Detailed Assessment of Speed of Handwriting (DASH 17+) assessment provides information about the speed and legibility of handwriting. Handwriting difficulties in general and DASH17+ performance, in particular, are signs of neuromotor difficulties. Individualized interventions can be developed with a better understanding of both the biomechanical and neurological underpinnings of the task. We used a multimodal assessment strategy to deconstruct the product and process of handwriting measures in adults. A total of 23 neurotypical college age adults took part in the study. We combined the standardized norm-referenced test DASH17+ and explored the online process of handwriting using the MovAlyzeR software, and simultaneously explored prefrontal cortex activity, using functional near infrared spectroscopy (fNIRS), during the task execution. Our research indicated that underlying neural and kinematic mechanisms changed between tasks, within tasks, and even from one trial block to another that are not reflected in the DASH17+ performance assessment alone. Therefore, this multi-modal approach provides a promising method in clinical populations to further investigate any subtle change in handwriting.
Gargot, T., et al. (2020) Acquisition of Handwriting in Children with and without Dysgraphia: A Computational Approach. PLOS ONE, 15, e0237575. https://doi.org/10.1371/journal.pone.0237575
Thomas, M., Lenka, A. and Kumar Pal, P. (2017) Handwriting Analysis in Parkinson’s Disease: Current Status and Future Directions. Movement Disorders Clinical Practice, 4, 806-818. https://doi.org/10.1002/mdc3.12552
Crespo, Y., Ibañez, A., Soriano, M.F., Iglesias, S. and Aznarte, J.I. (2019) Handwriting Movements for Assessment of Motor Symptoms in Schizophrenia Spectrum Disorders and Bipolar Disorder. PLOS ONE, 14, e0213657. https://doi.org/10.1371/journal.pone.0213657
Press, H.A., Hinojosa, J. and Roston, K.L. (2009) Improving a Child’s Writing Skills for Increased Attention to Academic Activities. Journal of Occupational Therapy, Schools, & Early Intervention, 2, 171-177. https://doi.org/10.1080/19411240903392566
Summers, J. and Catarro, F. (2003) Assessment of Handwriting Speed and Factors Influencing Written Output of University Students in Examinations. Australian Occupational Therapy Journal, 50, 148-157. https://doi.org/10.1046/j.1440-1630.2003.00310.x
Barnett, A.L., Henderson, S.E., Scheib, B. and Schulz, J. (2009) Development and Standardization of a New Handwriting Speed Test: The Detailed Assessment of Speed of Handwriting. British Journal of Educational Psychology, 2, 137-157. https://doi.org/10.1348/000709909X421937
Barnett, A., Henderson, S.E., Scheib, B. and Schulz, J. (2010) Dash 17+: Detailed Assessment of Speed of Handwriting 17+: Manual. Pearson, London.
Prunty, M.M., Barnett, A.L., Wilmut, K. and Plumb, M.S. (2014) An Examination of Writing Pauses in the Handwriting of Children with Developmental Coordination Disorder. Research in Developmental Disabilities, 35, 2894-2905. https://doi.org/10.1016/j.ridd.2014.07.033
Jolly, C. and Gentaz, E. (2014) Analysis of Cursive Letters, Syllables, and Words Handwriting in a French Second-Grade Child with Developmental Coordination Disorder and Comparison with Typically Developing Children. Frontiers in Psychology, 4, Article No. 1022. https://doi.org/10.3389/fpsyg.2013.01022
Rosenblum, S. and Livneh-Zirinski, M. (2008) Handwriting Process and Product Characteristics of Children Diagnosed with Developmental Coordination Disorder. Human Movement Science, 27, 200-214. https://doi.org/10.1016/j.humov.2008.02.011
Alamargot, D., Caporossi, G., Chesnet, D. and Ros, C. (2011) What Makes a Skilled Writer? Working Memory and Audience Awareness during Text Composition. Learning and Individual Differences, 21, 505-516. https://doi.org/10.1016/j.lindif.2011.06.001
