UMIN-ICDS Clinical Trial
| Unique ID issued by UMIN | UMIN000059576 |
|---|---|
| Receipt number | R000068134 |
| Scientific Title | Development and validation of a restless behavior detection model using Inertial Measurement Unit sensors and healthy person data |
| Date of disclosure of the study information | 2025/12/01 |
| Last modified on | 2025/10/29 10:52:38 |
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Basic information
Public title
Development and validation of an artificial intelligence model to detect restless movements using motion sensors
Acronym
AI motion sensor study for detecting restlessness
Scientific Title
Development and validation of a restless behavior detection model using Inertial Measurement Unit sensors and healthy person data
Scientific Title:Acronym
Inertial Measurement Unit-based Restless behavior Estimation and Sensing Technology Study: IMU-REST STUDY
Region
| Japan |
Condition
Condition
None
Classification by specialty
| Not applicable |
Classification by malignancy
Others
Genomic information
NO
Objectives
Narrative objectives1
The objective is to develop (train) a convolutional neural network (CNN) model that detects agitated behavior from motion data recorded by an IMU sensor using healthy subject data, and to evaluate its initial feasibility for future clinical application in intensive care units.
Basic objectives2
Efficacy
Basic objectives -Others
Trial characteristics_1
Trial characteristics_2
Developmental phase
Assessment
Primary outcomes
F1 Score for Target Location Estimation Using Convolutional Neural Networks (CNN)
Key secondary outcomes
Sensitivity
Specificity
Accuracy
AUC
etc.
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
| 18 | years-old | <= |
Age-upper limit
| 65 | years-old | >= |
Gender
Male and Female
Key inclusion criteria
healthy person
Key exclusion criteria
Individuals under the age of 18
Individuals with underlying musculoskeletal conditions or a history of collagen diseases
Individuals with a pacemaker implant
Individuals who did not consent to the study
Target sample size
45
Research contact person
Name of lead principal investigator
| 1st name | Ryuto |
| Middle name | |
| Last name | Yokoyama |
Organization
Yamagata University Faculty of Medicine
Division name
Department of Emergency and Citical Care Medicine
Zip code
990-9585
Address
2-2-2 Iida Nishi, Yamagata City, Yamagata Prefecture
TEL
0236331122
ryusi0311@gmail.com
Public contact
Name of contact person
| 1st name | RYUTO |
| Middle name | |
| Last name | YOKOYAMA |
Organization
Yamagata University Faculty of Medicine
Division name
Department of Emergency and Critical Care Medicine
Zip code
9902321
Address
2-2-2 Iida Nishi, Yamagata City, Yamagata Prefecture
TEL
08055544587
Homepage URL
ryusi0311@gmail.com
Sponsor or person
Institute
Yamagata Univercity
Institute
Department
Personal name
RYUTO YOKOYAMA
Funding Source
Organization
Yamagata Univercity
Organization
Division
Category of Funding Organization
Other
Nationality of Funding Organization
Other related organizations
Co-sponsor
Name of secondary funder(s)
IRB Contact (For public release)
Organization
Ethics Review Committee, Faculty of Medicine, Yamagata University
Address
2-2-2 Iida Nishi, Yamagata City, Yamagata Prefecture
Tel
0236331122
ryusi0311@gmail.com
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
Other administrative information
Date of disclosure of the study information
| 2025 | Year | 12 | 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 | 10 | Month | 28 | Day |
Date of IRB
Anticipated trial start date
| 2025 | Year | 12 | Month | 01 | Day |
Last follow-up date
| 2028 | Year | 01 | Month | 01 | Day |
Date of closure to data entry
Date trial data considered complete
Date analysis concluded
Other
Other related information
Recruitment of Participants and Explanation/Consent
This study will involve healthy individuals who have received a thorough explanation of the study's purpose and content and have provided written consent.
Sensor Attachment
IMU sensors will be safely attached to the participant's limbs and waist.
Performance of Movement Tasks
Under the researcher's guidance, subjects will perform multiple physical movements (e.g., elbow flexion/extension, sitting, trunk flexion/extension) that we consider "restless movements" within safe limits. Research staff will be present and monitor during the movements to avoid risks such as falls.
Data Acquisition and Storage
Data obtained from the IMU sensors will be collected and securely stored.
Data Analysis and Machine Learning Model Development
The acquired data will be organized and preprocessed to extract features for each movement. This data will be used to train a CNN model and develop an automatic detection model for agitated behavior.
Model Validation
The performance of the trained model will be evaluated using validation and test data. Validity will be assessed based on metrics such as accuracy, recall, and F1 score.
Management information
Registered date
| 2025 | Year | 10 | Month | 29 | Day |
Last modified on
| 2025 | Year | 10 | Month | 29 | Day |
Link to view the page
Value
https://center6.umin.ac.jp/cgi-open-bin/icdr_e/ctr_view.cgi?recptno=R000068134
