Decomposing cognitive-motor planning from execution: smartphone motor sequencing provides scalable digital biomarkers of cognitive-motor function across central nervous system disorders

The study examined the ability to plan and execute complex ordered motor actions using a digitalized smartphone task based on Luria's fist-edge-palm test. The study included 296 participants: 34 healthy individuals, 208 people with multiple sclerosis (MS), and 54 individuals with other neurological disorders. Researchers identified seven digital biomarkers measuring speed, accuracy, and performance. Six biomarkers significantly differentiated between groups according to disease severity, with motor sequencing deficit showing the strongest group separation (r=0.73, p=1.1x10-21). Analysis revealed distinct patterns in different MS types: secondary-progressive MS was characterized by slow and inaccurate execution (84%), while primary-progressive MS showed slow but accurate compensatory behavior (19%). A combined two-biomarker test achieved high diagnostic accuracy (concordance index = 0.868) and strongly correlated with brain tissue damage on MRI and clinical disability scales.