PANDA MOBILE Downloads & RevenuePANDA MOBILE · App Store
Not in any tracked top chart right now.
Updated 8 Nov 2026 · rankings refresh through the day
DeveloperAngel Eye Camera Systems
CategoryMedical
PriceFree
Released
Rating★ 2.5 (2)
Version1.6
Age rating4+
First seen by us
24 Oct 2026
Full timeline · 2 events in the last 12 months
- 🆕PANDA MOBILE first spotted by AppInsiderUnited States (found via developer)
- 🆕PANDA MOBILE released on the App Store
Collected from the stores by AppInsider since we first spotted the app. Dates are when we saw each change.
Rating
2.5 ★
2 ratings
Measured
PANDA MOBILE on the App Store
App details
App ID
1542013627
Publisher
Angel Eye Camera Systems, LLC
On the store since
Jan 2021
5 years on the store
Minimum OS
iOS 12.0+
iPhone 5s and later
Devices
iPhone · iPad
Content rating
4+
Languages
1
EN
Size
10 MB
Also listed in
Reference
Where it ranks now
Every top chart it appears in across 30 countries.
| Country | Charts | Rank |
|---|---|---|
| Not charting right now. | ||
Ratings
App Store, worldwide.
Rating
2.5 ★
2 ratings
Measured
Ratings
2
Measured
About PANDA MOBILE
PANDA MOBILE App allows us to collect video data of infants between 1 and 6 months old. We will analyze the videos using state of the art algorithms to build screening tools that can be used in life by lay clinicians and caregivers. The study’s goal is to develop an affordable non-invasive easy-to-use tool for early detection of infant neurodevelopmental disabilities so they can receive treatment at an early age.
Significance: In the USA, 1 in 10 infants are born at risk for these disabilities. Early treatment in the first year of life improves long-term outcomes. Today’s clinical tests are however less than adequate. Hard to administer, they require specialized training, and have limited long-term predictive value. There is a critical need for an objective, accurate, easy-to-use tool for early prediction of long-term physical disability. This project’s goal is to develop an automated assessment for early and accurate detection of infants at risk for neurodevelopmental disabilities by capitalizing on state of the art sensing and machine learning technologies. Our project will bring us closer to a universal non-invasive test for early detection of neurodevelopmental disabilities. This test will scale to infants worldwide, producing an affordable tool for infant health assessment.
Objectives: Our project has three aims. This effort focuses on aim 2 which is to populate a database of infant videos. We aim to collect at least 1200 unique infant videos (400 with early brain injury, 400 preterm without early brain injury, 400 controls). From the videos we will develop a computer vision algorithm to quantify infant motor performance.
Funding: Our project is being funded by the National Institutes of Health – National Institutes of Child Health and Development: R01- HD-097686. We are in partnership with AngelEye Health, a leader in developing cameras for the NICU and monitoring infants."
Significance: In the USA, 1 in 10 infants are born at risk for these disabilities. Early treatment in the first year of life improves long-term outcomes. Today’s clinical tests are however less than adequate. Hard to administer, they require specialized training, and have limited long-term predictive value. There is a critical need for an objective, accurate, easy-to-use tool for early prediction of long-term physical disability. This project’s goal is to develop an automated assessment for early and accurate detection of infants at risk for neurodevelopmental disabilities by capitalizing on state of the art sensing and machine learning technologies. Our project will bring us closer to a universal non-invasive test for early detection of neurodevelopmental disabilities. This test will scale to infants worldwide, producing an affordable tool for infant health assessment.
Objectives: Our project has three aims. This effort focuses on aim 2 which is to populate a database of infant videos. We aim to collect at least 1200 unique infant videos (400 with early brain injury, 400 preterm without early brain injury, 400 controls). From the videos we will develop a computer vision algorithm to quantify infant motor performance.
Funding: Our project is being funded by the National Institutes of Health – National Institutes of Child Health and Development: R01- HD-097686. We are in partnership with AngelEye Health, a leader in developing cameras for the NICU and monitoring infants."
Latest updates
1.6
- Bug fixes and usability enhancements