Online Analysis of Handwriting for Disease Diagnosis: A Review

  • Authors

    • Seema Kedar
    • D. S. Bormane
    • Sandeep Joshi
    https://doi.org/10.14419/ijet.v7i3.24.22802
  • Handwriting Analysis, Handwriting Features, Tablet, Disease.
  • Background/Objectives: Handwriting is an action governed by brain like any other action. This process is usually unconscious and is closely tied to impulses from brain. Any kind of disease affects the kinetic movement and reflects in subject’s handwriting. To understand the health and mental problems, it is important to focus on how subject writes instead of what subject writes. This also makes the process of handwriting analysis independent of any language. Handwriting analysis is a pseudo-science used to study physical and behavioral characteristics of handwriting. In this paper, the general approach used for the disease diagnosis based on digital handwriting analysis has been presented. The research work carried out to diagnose diseases such as Alzheimer, Mild Cognitive Impairment, Dysgraphia, Schizophrenia, Autism, Parkinson’s disease and Mental illness based on digital handwriting analysis has been reviewed in this paper. The features related to motion, time and pressure have been used for diagnosis of disease. The experiments and results are also summarized in this paper.

     

  • References

    1. [1] Cronje, Pierre E. and Hester E Roets, “Graphology in Psychological Assessment: A Diagnosis in Writingâ€, Universal Journal of Psychology, vol. 1, No. 4, pages: 163-168, 2013.

      [2] Bora Ugurlu, Rembiye Kandemir, Aydn Carus, Ercan Abay, “An Expert System for Determining the Emotional Change on a Critical Event Using Handwriting Featuresâ€, TEM Journal, vol. 5, Issue 4, Pages 480-486, 2016.

      [3] Emotions and Feelings, Available from: http://graphicinsight.co.za/emotions.htm.

      [4] Handwriting analysis and health, Available from: http://www.handwriting-graphology.com/handwriting-analysis-and-health-graphopathology.

      [5] Learn Graphology, Available from: http://www.handwriting-graphology.com/learn-graphology/

      [6] Zainab Harbiab, Yulia Hicksa and Rossitza Setchia, “Clock Drawing Test Digit Recognition Using Static and Dynamic Featuresâ€, Procedia Computer Science, vol. 112, Issue C, September 2017, Pages 1641-1650, 2017.

      [7] MMSE Test, Available from: https://www.healthdirect.gov.au/mini-mental-state-examination-mmse

      [8] House Tree and Person test, Available from: https://healthfully.com/interpret-housetreeperson-test-8631546.html

      [9] Xu-Yao Zhang, Guo-Sen Xie, Cheng-Lin Liu, and Yoshua Bengio, “End-to-End Online Writer Identification with Recurrent Neural Networkâ€, IEEE Transactions on Human-Machine Systems, vol. 47, Issue: 2, 2017.

      [10] Andrew Seniuk and Dorothea Blostein, “Pen Acoustic Emissions for Text and Gesture Recognitionâ€, 10th International Conference on Document Analysis and Recognition, 2009.

      [11] Laurence Likforman-Sulem, Anna Esposito, Marcos Faundez-Zanuy, Stephan Clemencon and Gennaro Cordasco, “EMOTHAW: A Novel Database for Emotional State Recognition from Handwriting and Drawingâ€, IEEE Transaction on Human-Machine Systems, 2017.

      [12] Essentials of Machine Learning Algorithms, Available from: https://www.analyticsvidhya.com/blog/2017/09/common-machine- learning-algorithms

      [13] Anova Test, Available from: http://www.statisticshowto.com/probability-and-statistics/hypothesis-testing/anova/

      [14] Naive Bayes Classifier, Available from: https://en.wikipedia.org/wiki/Naive Bayes classifier

      [15] K-means Algorithm, Available from: https://en.wikipedia.org/wiki/K-meansclustering

      [16] Random Forest Tree Generation, Available from: http://dataaspirant.com/2017/05/22/random-forest-algorithm-machine-learing/

      [17] Alzheimer’s disease, Available from: https://simple.wikipedia.org/wiki/Alzheimer’s disease

      [18] Perla Werner, Sara Rosenblum, Gady Bar-On, Jeremia Heinik and Amos Korczyn, “Handwriting Process Variables Discriminating Mild Alzheimer’s Disease and Mild Cognitive Impairmentâ€, The Journals of Gerontology: Series B, vol 61, Issue 4, Pages P228–P236, 2006.

      [19] Paola Fontana, Francesca Dagnino, Leonardo Cocito and Maurizio Balestrino, “Handwriting as a gauge of cognitive status: a novel forensic tool for posthumous evaluation of testamentary capacityâ€, Neurol Sci., 29(4):257-61, 2008.

      [20] Murad Badarna, Ilan Shimshoni, Gil Luria and Sara Rosenblum, “The Importance of Pen Motion Pattern Groups for Semi-Automatic Classification of Handwriting into Mental Workload Classesâ€, Cognitive Computation, vol. 10(2): 215-227, 2017.

