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Smartphone Keystroke-based Cognitive Impairment Diagnostic Methodology
Jaehun Uhm, Hong Yoon Kim, Byeongjin Choe, Hardik Agrawal, Seoyoung Yoon, Ji Hwan Yun. Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference, 2025-07
Topic: Brain imaging, connectivity and assessment
With the global population rapidly aging, dementia has emerged as a major public health concern. Significant efforts are being made to address the health and other problems associated with dementia. Although several advances have been made in the diagnosis and treatment of dementia, many challenges remain unresolved. Existing dementia diagnostic methods are often not performed in a timely manner due to poor accessibility, leading to delays in initiation of treatment. In this study, we propose a smartphone keystroke-based diagnostic method as a solution to overcome the limitations associated with the early diagnosis and treatment of dementia. As compared to other existing methods, the proposed diagnostic method is easier to develop and maintain, promoting commercialization and widespread use. The diagnostic method has been designed to extract language-agnostic keystroke data features from smartphone keyboard input logs. Rather than simply extracting features assessing motor skills from keystroke data or features demonstrating language usage patterns from text, this study focused on features that can assess cognitive abilities without using linguistic characteristics. Clinical trials were conducted in patients with mild cognitive impairment and early Alzheimer's dementia were conducted, and a series of experiments and validation tests were performed using the trial data. The results demonstrated that the proposed smartphone keystroke-based diagnostic method is effective in diagnosing cognitive impairment. The proposed method does not require the use of any special equipment except smartphones, which facilitates low-cost commercialization. This study presents a diagnostic method that addresses the problem of people who avoid tests for the diagnosis of dementia due to economic and psychological burdens.Clinical RelevanceThis study provides an approach for early detection of dementia using ordinary smartphone keystroke logs. The proposed method has the potential to improve the quality of life of patients with dementia. Following large-scale clinical research and the integration of more digital biomarkers, the methodology proposed in this study can potentially facilitate the development of an early diagnostic platform for dementia.
Key findings
- Significant efforts are being made to address the health and other problems associated with dementia.
- In this study, we propose a smartphone keystroke-based diagnostic method as a solution to overcome the limitations associated with the early diagnosis and treatment of dementia.
- As compared to other existing methods, the proposed diagnostic method is easier to develop and maintain, promoting commercialization and widespread use.
- The results demonstrated that the proposed smartphone keystroke-based diagnostic method is effective in diagnosing cognitive impairment.
Study details
- Evidence strengthLow
How this study scored 43/100
Published in a peer-reviewed journal. Scored zero for study design, sample size, effect reported, studied in people and randomised / blinded because the record does not state it. We have no data on journal's citation record, 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, multi-centre collaboration and free to read, so those were left out: it earned 24 of the 56 points we could judge it on, which is 43 out of 100.
| Component | Points | Why |
|---|---|---|
| Journal tier | 7 / 10 | Tier 3 — peer-reviewed journal (Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference) |
| Journal's citation record | — / 4 | No journal record from OpenAlex — left out of this score |
| 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 | 10 / 10 | Peer-reviewed. Published as an article in a named peer-reviewed journal. |
| How recent | 4 / 5 | 2025 — within 3 year(s) of the newest study here |
| Sample size | 0 / 4 | Participant count not stated — scores zero (not stated in the record — scored 0) |
| Effect reported | 0 / 3 | No effect size reported — scores zero (not stated in the record — scored 0) |
| Studied in people | 0 / 3 | Not stated whether this was studied in people — scores zero (not stated in the record — scored 0) |
| 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 | 2 / 2 | Indexed in PubMed (PMID 41337282) |
| Free to read | — / 2 | Access not recorded — left out of this score |
| Points | 24 / 56 | Scored on 10 of 20 parts. We have no data for the rest, so they are left out: 24 of the 56 points we could judge it on is 43 out of 100. |
| Total | 43 / 100 | — |
What each of these 20 components measures, and what this score is not →
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APA 7th
Uhm, J., Kim, H. Y., Choe, B., Agrawal, H., Yoon, S., & Yun, J. H. (2025). Smartphone Keystroke-based Cognitive Impairment Diagnostic Methodology. Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference. https://doi.org/10.1109/embc58623.2025.11253467
Vancouver
Uhm J, Kim HY, Choe B, Agrawal H, Yoon S, Yun JH. Smartphone Keystroke-based Cognitive Impairment Diagnostic Methodology. Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference. 2025. doi:10.1109/embc58623.2025.11253467. PMID: 41337282.
BibTeX
@article{uhm2025-41337282,
author = {Uhm, Jaehun and Kim, Hong Yoon and Choe, Byeongjin and Agrawal, Hardik and Yoon, Seoyoung and Yun, Ji Hwan},
title = {{Smartphone Keystroke-based Cognitive Impairment Diagnostic Methodology}},
journal = {Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference},
year = {2025},
doi = {10.1109/embc58623.2025.11253467},
pmid = {41337282},
url = {https://doi.org/10.1109/embc58623.2025.11253467}
}