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Year : 2022  |  Volume : 9  |  Issue : 2  |  Page : 79-86

A study of handwriting sample in geriatric population with cognitive impairment: A cross-sectional observational study

Department of Geriatric Mental Health, King George's Medical University, Lucknow, Uttar Pradesh, India

Correspondence Address:
Dr. V Suresh Heijebu
Department of Geriatric Mental Health, King George's Medical University, Lucknow - 226 003, Uttar Pradesh
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Source of Support: None, Conflict of Interest: None

DOI: 10.4103/jgmh.jgmh_39_22

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Objectives: Cognitive impairment in the geriatric population often remains undiagnosed until progressed enough to cause interruptions in activities of daily living. Routine tests are time taking, requiring a specialist. Handwriting function reflects the brain's cognitive capacity by involving it's both halves. It is easy to collect and does not strain the participant, and can aid in the faster diagnosis of cognitive impairment. Materials and Methods: To study handwriting parameters collected with Livescribe Echo Smart Pen and compare them with cognitive scores of Montreal Cognitive Assessment-Hindi (MOCA-H) and Addenbrooke's Cognitive Examination-Hindi (ACE-H) in a cross-sectional observational study. Handwritten parameters differentiating both cognitive groups were identified and analyzed. Results: The mean age of the study population was 66.4 (5.3) years. The mean MOCA score in the cognitively impaired (CI) and noncognitively (NCI) group was 22.67 and 27.00, respectively. The mean ACE-H score in CI and NCI group was 80.68 and 93.05, respectively. In all handwriting tasks (T1-T3), higher scores were obtained on all parameters in the CI group except text width (TW), stroke frequency (SF), and writing speed (WS). In handwriting task 3 (single letter repetition), WC (word count) was found to be higher in the NCI group. Handwriting parameters of the whole task (TOT, PSPS, TW, TH, NOL, and WS) and text line (MTOL and MTOSS) were found to be helpful in group differentiation in all three tasks. There was a moderate degree of positive correlation with handwriting parameters (PSPS, WS, and WC) and a negative correlation with handwriting parameters (NOPS, TOT, TH, NOL, MHOL, MTOL, and MTOSS) across the tasks with MOCA and ACE scores. Conclusion: Inclusion of quantitative handwriting analysis in neuropsychological assessment can be one step forward towards a simple, reliable, and faster diagnosis of geriatric cognitive impairment.

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