Prunty, M.M., Barnett, A.L., Wilmut, K. and Plumb, M.S. (2016) The Impact of Handwriting Difficulties on Compositional Quality in Children with Developmental Coordination Disorder. British Journal of Occupational Therapy, 79, 591-597. https://doi.org/10.1177/0308022616650903
Koiler, R., et al. (2022) The Impact of Fidget Spinners on Fine Motor Skills in Individuals with and without ADHD: An Exploratory Analysis. Journal of Behavioral and Brain Science, 12, 82-101. https://doi.org/10.4236/jbbs.2022.123005
Milla, K., Bakhshipour, E., Bodt, B. and Getchell, N. (2019) Does Movement Matter? Prefrontal Cortex Activity during 2D vs. 3D Performance of the Tower of Hanoi Puzzle. Frontiers in Human Neuroscience, 13, Article No. 156. https://doi.org/10.3389/fnhum.2019.00156
Liang, L.-Y., Chen, J.-J.J., Shewokis, P.A. and Getchell, N. (2016) Developmental and Condition-Related Changes in the Prefrontal Cortex Activity during Rest. Journal of Behavioral and Brain Science, 6, 485-497. https://doi.org/10.4236/jbbs.2016.612044
Ayaz, H., Shewokis, P.A., Bunce, S., Izzetoglu, K., Willems, B. and Onaral, B. (2012) Optical Brain Monitoring for Operator Training and Mental Workload Assessment. Neuroimage, 59, 36-47. https://doi.org/10.1016/j.neuroimage.2011.06.023
Ferrari, M. and Quaresima, V. (2012) A Brief Review on the History of Human Functional Near-Infrared Spectroscopy (fNIRS) Development and Fields of Application. Neuroimage, 63, 921-935. https://doi.org/10.1016/j.neuroimage.2012.03.049
Scholkmann, F., et al. (2014) A Review on Continuous Wave Functional Near-Infrared Spectroscopy and Imaging Instrumentation and Methodology. Neuroimage, 85, 6-27. https://doi.org/10.1016/j.neuroimage.2013.05.004
Wilcox, T. and Biondi, M. (2015) fNIRS in the Developmental Sciences. Wiley Interdisciplinary Reviews: Cognitive Science, 6, 263-283. https://doi.org/10.1002/wcs.1343
Lloyd-Fox, S., Blasi, A. and Elwell, C.E. (2010) Illuminating the Developing Brain: The Past, Present and Future of Functional Near-Infrared Spectroscopy. Neuroscience and Biobehavioral Reviews, 34, 269-284. https://doi.org/10.1016/j.neubiorev.2009.07.008
Shimoda, K., Moriguchi, Y., Tsuchiya, K., Katsuyama, S. and Tozato, F. (2014) Activation of the Prefrontal Cortex while Performing a Task at Preferred Slow Pace and Metronome Slow Pace: A Functional Near-Infrared Spectroscopy Study. Neural Plasticity, 2014, Article ID: 269120. https://doi.org/10.1155/2014/269120
McKendrick, R., et al. (2016) Into the Wild: Neuroergonomic Differentiation of Hand-Held and Augmented Reality Wearable Displays during Outdoor Navigation with Functional Near-Infrared Spectroscopy. Frontiers in Human Neuroscience, 10, Article No. 216. https://doi.org/10.3389/fnhum.2016.00216
Koiler, R. (2021) Development of a Portable Electromyography Biofeedback Device for Gait Rehabilitation and Associated Neuromechanical Analysis. University of Delaware, Newark.
Koiler, R., Bakhshipour, E. and Gettchell, N. (2022) Using fNIRS to Detect Prefrontal Cortex Changes due to EMG Biofeedback Walking and Training in Healthy Adults. Journal of Sport and Exercise Psychology, 44, S41.
Khan, H., Naseer, N., Yazidi, A., Eide, P.K., Hassan, H.W. and Mirtaheri, P. (2021) Analysis of Human Gait Using Hybrid EEG-fNIRS-Based BCI System: A Review. Frontiers in Human Neuroscience, 14, Article No. 605. https://doi.org/10.3389/fnhum.2020.613254
Bakhshipour, E., Koiler, R., Milla, K. and Getchell, N. (2021) Understanding the Cognitive Demands of the Purdue Pegboard Test: An fNIRs Study. Advances in Intelligent Systems and Computing, Vol. 1201, 55-61. https://doi.org/10.1007/978-3-030-51041-1_8
Koiler, R., Bakhshipour, E., Milla, K., Plumb, M. and Getchell, N. (2019) Understanding Handwriting Pauses in the Detailed Assessment of Speed of Handwriting Test using fNIRs. Journal of Sport and Exercise Psychology, 41, S38.
