Towards Safer Mobility: Developing and Evaluating a Fall Detection System for a Smart Walker
Maria Sole Cavaglià, Sergio D. Sierra M., Luca Palmerini, Silvia Orlandi, Marcela Múnera, Carlos A. Cifuentes · 2024
Fall detection and prevention is a key issue for healthcare in older adults since it prevents the development of multiple cognitive and physical disorders. This study aims to evaluate multiple falls and near-fall detection algorithms to be integrated into a smart walker, which usually comes with an increased risk for falls in case of improper use. A six-axis IMU worn at the user's waist extracts trunk inclination, angular velocity and acceleration. The study employs various fall detection algorithms, such as Kangas and Vertical Velocity, tailored for fall detection, Triangular Feature, Vertical Angle and a Modified Vertical Velocity for pre-fall detection. The ex-perimental protocol involved various Activities of Daily Living (ADLs) and simulated falls, emphasizing participant safety and data usability. The results from this study provide insights into the effectiveness and reliability of the integrated fall detection system in scenarios involving a smart walker.