Motor DisordersNCT06521918
Combined Artificial Intelligence and Mobile Application for Remote Infant Motor Screening: Development and Validation
An observational study of Motor Disorders, run by National Taiwan University Hospital at 1 site in Taiwan.
Trial summary
The purpose of this study is therefore five-fold: (1) designation of an APP "Baby Go" version 3.0 to include the assessment, follow-up, and education functions for parental use at home, (2) development and validation of the AI algorithm for infant motor assessment based on home videos obtained from term and preterm… Read more about this study
- Who is it for?
- Ages 2 to 18 monthsHealthy volunteers can take part
- Conditions the study is for
- Motor Disorders
- How many people
- 242 participants
- Where
- 1 siteTaiwan
- Study dates
- 17 Oct 2024to 31 Jul 2027
- Phase
- Observational
- Are there results?
- Not yet: the study is under way
Key requirements
Who can take part, as listed by the sponsor. Only the study team can confirm whether you are eligible, so take this list to your doctor.
- Ages 2 to 18 months
- All sexes
- Healthy volunteers accepted
- Child
Study population: This study will recruit preterm and term infants from National Taiwan University Children's Hospital (NTUCH), Taipei, Taiwan, with the former recruited from the neonatal follow-up clinic and the latter from the well-baby follow-up clinic. Two pediatric physiotherapists providing early intervention to the participating infants will be invited to complete a feedback questionnaire about the APP "Baby Go."
The inclusion criterion is:
Preterm infants: gestational age < 37 weeks, birth body weight < 2,500 grams, and corrected age of 2-18 months.
Term infants: gestational age 37-42 weeks, birth body weight >2,500 grams, and age of 2-18 months.
Clinicians: who provide early intervention to the participating infants in this study.
The exclusion criterion is:
Infants: parents can not read Chinese. Clinicians: can not read Chinese
Trial locations and contacts
1 site in 1 country. Contact the study team or a site near you to ask about taking part.
Taiwan1 site, 1 recruiting
- Recruiting
National Taiwan University
Taipei, Taiwan, 100
Suh-Fang Jeng, Professor, 886-2-33668132, jeng@ntu.edu.tw
About this study
The purpose of this study is therefore five-fold: (1) designation of an APP "Baby Go" version 3.0 to include the assessment, follow-up, and education functions for parental use at home, (2) development and validation of the AI algorithm for infant motor assessment based on home videos obtained from term and preterm infants, (3) comparison of parental perception and report with AI-driven assessment results, (4) examination of the predictive validity of the AI algorithm for infant motor assessment on subsequent outcome, and (5) investigation of the usability of the APP "Baby Go" version 3.0 in parents and clinicians.
Read the detailed description
Background and Purpose: Early identification and intervention of infants who are at risk of developmental disorders (such as preterm infants) is an important global health policy and action. The number of children with developmental disorders referred for early intervention in Taiwan has increased in the last ten years. Yet, they are more likely diagnosed and referred for intervention at an age beyond two years. Existing developmental diagnostic tests are frequently accessible at hospitals, whereas screening tests are often based on parental reports that are influenced by parents' knowledge and interpretation. Although the emerging artificial intelligence (AI) technology and deep learning have enabled the tracking and recognition of human movements in standardized laboratory settings, whether its incorporation with mobile application (APP) is feasible and accurate for infant motor assessment at home has rarely been investigated. Therefore, this study continues our previous endeavors that applied AI and machine learning to classify several infant movements at standardized laboratory. This study aims to combine the AI algorithm and machine learning with an APP for infant motor assessment in home setup. The specific purposes are (1) designation of an APP "Baby Go" version 3.0 to include the assessment, follow-up, and education functions for parental use at home, (2) development and validation of the AI algorithm for infant motor assessment based on home videos obtained from term and preterm infants, (3) comparison of parental perception and report with AI-driven assessment results, (4) examination of the predictive validity of the AI algorithm for infant motor assessment on subsequent outcome, and (5) investigation of the usability of the APP "Baby Go" version 3.0 in parents and clinicians. Method: This study will recruit 100 preterm infants, 20 term infants aged 2 to 18 months (corrected for prematurity), 120 infants' parents, and 2 clinicians at National Taiwan University Children's Hospital. The APP "Baby Go" version 3.0 will contain the features of age-based motor assessment with 2 to 5 movements at each age, follow-up, and education module. The parents will be asked to video record their baby's movements in prone, supine, sitting, and standing at home biweekly and to simultaneously upload the video files via the APP during the age period of 2 to 18 months, followed by recording their infant's age of walking attainment. Trained physiotherapists will annotate all video files and the results will serve as the gold standards for validation of the data of the AI model and parental perception. The video data will be randomly split into the training and testing set with an 8:2 ratio for model development and validation. The AI model of infant motor assessment will be examined for its predictive validity on age of walking attainment. The parents and clinicians will fill out the APP usability survey. Innovation and Significance: This study is an incremental AI model advancement in tracking and recognizing infant movements from a laboratory-based classification system to a home-based assessment system. The automatic AI-driven infant motor assessment via the APP "Baby Go" will provide parents and healthcare providers in Taiwan with innovative and feasible developmental resources in remote communities. The results are insightful to assist pediatricians and physiotherapists in planning diagnostic assessment and early intervention for infants at risk of neuromotor disorders.
