A Medtech device for diagnosing pneumonia

Each year there are approximately 120 million cases of pneumonia, of which 1 million kids under 5 years die. Especially in resource-limited areas, there is a higher risk of being affected by the disease. The diagnosis is typically given by local health care providers who count the children's respiratory rate. This can be a complicated procedure due to unexpected movements from the child and distracting sounds from the environment. In addition, being in this monitoring situation can cause increased heart rate. In this project, we have developed a product that can diagnose pneumonia using artificial intelligence and sound recognition. The monitoring process is shorter and the diagnose much more accurate because the diagnose is based on real data rather than an assessment of symptoms. Additionally, the risk of counting-errors are eliminated. The design form is based on and developed from ergonomics taking the availability of battery types into account.