Koiler, R., et al. (2021) Fidget Spinners May Decrease Prefrontal Cortex Activity during Cognitively Challenging Fine Motor Tasks. Advances in Intelligent Systems and Computing, 1201, 69-75. https://doi.org/10.1007/978-3-030-51041-1_10
Caçola, P., Getchell, N., Srinivasan, D., Alexandrakis, G. and Liu, H. (2018) Cortical Activity in Fine-Motor Tasks in Children with Developmental Coordination Disorder: A Preliminary fNIRS Study. International Journal of Developmental Neuroscience, 65, 83-90. https://doi.org/10.1016/j.ijdevneu.2017.11.001
Kawato, M. (1999) Internal Models for Motor Control and Trajectory Planning. Current Opinion in Neurobiology, 9, 718-727. https://doi.org/10.1016/S0959-4388(99)00028-8
Mita, A., Mushiake, H., Shima, K., Matsuzaka, Y. and Tanji, J. (2009) Interval Time Coding by Neurons in the Presupplementary and Supplementary Motor Areas. Nature Neuroscience, 12, 502-507. https://doi.org/10.1038/nn.2272
Wood, J.N. and Grafman, J. (2003) Human Prefrontal Cortex: Processing and Representational Perspectives. Nature Reviews Neuroscience, 4, 139-147. https://doi.org/10.1038/nrn1033
Jonides, J., Smith, E.E., Koeppe, R.A., Awh, E., Minoshima, S. and Mintun, M.A. (1993) Spatial Working Memory in Humans as Revealed by PET. Nature, 363, 623-625. https://doi.org/10.1038/363623a0
Pardo, J.V., Fox, P.T. and Raichle, M.E. (1991) Localization of a Human System for Sustained Attention by Positron Emission Tomography. Nature, 349, 61-64. https://doi.org/10.1038/349061a0
Posner, M.I., Rothbart, M.K., Sheese, B.E. and Tang, Y. (2007) The Anterior Cingulate Gyrus and the Mechanism of Self-Regulation. Cognitive, Affective, & Behavioral Neuroscience, 7, 391-395. https://doi.org/10.3758/CABN.7.4.391
Ridderinkhof, K.R., Ullsperger, M., Crone, E.A. and Nieuwenhuis, S. (2004) The Role of the Medial Frontal Cortex in Cognitive Control. Science, 306, 443-447. https://doi.org/10.1126/science.1100301
Euston, D.R., Gruber, A.J. and McNaughton, B.L. (2012) The Role of Medial Prefrontal Cortex in Memory and Decision Making. Neuron, 76, 1057-1070. https://doi.org/10.1016/j.neuron.2012.12.002
Caligiuri, M.P., Teulings, H.L., Filoteo, J.V., Song, D. and Lohr, J.B. (2006) Quantitative Measurement of Handwriting in the Assessment of Drug-Induced Parkinsonism. Human Movement Science, 25, 510-522. https://doi.org/10.1016/j.humov.2006.02.004
Ayaz, H., Onaral, B., Izzetoglu, K., Shewokis, P.A., Mckendrick, R. and Parasuraman, R. (2013) Continuous Monitoring of Brain Dynamics with Functional Near-Infrared Spectroscopy as a Tool for Neuroergonomic Research: Empirical Examples and a Technological Development. Frontiers in Human Neuroscience, 7, Article No. 871. https://doi.org/10.3389/fnhum.2013.00871
Nguyen, T., Condy, E.E., Park, S., Friedman, B.H. and Gandjbakhche, A. (2021) Comparison of Functional Connectivity in the Prefrontal Cortex during a Simple and an Emotional Go/No-Go Task in Female versus Male Groups: An fNIRS Study. Brain Sciences, 11, Article No. 909. https://doi.org/10.3390/brainsci11070909
Dashtestani, H., et al. (2018) The Role of Prefrontal Cortex in a Moral Judgment Task Using Functional Near-Infrared Spectroscopy. Brain and Behavior, 8, e01116. https://doi.org/10.1002/brb3.1116
Homan, R.W., Herman, J. and Purdy, P. (1987) Cerebral Location of International 10 - 20 System Electrode Placement. Electroencephalography and Clinical Neurophysiology, 66, 376-382. https://doi.org/10.1016/0013-4694(87)90206-9
Zimeo Morais, G.A., Balardin, J.B. and Sato, J.R. (2018) fNIRS Optodes’ Location Decider (fOLD): A Toolbox for Probe Arrangement Guided by Brain Regions-of-Interest. Scientific Report, 8, Article No. 3341. https://doi.org/10.1038/s41598-018-21716-z
Peirce, J., et al. (2019) PsychoPy2: Experiments in Behavior Made Easy. Behavior Research Methods, 51, 195-203. https://doi.org/10.3758/s13428-018-01193-y
Hartzheim, D.U., Foley, B., Studenka, B., Gillam, S.L. and Mclellan, M.R. (2015) Comparison of Neurological Activation Patterns of Children with and without Autism Spectrum Disorders when Verbally Responding to a Pragmatic Task.