- Conditions
- Motor Disorders
- Keywords
- AI, infant motor assessment, APP, validation
- Medical subject headings
- Motor Disorders, Alzheimer Disease
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
| Study group | Role | What they receive |
|---|---|---|
| Term infants | The inclusion criterion is: gestational age 37-42 weeks, birth body weight >2,500 grams, and age at 2-18 months. The exclusion criterion is: parents can not read Chinese. | |
| Preterm infants | The inclusion criterion is: gestational age < 37 weeks, birth body weight < 2,500 grams, and corrected age of 2-18 months. The exclusion criterion is: parents can not read Chinese. | |
| Clinicians | The inclusion criterion is: who provide early intervention to the participating infants in this study. The exclusion criterion is: can not read Chinese |
What is being measured
The primary outcome is the main question the study is designed to answer.
Alberta Infant Motor Scale (AIMS)
motor function in supine, prone, sitting and standing position
Measured: 3 - 18 months of age
Age of walking attainment
Age of attaining independent walking for at least five steps
Measured: 9 - 18 months of age
User experience from parents
Parents' perspectives on the use of the APP "Baby Go" were collected using Google Forms (For parents: https://forms.gle/BPL7CWopaB7qk3388). The questionnaire for parents was customized for the APP "Baby Go" in this study and adapted from a survey used in the "Baby Moves" APP previously described by Kwong et al. The questionnaire for the parents consisted of three sections: (1) frequency of the APP use, (2) benefits of the APP use, and (3) user's experience. Questionnaires contained three types of measures: (1) multiple choice, (2) five-point Likert scale, and (3) open-ended questions.
Measured: When the infant approached 6 months, 12 months, and 18 months
User experience from clinicians
Clinicians' perspectives on the use of the APP "Baby Go" were collected using Google Forms (for clinicians: https://forms.gle/3L7nGKe2ZTT39t7n6). The questionnaire for clinicians is customized for the APP "Baby Go" in this study and adapted from a healthcare professional interview previously described by AlMahadin et al. 44 The questionnaire for clinicians contains two sections: (1) perspectives of the APP use and (2) recommendations of APP use. Each questionnaire contains three types of measures: (1) multiple choice, (2) five-point Likert scale, and (3) open-ended questions.
Measured: When the infant 18 months
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted26 Jul 2024
- Study start17 Oct 2024
- Primary completion31 Jul 2027 (estimated)
- Study completion31 Jul 2027 (estimated)
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Other trials for Motor DisordersStudies of the same condition, open and under way.
- More trials run by National Taiwan University HospitalThe sponsor's other registered studies.
- What the trial phases meanHow a treatment moves from first tests in people to approval.
More details
For doctors and researchers: how the study is designed, who runs it, and its registry IDs.