      [21] Understanding Dysgraphia By Erica Patino, Available from: https://www.understood.org/en/learningattentionissues/childlearning-disabilities/dysgraphia/understanding-dysgraphia

      [22] Jiri Mekyska, Marcos Faundez-Zanuy, “Identification and Rating of Developmental Dysgraphia by Handwriting Analysisâ€, IEEE Transactions on Human-Machine Systems, vol. 47, Issue: 2, 2017.

      [23] Sara Rosenblum, Patrice L. Weiss and Shula Parush, “Handwriting evaluation for developmental dysgraphia: Process versus productâ€, Kluwer Academic Publishers, 2004.

      [24] Sara Rosenblum and Gideon Dror, “Identifying Developmental Dysgraphia Characteristics Utilizing Hand- writing Classification Methodsâ€, IEEE Transactions on Human-Machine Systems, vol. 47, Issue: 2, 2017.

      [25] Schizophrenia, Available from: https://faculty.washington.edu/chudler/schiz.html

      [26] Michael P. Caligiuri, Hans-Leo Teulings, Charles E. Alexander B. Niculescu, James Lohr, “Handwriting Movement Analyses for Monitoring Drug-Induced Motor Side Effects in Schizophrenia Patients Treated with Risperidoneâ€, Hum Mov Sci., vol. 28(5): 633–642, 2009.

      [27] M. Borjkhani, M. Ahmadlou, F. Towhidkhah, “Extracting Reliable Handwriting Kinematic Features by Using Neural Network for Diagnosing Schizophrenia Diseaseâ€, Biomedical Engineering Conference, 2008.

      [28] Crystal R. Blyler, Brendan A. Maher, Theo C. Manschreck and Wayne S. Fenton, “Line drawing as a possible measure of lateralized motor performance in schizophreniaâ€, Schizophrenia Research, vol. 26, Issue 1, Pages 15-23, 1997.

      [29] What is Autism in Simple Terms, Available from: https://www.dealwithautism.com/whatisautisminsimpleterms/

      [30] Sara Rosenblum, “Children with high-functioning autism spectrum disorder show unique handwriting patternsâ€, University of Haifa. Available from: https://www.sciencedaily.com/releases/2016/06/160601084649.htm.

      [31] Nicci Grace, Peter Gregory Enticott, Beth Patricia Johnson, Nicole Joan Rinehart, “Do Handwriting Difficulties Correlate with Core Symptomology, Motor Proficiency and Attentional Behaviours?â€, Journal of autism and developmental disorders, 2017.

      [32] Azadeh Kushki, Tom Chau, Evdokia Anagnostou, “Handwriting Difficulties in Children with Autism Spectrum Disorders: A Scoping Reviewâ€, Journal of Autism and Developmental Disorders, vol. 41, Issue 12, pp 1706–1716, 2011.

      [33] What is Depression, Anxiety and Stress, Available from: https://www.psychologytoday.com/basics/depression

      [34] Psychology Today, Available from: https://www.psychologytoday.com/

      [35] DASS Assessment, Available from: https://openpsychometrics.org/tests/DASS/

      [36] Clara Rispler, Gil Luria, Allon Kahana, Sara Rosenblum, “Mood Impact on Automaticity of Performance: Handwriting as Exemplarâ€, Cognitive Computation, 2018.

      [37] Sara Rosenblum, Perla Werner, Tal Dekel, Ilya Gurevitz and Jeremia Heinik, “Handwriting process variables among elderly people with mild Major Depressive Disorder: A Preliminary Studyâ€, Aging Clinical and Experimental Research, vol. 22, Issue 2, pp 141–147, 2010.

      [38] Parkinson’s disease, Available from: https://simple.wikipedia.org/wiki/Parkinson

      [39] Michael P. Caligiuri, Hans-Leo Teulings, J. Vincent Filoteo, David Song, James B. Lohr, “Quantitative measurement of handwriting in the assessment of drug- induced parkinsonismâ€, Human Movement Science, vol. 25, pp 510–522, 2006.

      [40] Naiqian Zhi, Beverly Kris Jaeger, “Toward Monitoring Parkinson’s through Analysis of Static Handwriting Samplesâ€, IEEE Journal of Biomedical and Health Informatics, vol.: 21, Issue: 2, 2017.

      [41] O. Tucha, L. Mecklinger, J. Thome, A. Reiter, G. L. Alders, H. Sartor, M. Naumann, and K. W. Lange, “Kinematic analysis of dopaminergic effects on skilled handwriting movements in Parkinson’s diseaseâ€, Journal of Neural Transmission, vol. 113, Issue 5, pp 609–623, 2006.

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    Kedar, S., S. Bormane, D., & Joshi, S. (2018). Online Analysis of Handwriting for Disease Diagnosis: A Review. International Journal of Engineering & Technology, 7(3.24), 505-511. https://doi.org/10.14419/ijet.v7i3.24.22802