As the burden of neurodegenerative diseases increases, time-limited clinic encounters do not allow quantification of complex neurological functions. Patient-collected digital biomarkers may remedy this, if they provide reliable information. However, psychometric properties of digital tools remain largely un-assessed. We developed a smartphone adaptation of the cognitive test, the Symbol-Digit Modalities Test (SDMT) by randomizing the test's symbol-number codes and testing sequences. The smartphone SDMT showed comparable psychometric properties in 154 multiple sclerosis (MS) patients and 39 healthy volunteers (HV). E.g., smartphone SDMT achieved slightly higher correlations with cognitive subscores of neurological examinations and with brain injury measured by MRI (R2 = 0.75, Rho = 0.83, p < 0.0001) than traditional SDMT. Mathematical adjustment for motoric disability of the dominant hand, measured by another smartphone test, compensates for the disadvantage of touch-based test. Averaging granular home measurements of the digital biomarker also increases accuracy of identifying true neurological decline.