Study design
- Study type
- Observational
- Observational model
- Cohort
- Time perspective
- Prospective
- Enrolment
- 242 participants (estimated)
Sponsor and investigators
- Lead sponsor
- National Taiwan University Hospital
- Sponsor type
- University, hospital or other
- Collaborators
- National Health Research Institutes, Taiwan
- Responsible party
- Sponsor
- Investigators
- Suh-Fang Jeng, Professor, Principal investigator, School and Graduate Institute of Physical Therapy, National Taiwan University
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT06521918
- Sponsor's protocol ID
- 202311095RIND
- Status last verified
- Dec 2024
- First submitted
- 21 Jul 2024
- Last updated
- 13 Jan 2025
- Results posted
- No
- FDA-regulated drug
- No
- FDA-regulated device
- No
Study at a glance
From the registry record, last updated by the sponsor on 13 Jan 2025. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Combined Artificial Intelligence and Mobile Application for Remote Infant Motor Screening: Development and Validation
- ClinicalTrials.gov ID
- NCT06521918
- Acronym / sponsor ID
- 202311095RIND
- Conditions
- Motor Disorders
- Keywords
- AI, infant motor assessment, APP, validation
- Study type
- Observational
- Recruitment status
- Recruiting
- Enrolment
- 242 participants (estimated)
- Lead sponsor
- National Taiwan University HospitalUniversity, hospital or other
- Collaborators
- National Health Research Institutes, Taiwan
- Study start
- 17 Oct 2024 (actual)
- Primary completion
- 31 Jul 2027 (estimated)
- Study completion
- 31 Jul 2027 (estimated)
- First posted
- 26 Jul 2024 (actual)
- Results
- Not posted in the source record
Clinical summary
The research question as the sponsor registered it. This describes what the study plans to test, not what it found.
The purpose of this study is therefore five-fold: (1) designation of an APP "Baby Go" version 3.0 to include the assessment, follow-up, and education functions for parental use at home, (2) development and validation of the AI algorithm for infant motor assessment based on home videos obtained from term and preterm infants, (3) comparison of parental perception and report with AI-driven assessment results, (4) examination of the predictive validity of the AI algorithm for infant motor assessment on subsequent outcome, and (5) investigation of the usability of the APP "Baby Go" version 3.0 in parents and clinicians.
Detailed description
Background and Purpose: Early identification and intervention of infants who are at risk of developmental disorders (such as preterm infants) is an important global health policy and action. The number of children with developmental disorders referred for early intervention in Taiwan has increased in the last ten years. Yet, they are more likely diagnosed and referred for intervention at an age beyond two years. Existing developmental diagnostic tests are frequently accessible at hospitals, whereas screening tests are often based on parental reports that are influenced by parents' knowledge and interpretation. Although the emerging artificial intelligence (AI) technology and deep learning have enabled the tracking and recognition of human movements in standardized laboratory settings, whether its incorporation with mobile application (APP) is feasible and accurate for infant motor assessment at home has rarely been investigated. Therefore, this study continues our previous endeavors that applied AI and machine learning to classify several infant movements at standardized laboratory. This study aims to combine the AI algorithm and machine learning with an APP for infant motor assessment in home setup. The specific purposes are (1) designation of an APP "Baby Go" version 3.0 to include the assessment, follow-up, and education functions for parental use at home, (2) development and validation of the AI algorithm for infant motor assessment based on home videos obtained from term and preterm infants, (3) comparison of parental perception and report with AI-driven assessment results, (4) examination of the predictive validity of the AI algorithm for infant motor assessment on subsequent outcome, and (5) investigation of the usability of the APP "Baby Go" version 3.0 in parents and clinicians. Method: This study will recruit 100 preterm infants, 20 term infants aged 2 to 18 months (corrected for prematurity), 120 infants' parents, and 2 clinicians at National Taiwan University Children's Hospital. The APP "Baby Go" version 3.0 will contain the features of age-based motor assessment with 2 to 5 movements at each age, follow-up, and education module. The parents will be asked to video record their baby's movements in prone, supine, sitting, and standing at home biweekly and to simultaneously upload the video files via the APP during the age period of 2 to 18 months, followed by recording their infant's age of walking attainment. Trained physiotherapists will annotate all video files and the results will serve as the gold standards for validation of the data of the AI model and parental perception. The video data will be randomly split into the training and testing set with an 8:2 ratio for model development and validation. The AI model of infant motor assessment will be examined for its predictive validity on age of walking attainment. The parents and clinicians will fill out the APP usability survey. Innovation and Significance: This study is an incremental AI model advancement in tracking and recognizing infant movements from a laboratory-based classification system to a home-based assessment system. The automatic AI-driven infant motor assessment via the APP "Baby Go" will provide parents and healthcare providers in Taiwan with innovative and feasible developmental resources in remote communities. The results are insightful to assist pediatricians and physiotherapists in planning diagnostic assessment and early intervention for infants at risk of neuromotor disorders.
