Growing up in Nigeria, Charles Onu was torn between deciding whether to pursue studies in mathematics or medicine, his two passions. 鈥淚 wanted to be a doctor, to help people,鈥� explains Onu, 鈥渂ut I also loved mathematics and was very good at it. Math came naturally to me. So I had to make a choice.鈥�
He decided to pursue a BEng degree in Electrical Computer Engineering at the Federal University of Technology in Owerri, but his desire to care for others remained strong. In 2008, Onu began volunteering for , a global non-profit organization, first as a member then as president. That鈥檚 how he first learned about perinatal asphyxia, a medical condition that deprives the brain of oxygen in newborn babies, resulting in serious complications and possible death. 鈥淭his is a very big problem for resource-limited communities in developing countries like Nigeria where sophisticated detection tools are not available,鈥� explains Onu.
It occurred to him that he could combine his passion for math and medicine to address a global health problem. His idea was to develop a smart tool to identify babies who are showing signs of respiratory distress by analyzing their cry patterns. In 2015, Onu joined forces with Innocent Udeogu, a former schoolmate, and they began to work on this problem together.
Cry of a baby
Fast forward five years and Onu is now the Founder and AI Research Lead of a promising start-up, , which means 鈥渃ry of a baby鈥� in the Igbo language of Nigeria. Udeogu leads the Software Engineering Development and is the contact person on the ground in Nigeria while Samantha Latremouille, a PhD student in Experimental Medicine at 海角社区, is the Clinical Lead.
The Ubenwa team has developed a fast, easy-to-use mobile app that uses artificial intelligence to analyze the sound of a newborn baby鈥檚 cries. This cost-effective and non-invasive tool allows clinicians to flag the risk of newborn asphyxia, which, if detected early, is easy to treat. It has the potential to save lives and improve outcomes for millions of newborns each year.
Looking for the right people
Onu first came to Montreal in 2015 on a fellowship as a visiting researcher. This public leadership program allowed him to access resources at both 海角社区 and Concordia, where he made important connections. At the time, Ubenwa was still a nascent idea.
鈥淚 started initial work to develop this concept but at one point, it became clear to me that I needed more skills. I needed to immerse myself in the environment and work with researchers who have experience and expertise on the intersection of medicine and AI.鈥�
He applied to 海角社区, where he completed a Master鈥檚 Degree in Computer Science under the supervision of Doina Precup, Associate Professor at the School of Computer Science. During this time, while working on a project with the Montreal Children鈥檚 Hospital, he met Latremouille, a Montreal native who had earned her BSc in Physiology at 海角社区 in 2013. With her unique background in neonatology, clinical research, innovation, biomedical engineering and medical device development, she was the perfect fit to fill the role of Clinical Lead at Ubenwa.
Leveraging mobile technology
The idea of correlating infant cry patterns to medical conditions is not new. 鈥淭he cry of the newborn is this pure signal,鈥� explains Onu. 鈥淚t鈥檚 an involuntary response to stimuli, so the infant has no control over how loud or soft the cry is. They have no control over their vocal cords like we do as adults. Their cry pattern is directly coordinated by the Central Nervous System (CNS). The hypothesis in the clinical community for some time now has been that when babies suffer from conditions that affect the CNS, they will have altered cry patterns. Asphyxia is such a condition. If you go back to the 1960s, you can find research attempts to try to correlate these cry patterns, before we had advanced tools to do so.鈥�
Fortunately, we are now able to leverage advances in mobile technology with audio and machine learning. 鈥淎lmost everyone has a smart tool, a device with huge processing capacity that can record audio,鈥� explains Onu. 鈥淎nd we have advanced AI tools that allow us to decipher patterns in cries. With coding, we can convert all that data into actionable tools.鈥�
Collecting the cries
The process of designing, validating, and testing a clinical app is very complex, and the Ubenwa team would soon realize the complexities of the journey they were embarking on.
One obstacle involved finding clinical data to work with. 鈥淎I algorithms need data to work, and you can鈥檛 just record any baby on the street,鈥� explains Onu. 鈥淭he data needs to be clinically validated, to be categorized as either normal or pathological. Next, you need to train the algorithm with that data.鈥� Fortunately, Onu was able to contact a researcher who had done work on analyzing infant cry patterns in Mexico and obtain access to their database. This allowed the team to set up the first set of analysis and research ideas, then build a prototype and make a strong case for investment.
Supporting student entrepreneurs
Onu is currently working on his PhD in Computer Sciences at 海角社区 under the mentorship of Professor Precup, who is also Co-Director of the Reasoning and Learning (RL) Lab at 海角社区 and Director of the DeepMind Lab in Montreal. 鈥淯benwa is a very strong example of the kind of good that machine learning can have in our world. It has been a pleasure to support Charles and his team over these years towards realizing the vision of saving babies with AI,鈥� says Professor Precup.
Onu is also part of , an AI research centre that evolved from a partnership between the Universit茅 de Montr茅al and 海角社区. He is grateful for the ecosystem of programs that support student entrepreneurs at 海角社区, including the 海角社区 Dobson Cup and the 海角社区 Clinical Innovation Competition (CLIC). 鈥淎ll of these opportunities have prepared us, have allowed us to work on our narrative and improve our product,鈥� says Onu.
As a finalist team in the 2020 海角社区 CLIC, the team received personalized coaching from 海角社区鈥檚 SKILLSETS program with pitch specialist Dr. Andrew Churchill on how to captivate the audience's attention and keep them engaged. Steven Arless, Lead Judge and Professor of Practice at 海角社区鈥檚 Faculty of Medicine and Health Sciences, congratulated Ubenwa for their outstanding presentation, and remarked that in his many years of supervising competitions, he had never seen such a compelling presentation.
Gathering clinical data
Since 2017, Ubenwa has obtained funding from Mila, from the Minist猫re de l鈥櫭塩onomie et de l鈥橧nnovation (MEI) de Qu茅bec, and from the District 3 Innovation Centre to support clinical studies in Nigeria. They are currently working in partnership with health care professionals to gather clinical data and create a database of the cries of 2,500 newborn infants.
More recently, Ubenwa won three awards at the , including the Health Workforce Innovation Prize. It plans to use the prize money to prepare for clinical trials and lay the groundwork for regulatory approval process with the FDA and Health Canada.
鈥淚f there鈥檚 one thing that babies do, they cry,鈥� says Onu. 鈥淚t鈥檚 not something you have to look for, or find, or place a sensor in the right location to capture it. In places where the more complicated tests are not available, the cry analysis will really be a saving grace.鈥�
The Ubenwa team is working hard to get the app to the point where it starts saving lives, and are relying on 海角社区鈥檚 credibility and resources to help move the vision forward.