Liang, L.-Y. (2015) Prefrontal Cortex Activity during Resting and Task States as Measured by Functional Near-Infrared Spectroscopy. University of Delaware, Newark.
Delpy, D.T., Cope, M., Van Der Zee, P., Arridge, S., Wray, S. and Wyatt, J. (1988) Estimation of Optical Path Length through Tissue from Direct Time of Flight Measurement. Physics in Medicine & Biology, 33, 1433-1442. https://doi.org/10.1088/0031-9155/33/12/008
Zhang, H., Duan, L., Zhang, Y.J., Lu, C.M., Liu, H. and Zhu, C.Z. (2011) Test-Retest Assessment of Independent Component Analysis-Derived Resting-State Functional Connectivity Based on Functional Near-Infrared Spectroscopy. Neuroimage, 55, 607-615. https://doi.org/10.1016/j.neuroimage.2010.12.007
Liang, L.-Y. et al. (2016) Developmental and Condition-Related Changes in the Prefrontal Cortex Activity during Rest. Journal of Behavioral and Brain Science, 6, 485-497. https://doi.org/10.4236/jbbs.2016.612044
Liang, L.-Y., Shewokis, P.A., Getchell, N., Liang, L.-Y., Shewokis, P.A. and Getchell, N. (2016) Brain Activation in the Prefrontal Cortex during Motor and Cognitive Tasks in Adults. Journal of Behavioral and Brain Science, 6, 463-474. https://doi.org/10.4236/jbbs.2016.612042
Strangman, G., Boas, D.A. and Sutton, J.P. (2002) Non-Invasive Neuroimaging Using Near-Infrared Light. Biological Psychiatry, 52, 679-693. https://doi.org/10.1016/S0006-3223(02)01550-0
Hoshi, Y. (2007) Functional Near-Infrared Spectroscopy: Current Status and Future Prospects. Journal of Biomedical Optics, 12, Article ID: 062106. https://doi.org/10.1117/1.2804911
Manoj, K. and Kannan, S.K. (2013) Comparison of Methods for Detecting Outliers. International Journal of Scientific and Engineering Research, 4, 709-714.
Allen, M., et al. (2021) Raincloud Plots: A Multi-Platform Tool for Robust Data Visualization. Wellcome Open Research, 4, Article No. 63. https://doi.org/10.12688/wellcomeopenres.15191.2
Mizrahi, J. (2015) Mechanical Impedance and Its Relations to Motor Control, Limb Dynamics, and Motion Biomechanics. Journal of Medical and Biological Engineering, 35, 1-20. https://doi.org/10.1007/s40846-015-0016-9
Kaller, C.P., Rahm, B., Köstering, L. and Unterrainer, J.M. (2011) Reviewing the Impact of Problem Structure on Planning: A Software Tool for Analyzing Tower Tasks. Behavioural Brain Research, 216, 1-8. https://doi.org/10.1016/j.bbr.2010.07.029
Olive, T., Favart, M., Beauvais, C. and Beauvais, L. (2009) Children’s Cognitive Effort and Fluency in Writing: Effects of Genre and of Handwriting Automatisation. Learning and Instruction, 19, 299-308. https://doi.org/10.1016/j.learninstruc.2008.05.005
Deepak, K.K. and Behari, M. (1999) Specific Muscle EMG Biofeedback for Hand Dystonia. Applied Psychophysiology and Biofeedback, 24, 267-280. https://doi.org/10.1023/A:1022239014808
Koiler, R., Bakhshipour, E., Glutting, J., Lalime, A., Kofa, D. and Getchell, N. (2021) Repurposing an EMG Biofeedback Device for Gait Rehabilitation: Development, Validity and Reliability. International Journal of Environmental Research and Public Health, 18, Article No. 6460. https://doi.org/10.3390/ijerph18126460
Feder, K.P. and Majnemer, A. (2007) Handwriting Development, Competency, and Intervention. Developmental Medicine & Child Neurology, 49, 312-317. https://doi.org/10.1111/j.1469-8749.2007.00312.x