Study design
- Observational model
- Cohort
- Time perspective
- Prospective
- Number of arms
- 3
| Arm | Type | Receives |
|---|---|---|
| Term infants | – | –The inclusion criterion is: gestational age 37-42 weeks, birth body weight >2,500 grams, and age at 2-18 months. The exclusion criterion is: parents can not read Chinese. |
| Preterm infants | – | –The inclusion criterion is: gestational age < 37 weeks, birth body weight < 2,500 grams, and corrected age of 2-18 months. The exclusion criterion is: parents can not read Chinese. |
| Clinicians | – | –The inclusion criterion is: who provide early intervention to the participating infants in this study. The exclusion criterion is: can not read Chinese |
Who may qualify
- Ages
- 2 to 18 months
- Sex
- All
- Healthy volunteers
- Accepted
- Age groups
- Child
- Study population
- This study will recruit preterm and term infants from National Taiwan University Children's Hospital (NTUCH), Taipei, Taiwan, with the former recruited from the neonatal follow-up clinic and the latter from the well-baby follow-up clinic. Two pediatric physiotherapists providing early intervention to the participating infants will be invited to complete a feedback questionnaire about the APP "Baby Go."
Eligibility is decided by the study team after screening; this overview does not establish that a patient qualifies. Full inclusion and exclusion criteria.
Primary outcome
Alberta Infant Motor Scale (AIMS)
Time frame: 3 - 18 months of age
motor function in supine, prone, sitting and standing position
Age of walking attainment
Time frame: 9 - 18 months of age
Age of attaining independent walking for at least five steps
User experience from parents
Time frame: When the infant approached 6 months, 12 months, and 18 months
Parents' perspectives on the use of the APP "Baby Go" were collected using Google Forms (For parents: https://forms.gle/BPL7CWopaB7qk3388). The questionnaire for parents was customized for the APP "Baby Go" in this study and adapted from a survey used in the "Baby Moves" APP previously described by Kwong et al. The questionnaire for the parents consisted of three sections: (1) frequency of the APP use, (2) benefits of the APP use, and (3) user's experience. Questionnaires contained three types of measures: (1) multiple choice, (2) five-point Likert scale, and (3) open-ended questions.
User experience from clinicians
Time frame: When the infant 18 months
Clinicians' perspectives on the use of the APP "Baby Go" were collected using Google Forms (for clinicians: https://forms.gle/3L7nGKe2ZTT39t7n6). The questionnaire for clinicians is customized for the APP "Baby Go" in this study and adapted from a healthcare professional interview previously described by AlMahadin et al. 44 The questionnaire for clinicians contains two sections: (1) perspectives of the APP use and (2) recommendations of APP use. Each questionnaire contains three types of measures: (1) multiple choice, (2) five-point Likert scale, and (3) open-ended questions.
Results and safety
This study is still under way. Results are not available in the source record yet.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 13 Jan 2025.
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Referral and contact
AzTrials does not enrol participants or take referrals. Contact the study team or a site listed below; they decide who can take part.
Suh-Fang Jeng, Professor principal investigator
School and Graduate Institute of Physical Therapy, National Taiwan University
1 site in 1 country: see every site and its status.
Questions about this trial
What is this clinical trial studying?
An observational study of Motor Disorders, run by National Taiwan University Hospital at 1 site in Taiwan.
The full registered description is in the About this study section and the official record.
Who may be eligible to take part?
Eligibility is decided by the study team after screening, so read the full criteria and contact a listed site.
Is this clinical trial currently recruiting?
The record says: looking for participants now, as of the sponsor's last update on 13 Jan 2025. Status can change between updates, so confirm with the study contact before making plans.
Where is the study taking place?
The record lists 1 site in Taiwan. Whether a site is taking part right now should be confirmed with that site. See every site.
What are the possible benefits and risks?
They depend on the study and the treatment, and no study can promise a benefit. The study team explains the known risks during informed consent, before anyone joins; the record itself does not list them.
Are results available for this study?
This study is still under way. Results are not available in the source record yet.
How can a doctor refer a patient or contact the research team?
Contact Suh-Fang Jeng, Professor (886-2-33668132, jeng@ntu.edu.tw), or a site near the patient. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
Alberta Infant Motor Scale (AIMS) (time frame: 3 - 18 months of age). The study lists 4 primary outcomes in all. It is what the study was designed to measure, not a finding.
Where can I read the original study information?
Does a listing mean the treatment is approved or proven to work?
No. A listing means the study is registered. It does not show that the treatment is safe, works, or is approved by a regulator.
How often is this information updated?
AzTrials copies changed records from ClinicalTrials.gov every night and reloads the whole registry every week. The sponsor last updated this record on 13 Jan 2025.