According to the World Health Organization (WHO), pneumonia is one of the most solvable problems in global health – it can be treated with a 3- to 5-day course of antibiotics that cost $0.40. However, it often goes undiagnosed or misdiagnosed until it’s too late; a child dies from the infection every 20 seconds, especially in remote areas where diagnostic equipment and doctors are scarce. In sub-Saharan Africa, more than 490,000 children younger than five died from the disease in 2015.
Wearable medical device
Graduates Olivia Koburongo, Besufekad Shifferaw, and Brian Turyabagye from Makere University in Uganda set out to create a diagnostic tool after seeing the results of a missed pneumonia diagnosis: Koburongo lost her grandmother to the illness that doctors initially thought was malaria.
“Many of those deaths are because of misdiagnosis,” Turyabagye says. “In villages and remote areas, children get sick, and the first reaction is to treat them for malaria. Most people are aware of malaria, and the signs for malaria and pneumonia are very similar. So, it is difficult for health professionals to differentiate.”
The team designed a biomedical smart jacket that would analyze the patient’s temperature, breathing rate, and wheezing sound in the lungs, diagnosing pneumonia 3x to 4x faster than a doctor and lessening the burden on medical professionals in a region that faces an extreme shortage of trained doctors.
The device – MamaOpe, which means mother’s hope – uses precisely placed sensors to work like a wearable stethoscope. Since it doesn’t require a doctor to run the tests, it can be used in remote locations.
MamaOpe connects to a mobile phone app via Bluetooth, surveying specific points on the lungs for pneumonia symptoms, characterized by swelling of the lungs.
It then records and analyzes data, which is sent to a healthcare professional for a diagnosis.MamaOpe was developed through MATLAB, a proprietary programming language and numerical computing engineering environment offered by mathematical computing software expert MathWorks.
“We use MATLAB signal analysis functions to analyze the data collected by the device. It helps filter and identify abnormal patterns,” Turyabagye notes. “The analysis determined parameters that were crucial to the project. These parameters guided the implementation stages, such as the design of the filter and amplifier circuits.”
“The problem we’re trying to solve is diagnosing pneumonia at an early stage before it gets severe and we’re also trying to solve the lack of manpower in hospitals because currently we have a doctor-to-patient ratio which is 1-to-24,000 in the country,” Koburongo says.
The team is currently working to have the device certified in Uganda. Once certified by the regulatory authority, the team intends to produce and supply the jacket to countries in East Africa.