm observational study.SETTING: Academic research institution.PARTICIPANTS: Fifty-seven typically developing right-handed children ages 9 to 12 yr with knowledge of cursive.OUTCOMES AND MEASURES: Predicted quality, measured as the correlation between handwriting letter legibility (Evaluation Tool of Children's Handwriting-Cursive [ETCH-C]) and predicted legibility (calculated from STEGA's 120 Hz, nine-variable data).RESULTS: STEGA successfully predicted handwriting (r2 = .437, p < .001) using a support vector regression method. Angular error was the most important aspect of STEGA performance. STEGA was much faster to administer than the ETCH-C (M = 6.7 min, SD = 1.3, versus M = 19.7 min, SD = 5.2).CONCLUSIONS AND RELEVANCE: Assessment of motor control (and especially pen direction control) may provide a meaningful, objective way to assess handwriting. Future studies are needed to validate STEGA with a wider age range, but the initial results indicate that STEGA can provide the first rapid, quantitative, high-resolution, telehealth-capable assessment of the motor control that underpins handwriting. What This Article Adds: The ability to control pen direction may be the most important motor skill for successful handwriting. STEGA may provide the first criterion standard for the fine motor control skills that underpin handwriting, suitable for rehabilitation research and practice.
KW - Humans
KW - Child
KW - Cross-Sectional Studies
KW - Mobile Applications
KW - Hand
KW - Fingers
KW - Handwriting
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U2 - 10.5014/ajot.2023.050098
DO - 10.5014/ajot.2023.050098
M3 - Article
C2 - 37310748
AN - SCOPUS:85163901168
SN - 0272-9490
VL - 77
JO - American Journal of Occupational Therapy
JF - American Journal of Occupational Therapy
IS - 3
M1 - 7703205010
ER -