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Harnessing Speech-Derived Digital Biomarkers to Detect and Quantify Cognitive Decline Severity in Older Adults
Cay G, Pfeifer VA, Lee M, Rouzi MD, Nunes AS, El-Refaei N, Momin AS, Atique MMU et al.. Gerontology, 2024-01-12
Topic: Risk, prevention and care in population studies
Introduction Current cognitive assessments suffer from floor/ceiling and practice effects, poor psychometric performance in mild cases, and repeated assessment effects. This study explores the use of digital speech analysis as an alternative tool for determining cognitive impairment. The study specifically focuses on identifying the digital speech biomarkers associated with cognitive impairment and its severity. Methods We recruited older adults with varying cognitive health. Their speech data, recorded via a wearable microphone during the reading aloud of a standard passage, were processed to derive digital biomarkers such as timing, pitch, and loudness. Cohen's d effect size highlighted group differences, and correlations were drawn to the Montreal Cognitive Assessment (MoCA). A stepwise approach using a Random Forest model was implemented to distinguish cognitive states using speech data and predict MoCA scores based on highly correlated features. Results The study comprised 59 participants, with 36 demonstrating cognitive impairment and 23 serving as cognitively intact controls. Among all assessed parameters, similarity, as determined by Dynamic Time Warping (DTW), exhibited the most substantial positive correlation (rho = 0.529, p < 0.001), while timing parameters, specifically the ratio of extra words, revealed the strongest negative correlation (rho = -0.441, p < 0.001) with MoCA scores. Optimal discriminative performance was achieved with a combination of four speech parameters: total pause time, speech-to-pause ratio, similarity via DTW, and intelligibility via DTW. Precision and balanced accuracy scores were found to be 88.1 ± 1.2% and 76.3 ± 1.3%, respectively. Discussion Our research proposes that reading-derived speech data facilitates the differentiation between cognitively impaired individuals and cognitively intact, age-matched older adults. Specifically, parameters based on timing and similarity within speech data provide an effective gauge of cognitive impairment severity. These results suggest speech analysis as a viable digital biomarker for early detection and monitoring of cognitive impairment, offering novel approaches in dementia care.
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APA 7th
Cay, G., Pfeifer, V. A., Lee, M., Rouzi, M. D., Nunes, A. S., El-Refaei, N., et al. (2024). Harnessing Speech-Derived Digital Biomarkers to Detect and Quantify Cognitive Decline Severity in Older Adults. Gerontology. https://doi.org/10.1159/000536250
Vancouver
Cay G, Pfeifer VA, Lee M, Rouzi MD, Nunes AS, El-Refaei N, et al. Harnessing Speech-Derived Digital Biomarkers to Detect and Quantify Cognitive Decline Severity in Older Adults. Gerontology. 2024. doi:10.1159/000536250. PMID: 38219728.
BibTeX
@article{cay2024-38219728,
author = {Cay, G. and Pfeifer, V. A. and Lee, M. and Rouzi, M. D. and Nunes, A. S. and El-Refaei, N. and Momin, A. S. and Atique, M. M. U. and others},
title = {{Harnessing Speech-Derived Digital Biomarkers to Detect and Quantify Cognitive Decline Severity in Older Adults}},
journal = {Gerontology},
year = {2024},
doi = {10.1159/000536250},
pmid = {38219728},
url = {https://doi.org/10.1159/000536250}
}
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Key findings
- The study specifically focuses on identifying the digital speech biomarkers associated with cognitive impairment and its severity.
- Results The study comprised 59 participants, with 36 demonstrating cognitive impairment and 23 serving as cognitively intact controls.
- Among all assessed parameters, similarity, as determined by Dynamic Time Warping (DTW), exhibited the most substantial positive correlation (rho = 0.529, p < 0.001), while timing parameters, specifically the ratio of extra words, revealed the strongest negative correlation (rho = -0.441, p < 0.001) with MoCA scores.
- These results suggest speech analysis as a viable digital biomarker for early detection and monitoring of cognitive impairment, offering novel approaches in dementia care.
Study details
- Participants59
- Effect size1.2%; 1.3%
- Evidence strengthLow
How this study scored 52/100
Published in a peer-reviewed journal. Scored zero for study design 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 and multi-centre collaboration, so those were left out: it earned 30 of the 58 points we could judge it on, which is 52 out of 100.
| Component | Points | Why |
|---|---|---|
| Journal tier | 7 / 10 | Tier 3 — peer-reviewed journal (Gerontology) |
| 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 | 2024 — within 3 year(s) of the newest study here |
| Sample size | 1 / 4 | 59 participants |
| Effect reported | 2 / 3 | Effect reported as a number, without an interval or test |
| 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 | 2 / 2 | Indexed in PubMed (PMID 38219728) |
| Free to read | 0 / 2 | Behind a paywall — scores zero |
| Points | 30 / 58 | Scored on 11 of 20 parts. We have no data for the rest, so they are left out: 30 of the 58 points we could judge it on is 52 out of 100. |
| Total | 52 / 100 | — |
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