UMIN-ICDS Clinical Trial
| Unique ID issued by UMIN | UMIN000062629 |
|---|---|
| Receipt number | R000071478 |
| Scientific Title | Development of a Multitask Machine Learning Framework for Detecting Psychological Frailty in Older Adults Using Acoustic Speech Features |
| Date of disclosure of the study information | 2026/09/01 |
| Last modified on | 2026/08/22 09:24:08 |
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Basic information
Public title
Development of a Multitask Machine Learning Framework for Detecting Psychological Frailty in Older Adults Using Acoustic Speech Features
Acronym
Development of a Multitask Machine Learning Framework for Detecting Psychological Frailty in Older Adults Using Acoustic Speech Features
Scientific Title
Development of a Multitask Machine Learning Framework for Detecting Psychological Frailty in Older Adults Using Acoustic Speech Features
Scientific Title:Acronym
Development of a Multitask Machine Learning Framework for Detecting Psychological Frailty in Older Adults Using Acoustic Speech Features
Region
| Japan |
Condition
Condition
Dementia, Depressive symptoms
Classification by specialty
| Geriatrics | Psychiatry |
Classification by malignancy
Others
Genomic information
NO
Objectives
Narrative objectives1
To establish a foundation for speech analysis capable of simultaneously estimating cognitive function (cognitively normal, mild cognitive impairment [MCI], and dementia) and depressive symptoms from older adults' conversational speech, and to construct a multitask machine learning algorithm to achieve this from a single voice sample.
Basic objectives2
Others
Basic objectives -Others
Development and validation of an algorithm for estimating cognitive function and depressive symptoms using speech analysis
Trial characteristics_1
Trial characteristics_2
Developmental phase
Assessment
Primary outcomes
Accuracy of cognitive function and depressive symptom estimates based on acoustic features using the developed machine learning model.
Key secondary outcomes
Associations between acoustic features and cognitive function, as well as symptoms and clinical states including depressive symptoms, apathy, and those assessed using the Neuropsychiatric Inventory (NPI).
Base
Study type
Observational
Study design
Basic design
Randomization
Randomization unit
Blinding
Control
Stratification
Dynamic allocation
Institution consideration
Blocking
Concealment
Intervention
No. of arms
Purpose of intervention
Type of intervention
Interventions/Control_1
Interventions/Control_2
Interventions/Control_3
Interventions/Control_4
Interventions/Control_5
Interventions/Control_6
Interventions/Control_7
Interventions/Control_8
Interventions/Control_9
Interventions/Control_10
Eligibility
Age-lower limit
| 65 | years-old | <= |
Age-upper limit
| Not applicable |
Gender
Male and Female
Key inclusion criteria
Individuals aged 65 or older who provide written informed consent to participate in this study (or whose legally acceptable representative provides written consent).
Key exclusion criteria
Individuals with complications or impairments that affect speech measurement (e.g., difficulty speaking due to laryngectomy, etc.), and individuals deemed unsuitable for participation in this study by the principal or sub-investigators.
Target sample size
150
Research contact person
Name of lead principal investigator
| 1st name | Taishiro |
| Middle name | |
| Last name | Kisimoto |
Organization
Keio University School of Medicine
Division name
Center for Integrated Medical Research
Zip code
106-0041
Address
7F Azabudai Hills Mori JP Tower, 1-3-1 Azabudai, Minato-ku, Tokyo, Japan
TEL
03-5363-3685
tkishimoto@keio.jp
Public contact
Name of contact person
| 1st name | Toshiro |
| Middle name | |
| Last name | Horigome |
Organization
Keio university school of medicine
Division name
Center for Promotion of Interdisciplinary Research in Medicine and life Science
Zip code
106-0041
Address
Mori JP Tower F7, 1-3-1, Azabudai, Minato-ku, Tokyo
TEL
03-5363-3219
Homepage URL
toshirou.ho@keio.jp
Sponsor or person
Institute
Keio University
Institute
Department
Personal name
Funding Source
Organization
Eisai Co., Ltd.
Organization
Division
Category of Funding Organization
Profit organization
Nationality of Funding Organization
Other related organizations
Co-sponsor
Shonan Keiiku Hospital
Name of secondary funder(s)
IRB Contact (For public release)
Organization
Keio University School of Medicine Ethics Committee
Address
35 Shinanomachi, Shinjuku-ku, Tokyo, Japan
Tel
0353633503
med-rinri-jimu@adst.keio.ac.jp
Secondary IDs
Secondary IDs
NO
Study ID_1
Org. issuing International ID_1
Study ID_2
Org. issuing International ID_2
IND to MHLW
Institutions
Institutions
湘南慶育病院（神奈川県）
Other administrative information
Date of disclosure of the study information
| 2026 | Year | 09 | Month | 01 | Day |
Related information
URL releasing protocol
Publication of results
Unpublished
Result
URL related to results and publications
Number of participants that the trial has enrolled
Results
Results date posted
Results Delayed
Results Delay Reason
Date of the first journal publication of results
Baseline Characteristics
Participant flow
Adverse events
Outcome measures
Plan to share IPD
IPD sharing Plan description
Progress
Recruitment status
Preinitiation
Date of protocol fixation
| 2025 | Year | 04 | Month | 17 | Day |
Date of IRB
| 2026 | Year | 06 | Month | 29 | Day |
Anticipated trial start date
| 2026 | Year | 09 | Month | 01 | Day |
Last follow-up date
| 2032 | Year | 03 | Month | 31 | Day |
Date of closure to data entry
Date trial data considered complete
Date analysis concluded
Other
Other related information
This is an observational study aimed at developing a multi-task machine learning algorithm to detect psychological frailty in older adults using voice data and acoustic features.
Management information
Registered date
| 2026 | Year | 08 | Month | 20 | Day |
Last modified on
| 2026 | Year | 08 | Month | 22 | Day |
Link to view the page
Value
https://center6.umin.ac.jp/cgi-open-bin/ctr_e/ctr_view.cgi?recptno=R000071478
