B1925
Title: Digital health for Parkinson's disease (PD) diagnose and assessment
Authors: Aamna AlShehhi - Khalifa University (United Arab Emirates) [presenting]
Abstract: Parkinson's Disease (PD) is one of the fastest-growing neurological diseases in the world; it is also the second most common neurological disorder after Alzheimer's disease. In 2020, over 10 million worldwide live with PD, accounting for an annual economic burden of 52 US dollar billion. Unfortunately, to date, there is no treatment to stop or delay the progression of the disease due to the lack of effective diagnostic biomarkers. As a progressive disorder, Parkinsons' starts with slight tremors in the hand and eventually leads to uncontrollable movements. PD disease diagnosis is based on clinical symptoms that are reflected in the patient's motor functions, such as tremors and rigidity; however, these symptoms tend to appear several years after the disease's onset. A remarkable paper published recently in Nature Medicine 2022 used an artificial intelligence-based biomarker for PD using nocturnal breathing signals extracted from a breathing belt or wireless sensor. This confirms the importance of developing innovative diagnostic tools, treatments, and management protocols for these diseases. The latter can only be accomplished with the implementation of new innovative technology. Digital biomarkers are employed for PD diagnosis and assessment.
