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Advances on Automatic Speech Analysis for Early Detection of Alzheimer Disease: A Non-linear Multi-task Approach
Lopez-de-Ipina K, Lopez-de-Ipina K, Martinez-de-Lizarduy U, Calvo PM, Mekyska J, Beitia B, Barroso N, Estanga A et al.. Current Alzheimer research, 2018-01-01
Topic: Amyloid, tau and blood-test diagnosis
Objective Nowadays proper detection of cognitive impairment has become a challenge for the scientific community. Alzheimer's Disease (AD), the most common cause of dementia, has a high prevalence that is increasing at a fast pace towards epidemic level. In the not-so-distant future this fact could have a dramatic social and economic impact. In this scenario, an early and accurate diagnosis of AD could help to decrease its effects on patients, relatives and society. Over the last decades there have been useful advances not only in classic assessment techniques, but also in novel non-invasive screening methodologies. Methods Among these methods, automatic analysis of speech -one of the first damaged skills in AD patients- is a natural and useful low cost tool for diagnosis. Results In this paper a non-linear multi-task approach based on automatic speech analysis is presented. Three tasks with different language complexity levels are analyzed, and promising results that encourage a deeper assessment are obtained. Automatic classification was carried out by using classic Multilayer Perceptron (MLP) and Deep Learning by means of Convolutional Neural Networks (CNN) (biologically- inspired variants of MLPs) over the tasks with classic linear features, perceptual features, Castiglioni fractal dimension and Multiscale Permutation Entropy. Conclusion Finally, the most relevant features are selected by means of the non-parametric Mann- Whitney U-test.
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APA 7th
Lopez-de-Ipina, K., Martinez-de-Lizarduy, U., Calvo, P. M., Mekyska, J., Beitia, B., Barroso, N., et al. (2018). Advances on Automatic Speech Analysis for Early Detection of Alzheimer Disease: A Non-linear Multi-task Approach. Current Alzheimer research. https://doi.org/10.2174/1567205014666171120143800
Vancouver
Lopez-de-Ipina K, Martinez-de-Lizarduy U, Calvo PM, Mekyska J, Beitia B, Barroso N, et al. Advances on Automatic Speech Analysis for Early Detection of Alzheimer Disease: A Non-linear Multi-task Approach. Current Alzheimer research. 2018. doi:10.2174/1567205014666171120143800. PMID: 29165084.
BibTeX
@article{lopezdeipina2018-29165084,
author = {Lopez-de-Ipina, K. and Martinez-de-Lizarduy, U. and Calvo, P. M. and Mekyska, J. and Beitia, B. and Barroso, N. and Estanga, A. and others},
title = {{Advances on Automatic Speech Analysis for Early Detection of Alzheimer Disease: A Non-linear Multi-task Approach}},
journal = {Current Alzheimer research},
year = {2018},
doi = {10.2174/1567205014666171120143800},
pmid = {29165084},
url = {https://doi.org/10.2174/1567205014666171120143800}
}
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Key findings
- Results In this paper a non-linear multi-task approach based on automatic speech analysis is presented.
- Three tasks with different language complexity levels are analyzed, and promising results that encourage a deeper assessment are obtained.
Why it matters
This paper presents a non-linear multi-task approach based on automatic speech analysis for early detection of Alzheimer's disease. It obtained promising results encouraging deeper assessment, but it is a diagnostic method, not a treatment or cure.
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Study details
- Evidence strengthLow
How this study scored 37/100
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.
| Component | Points | Why |
|---|---|---|
| Journal tier | 7 / 10 | Tier 3 — peer-reviewed journal (Current Alzheimer research) |
| Journal's citation record | 1 / 4 | Current Alzheimer Research: journal h-index 119 (OpenAlex, 2026-10-29) |
| 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 | 2 / 5 | 2018 — within 10 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 | 4 / 7 | Cited 66 times (OpenAlex, 2026-10-10) |
| Citations per year | 2 / 5 | 6.6 citations a year over 10 year(s) since 2018 |
| Impact for its field and year | 3 / 6 | Cited 3.8× the average for papers of its field and year (OpenAlex FWCI) |
| Cited by studies here | 1 / 6 | Cited by 1 other studies in this library |
| Still being cited | 1 / 4 | Cited 14 times in 2024–2026 (2026 still in progress; OpenAlex) |
| Senior author's track record | 2 / 4 | Last-listed author Mirian Ecay‐Torres: h-index 21 (OpenAlex, whole career) |
| Institution's track record | 0 / 3 | University of the Basque Country: institution h-index 510 (OpenAlex) |
| Multi-centre collaboration | 1 / 3 | OpenAlex lists 3 institution(s) in 2 countries |
| Indexed in PubMed | 2 / 2 | Indexed in PubMed (PMID 29165084) |
| Free to read | 0 / 2 | Behind a paywall — scores zero |
| Total | 37 / 100 | — |
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