Katherine D. Mayes

Fall detection in extreme class imbalance: a cascade architecture for real-world deployment

A cascade architecture that decomposes fall detection into two sequential stages with complementary optimization objectives improves clinical viability while maintaining sensitivity above 80%, providing a foundation for real-world deployment in care settings facing severe data constraints.