Enhancing MCI Assessment: A Digital Trail Making Test with Integrated Eye and Hand Tracking

TL;DR

A digital version of the Trail Making Test with eye and hand tracking helps detect cognitive impairments more accurately than traditional methods.

Contribution

Integrating eye and hand tracking into the Trail Making Test reveals new digital biomarkers for Mild Cognitive Impairment.

Findings

MCI patients showed significantly longer scanpaths compared to controls.

Eye and hand movement analysis provides more detailed insights than total completion time.

Fixation patterns differ by trial type but not by subject group.

Abstract

We extended our computerized Trail Making Test (c‐TMT) to investigate deficits in Mild Cognitive Impairment (MCI) compared to neurotypical controls. By integrating hand and eye tracking, we captured fine‐grained movement dynamics, revealing distinct trajectory alterations in MCI patients. These differences suggest potential digital biomarkers, offering a more precise assessment beyond traditional total time measurements.

Twenty‐nine MCI patients and 28 age‐ and education‐matched controls (with significant Mini‐Mental Test differences, p < 0.001) were enrolled at Hospital Italiano de Buenos Aires, Argentina, with informed consent. Two practice trials and 20 experimental trials (alternating TMT‐A and TMT‐B) were presented. Stimuli were displayed on a 24‐inch screen. Gaze was recorded from the right eye at 500 Hz using an EyeLink 1000 Plus. The mouse trajectory was displayed in real‐time, with feedback on the correct element selection.

Linear Mixed Models (LMM) were applied to correct trials to estimate the main effects of subject group (MCI vs. control), trial type (TMT‐A vs. TMT‐B), and their interaction using the statsmodels library in Python. For performance metrics, LMM revealed a significant effect of subject group and trial type on the percentage of completion (PC) (SE = 0.066, p = 0.040; SE = ‐9.017, p = 1.9 × 10−19) and the time required to complete a trial (RT) (SE = ‐2.514, p = 0.012; SE = 7.896, p = 2.9 × 10−15). For eye‐tracking metrics, we found significant differences for both trial type (SE = 2.06, p = 0.002) and subject group (SE = 2.81, p = 0.023) in scanpath length (number of fixations). However, fixation duration differences were not significant (SE = 7.830, p = 0.68; SE = 12.90, p = 0.80). We also analyzed eye‐hand coordination by parsing fixations based on mouse position and time‐locking mouse and hand movements to target entry. Differences were observed by trial type but not by subject group.

Our c‐TMT version identified significant differences in scanpath length between MCI patients and controls. Hand and eye movements together allow fixation analysis to determine how increased fixations are distributed. These findings highlight the potential of this approach in Digital Neuropsychology.

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