Infant Behavior
Conditions
Brief summary
To assess the ability of a machine learning algorithm to accurately detect fussing and crying time in infants using accelerometery data collected from a wearable device, compared to the Barr's parent-/caregiver-completed behaviour diary.
Interventions
DEVICEActiveInsights accelerometer device
Accelerometer device
Sponsors
Atlantia Food Clinical Trials
ActivInsights
BioGaia AB
Study design
Allocation
NON_RANDOMIZED
Intervention model
SINGLE_GROUP
Primary purpose
DEVICE_FEASIBILITY
Masking
NONE
Intervention model description
Part 1: 3 subjects for 4 days included to collect initial data for algoritm development for device feasibility evaluation Part 2: 10 subjects for 7 days included to evaluate device feasibility
Eligibility
Sex/Gender
ALL
Age
4 Weeks to 12 Weeks
Healthy volunteers
Yes
Inclusion criteria
1. Aged between 4-12 weeks at screening. 2. Gestational age 37 weeks - 41 weeks at birth. 3. Birth weight appropriate for gestational age (AGA - weight between 10th and 90th percentile) or Large for Gestational Age (LGA - weight above the 90th percentile) determined using WHO Weight-for Age percentile guides. 4. Infant has excessive crying, defined as 3 or more hours per day, during 3 or more days in the preceding week. 5. No birth trauma and nonsyndromic. 6. Readiness and the opportunity for parents/caregivers to fill out a study diary, questionnaires and for infant to wear device. 7. Parent/caregiver with ability to understand and comply with the requirements of the study, as judged by the Investigator. 8. Parent/caregiver willing and able to give informed consent for their and their infant's participation in the study. 9. Infant is considered healthy, following physical exam.
Exclusion criteria
1. Infants with failure to thrive, intrauterine growth retardation, haematochezia (blood in the stools), diarrhoea (watery stools that takes the shape of a container \> 12x in breastfed and \>5 in partially breastfed infants daily), or fever (38.0 degrees). 2. Premature infants (\<35 weeks gestation at birth). 3. Infants with congenital heart disease, immunodeficiency, asplenia, cancer, cystic fibrosis, formula-fed infants, and those with liver disease.
Design outcomes
Primary
| Measure | Time frame | Description |
|---|---|---|
| Device feasibility: Comparison of device-generated versus diary-reported crying and fussing time data | 4 days | Part 1: Comparison of daily crying and fussing time data generated by accelerometer and machine-learning versus crying and fussing time data reported by parental Barrs diary |
Secondary
| Measure | Time frame | Description |
|---|---|---|
| Device feasibility: Comparison of device-generated versus diary-reported crying time data | 7 days | Part 2: Comparison of daily crying time data generated by accelerometer and machine-learning versus crying time data reported by parental Barrs diary |
| Device feasibility: Comparison of device-generated versus diary-reported fussing time data | 7 days | Part 2: Comparison of daily fussing time data generated by accelerometer and machine-learning versus fussing time data reported by parental Barrs diary |
| Device feasibility: Comparison of device-generated versus diary-reported sleeping time data | 7 days | Part 2: Comparison of daily sleeping time data generated by accelerometer and machine-learning versus sleeping time data reported by parental Barrs diary |
Countries
Ireland
Contacts
Primary ContactGianfranco Grompone, PhD
Outcome results
None listed