Currently filtering using: All categories and variables
These data are currently available in MARS and Clinical Core.
The RADC digital capture of behavior uses digital pen technology developed by Anoto, Inc. The pen works as an ordinary ballpoint pen while capturing pen position 80 times/second ±0.002. Thus, the data reported by the pen is time-stamped, allowing the pen to capture the final product (i.e., the clock drawing) as well as the behavior that produced it for more accurate classifications than would be possible without this technology.
Currently, behavior is captured during a digital Clock Drawing Test (dCDT) that was originally developed by the Lahey Clinic and Massachusetts Institute of Technology in collaboration with the Clock Sketch Consortium. Upon retrieval of the digital pen data, raw data are downloaded, viewed, and scored using a semi-automated program for both the Command and Copy condition in which participants are asked to either spontaneously “draw the face of a clock with all of the numbers and set the hands to 10 after 11” or copy a model of a clock with the hands set for “10 after 11.” The Copy condition is always presented immediately after the Command condition.
Pipelines to capture and process all graphomotor behavior using digital pen technology that is part of the RADC cognitive evaluation (e.g., pentagons, sentence from the MMSE) are in progress.
Raw data file available - subject to committee review.
Test procedure: Goodglass H & Kaplan E: The assessment of aphasia and related disorders, Philadelphia, Lea & Febiger. Ann Neurol, 1983; 16: 625.
Lamar M, Ajilore O, Leow A, Charlton R, Cohen J. GadElkarim J, Yang S, Zhang A, Davis R, Penney D, Libon DJ & Kumar A: Cognitive and connectome properties detectable through individual differences in graphomotor organization. Neuropsychologia, 2016; 85: 301-309. PMID: 27037044 PMCID: PMC4853274
Souillard-Mandar W, Davis R, Rudin C, Au R, Libon DJ, Swenson R, Price CC, Lamar M & Penney D. Learning classification models of cognitive conditions from subtle behaviors in the digital Clock Drawing Test. Machine Learning, 2016; 102: 393-441. PMID: 27057085 PMCID: PMC4821477
Cohen J, Penney DL, Davis R, Libon DJ, Ajilore O, Kumar A & Lamar M. Digital clock drawing: Differentiating ‘thinking’ versus ‘doing’ in younger and older adults with depression. The Journal of the International Neuropsychological Society, 2014; 20: 920-928. PMCID: PMC4310546
Piers RJ, Devlin KN, Ning B, Liu Y, Wasserman B, Massaro JM, Lamar M, Price CC, Swenson R, Davis R, Penney DL, Au R & Libon DJ. Age and graphomotor decision making assessed with the Digital Clock Drawing Test: The Framingham Heart Study. Journal of Alzheimer’s Disease, 2017; 60(4), 1611-1620. PMID: 29036819
|Number of strokes (Command)||Total number of strokes in command condition|
|Number of strokes (Copy)||Total number of strokes in copy condition|
|Completion time (Command)||Total time to completion of command condition|
|Completion time (Copy)||Total time to completion of copy condition|
|Percent ink time (Command)||Total time pen is in contact with paper in command condition|
|Percent ink time (Copy)||Total time pen is in contact with paper in copy condition|
|Percent think time (Command)||Total time pen is not in contact with paper in command condition|
|Percent think time (Copy)||Total time pen is not in contact with paper in copy condition|
|Latency time (Command)||Total latency time in command condition|
|Latency time (Copy)||Total latency time in copy condition|