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Stable and Interpretable Cognitive Status Screening Using Longitudinal Wearable Data
Kim H, Cho T, Choi AJ, Lee S.. Research Square, 2026-10-20
Topic: Brain imaging, connectivity and assessment
Wearable devices repeatedly measure activity, sleep, and nocturnal physiology, but their value for three-class cognitive screening remains uncertain. We developed an interpretable hierarchical framework to distinguish cognitively normal (CN), mild cognitive impairment (MCI), and dementia (DEM) without the Mini-Mental State Examination or device-generated composite scores. Data from 174 adults aged 55 years or older were represented by seven-day windows encoding level, variability, trend, transitions, bouts, and complexity. Stage 1 separated DEM from non-DEM using the top-3 mean of window probabilities; Stage 2 separated CN from MCI using participant-median slope-and-change features. Participant-level cross-validation and repeated 3- to 6-fold sensitivity analyses preceded evaluation on an internal holdout of 38 participants. Accuracy was 0.711, balanced accuracy was 0.738, and macro F1 was 0.692; recall was 0.682, 0.700, and 0.833 for CN, MCI, and DEM, respectively. TreeSHAP and correlation grouping yielded four preliminary DEM patterns---activity complexity, device-state organization, rest, and light-sleep structure---and three exploratory MCI domains spanning activity persistence, sleep-wake timing, and nocturnal physiology. These findings support risk screening and hypothesis generation rather than diagnosis or validated biomarker claims; external multicenter validation is needed.
Key findings
- These findings support risk screening and hypothesis generation rather than diagnosis or validated biomarker claims; external multicenter validation is needed.
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Study details
- Participants174
- Evidence strengthLow
How this study scored 16/100
Preprint — not yet peer-reviewed. It scored 29 on the same rubric, but non-peer-reviewed sources are capped at 16, so it shows as 16. Scored zero for study design, effect reported and randomised / blinded because the record does not state it. We have no data on times cited, citations per year, impact for its field and year, cited by studies here, still being cited, senior author's track record, institution's track record and multi-centre collaboration, so those were left out: it earned 18 of the 62 points we could judge it on, which is 29 out of 100.
| Component | Points | Why |
|---|---|---|
| Journal tier | 2 / 10 | Tier 4 — not a peer-reviewed journal (Research Square) |
| Journal's citation record | 0 / 4 | Not a journal article, so the journal's record does not count |
| Study design | 0 / 12 | No study design recorded — scores zero, not guessed (not stated in the record — scored 0) |
| Strength of evidence | 1 / 5 | Rated “low” in our summary |
| Peer-review validation | 4 / 10 | Preprint — not yet peer-reviewed. Hosted on a preprint server. |
| How recent | 5 / 5 | 2026 — within 1 year(s) of the newest study here |
| Sample size | 2 / 4 | 174 participants |
| Effect reported | 0 / 3 | No effect size reported — scores zero (not stated in the record — scored 0) |
| Studied in people | 3 / 3 | Studied in people (participant count stated) |
| Randomised / blinded | 0 / 2 | No randomisation or blinding stated — scores zero (not stated in the record — scored 0) |
| Times cited | — / 7 | No citation count (not found in OpenAlex) — left out of this score |
| Citations per year | — / 5 | No citation count or no year — left out of this score |
| Impact for its field and year | — / 6 | No field-weighted citation impact (OpenAlex has none yet) — left out of this score |
| Cited by studies here | — / 6 | Not yet checked against this library's citation graph — left out of this score |
| Still being cited | — / 4 | No yearly citation counts — left out of this score |
| Senior author's track record | — / 4 | Senior author's record not available — left out of this score |
| Institution's track record | — / 3 | No institution listed in OpenAlex — left out of this score |
| Multi-centre collaboration | — / 3 | Institutions not listed — left out of this score |
| Indexed in PubMed | 1 / 2 | Not in PubMed, but has a DOI |
| Free to read | 0 / 2 | Behind a paywall — scores zero |
| Points | 18 / 62 | Scored on 12 of 20 parts. We have no data for the rest, so they are left out: 18 of the 62 points we could judge it on is 29 out of 100. |
| Total | 29 / 100 | Capped to 16 because this is not a peer-reviewed article. |
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APA 7th
Kim, H., Cho, T., Choi, A. J., & Lee, S. (2026). Stable and Interpretable Cognitive Status Screening Using Longitudinal Wearable Data. Research Square. https://doi.org/10.21203/rs.3.rs-11111108/v1
Vancouver
Kim H, Cho T, Choi AJ, Lee S. Stable and Interpretable Cognitive Status Screening Using Longitudinal Wearable Data. Research Square. 2026. doi:10.21203/rs.3.rs-11111108/v1.
BibTeX
@article{kim2026-208656a7,
author = {Kim, H. and Cho, T. and Choi, A. J. and Lee, S.},
title = {{Stable and Interpretable Cognitive Status Screening Using Longitudinal Wearable Data}},
journal = {Research Square},
year = {2026},
doi = {10.21203/rs.3.rs-11111108/v1},
url = {https://doi.org/10.21203/rs.3.rs-11111108/v1}
}