Agriculture
June 22, 2024
Okoa Ambulance
Read SolutionImplemented by
The Okoa Project
Product Description
Eyeanemia is a a mobile app for non-invasive screening for anemia.
Target SDGs
SDG 3: Good Health and Well-Being
Target Users (Target Impact Group)
Distributors / Implementing Organizations
STAT innovation
Manufacturing/Building Method
N/A
Intellectural Property Type
Copyright
User Provision Model
(Awaiting answer from manufacturer)
Distributions to Date Status
Not yet commercialized
Mobile service required
Yes, smartphone
Level of coverage needed
Unknown
Device(s) required
Unknown
Additional features required
Unknown
Permanent network connectivity required (Y/N)
Unknown
Two way communication (Y/N)
Unknown
Usage rate (%)
Unknown
Literacy support (Y/N)
Unknown
Languages available
Unknown
Operating system and version
Unknown
mHealth application
Anemia diagnosis
Design Specifications
- Simple
- Non-Invasive
- Easily accesible
Technical Support
Unknown
Replacement Components
Unknown
Lifecycle
N/A
Manufacturer Specified Performance Parameters
Unknown
Vetted Performance Status
Unknown
Safety
Unknown
Complementary Technical Systems
Unknown
Academic Research and References
Christopher Bain, Jarrel Seah, Bismi Jomon: Clinician value from big data: creating a path forwards. International Journal of Electronic Healthcare (IJEH), Vol. 9, No. 4, 2017
Wang, Edward Jay and Li, William and Hawkins, Doug and Gernsheimer, Terry and Norby-Slycord, Colette and Patel, Shwetak N (2016): HemaApp: Noninvasive Blood Screening of Hemoglobin Using Smartphone Cameras. Proceedings of the 2016 ACM International Joint Conference on Pervasive and Ubiquitous Computing
Jarrel Seah, Christopher Bain, Christopher Mac Manus, and Helen Kavnoudias (2015): A Computational Platform for Radiology Image Retrieval and Analysis. 2015 International Conference on Computer Science and Information Systems (ICCSIS-15) April 24-25, 2015 Pattaya (Thailand)
M. K. Hasan, N. Sakib, J. Field, R. R. Love and S. I. Ahamed, “A Novel Technique of Noninvasive Hemoglobin Level Measurement Using HSV Value of Fingertip Image,” 2017 IEEE 41st Annual Computer Software and Applications Conference (COMPSAC), Turin, Italy, 2017, pp. 221-229.
doi:10.1109/COMPSAC.2017.30
M. K. Hasan, N. Sakib, R. R. Love and S. I. Ahamed, “RGB pixel analysis of fingertip video image captured from sickle cell patient with low and high level of hemoglobin,” 2017 IEEE 8th Annual Ubiquitous Computing, Electronics and Mobile Communication Conference (UEMCON), New York City, NY, 2017, pp. 499-505. doi: 10.1109/UEMCON.2017.8249004
Compliance with regulations
N/A
Other Information
N/A
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