Journal: NPJ Digital Medicine

Article Title: Continuous assessment of daily-living gait using self-supervised learning of wrist-worn accelerometer data

doi: 10.1038/s41746-026-02528-2

Figure Lengend Snippet: Curves represent mean values (±1 standard deviation across 10 folds) obtained from nested cross-validation. Three different feature sets were compared: supervised-based accelerometry features (blue) extracted from standardized walking tests (8-ft and 32-ft walks) measuring gait speed, step length, cadence, and stride regularity; physical activity features (red) and gait quality features (green) extracted from daily-living accelerometer data. Classification performance, indicated by the area under the curve (AUC), improved from supervised-based features (AUC = 0.67 ± 0.09) to physical activity features (AUC = 0.69 ± 0.06), and was highest when using all available wrist multi-day gait metrics (AUC = 0.80 ± 0.06). A Friedman test showed a significant effect of feature set on AUC ( p < 0.001). Post hoc Wilcoxon tests revealed the gait quality model outperformed both supervised ( p < 0.01) and physical activity models ( p < 0.01), with no significant difference between the latter two. Note that these results are based on the application of both stages of the ElderNet pipeline: gait detection, followed by the estimation of wrist-derived gait features.

Article Snippet: Dataset 2: Rush Memory and Aging Project (MAP), which includes 819 older adults (mean age 83.4 ± 7.3 years) who wore a wrist accelerometer (Axivity AX3, 50 Hz sampling rate or GENEActiv, 40 Hz sampling rate) for up to 10 consecutive days.

Techniques: Standard Deviation, Biomarker Discovery, Activity Assay, Derivative Assay

Journal: Translational Psychiatry

Article Title: The interplay between genomic copy number variants, sleep, and cognition in the general population

doi: 10.1038/s41398-025-03579-x

Figure Lengend Snippet: Fitted curves of the Quadratic model associating cognition and sleep duration (dark line). The light line represents the GAM model. The dotted vertical line indicates the vertex of the parabola. a Relationship between general cognition aggregated across visits and sleep duration (self-reported on the left and accelerometer on the right). b Relationship between executive functioning measured by the trail-making task administered in person and online and self-reported sleep duration (self-reported on the left and accelerometer on the right). c Relationship between executive functioning measured by the tower rearranging task administered in person and self-reported sleep duration (Note: this relationship was not significant with accelerometer-derived sleep duration). Blue = General cognitive ability, Green = Trail making task, Purple = Tower task. X-axis: durations are in hours (first line) and z-scored duration (second line). Y-axis: z-scored cognitive ability.

Article Snippet: A subset of participants were invited to wear a triaxial accelerometer device (Axivity AX3) between 3 to 10 years after the initial study assessment.

Techniques: Derivative Assay

Journal: Translational Psychiatry

Article Title: The interplay between genomic copy number variants, sleep, and cognition in the general population

doi: 10.1038/s41398-025-03579-x

Figure Lengend Snippet: Forest plots depicting the associations between specific recurrent CNV (red = deletion; blue = duplications) and 7 cognitive and sleep measures. Estimates are computed only for CNVs with more than 10 carriers for a given measure. As a result, some phenotypes (accelerometer-derived) have fewer estimates depicted in the figure. Only CNVs with a significant association (FDR < 0.05) with at least one trait are shown. The Y-axis represents the cognitive and sleep traits. The X-axis represents the estimate of the linear models associating CNVs and traits. Abbreviation: TMT trail making task.

Article Snippet: A subset of participants were invited to wear a triaxial accelerometer device (Axivity AX3) between 3 to 10 years after the initial study assessment.

Techniques: Derivative Assay