Linear-Sigmoidal modelling of accelerometer features and Tinetti score for automatic fall risk assessment

• Published in: Conference proceedings (IEEE Engineering in Medicine and Biology Society. Conf.) Vol. 2017; pp. 3810 - 3813
• Main Authors: Rivolta, Massimo W., Sassi, Roberto
• Format: Conference Proceeding Journal Article
• Language: English
• Published: United States IEEE 01.07.2017
• Subjects: Accelerometers; Biological system modeling; Feature extraction; Linear regression; Predictive models; Training

Falling in elderly is a worldwide major problem and it can lead to severe injuries or death. Despite the effort made to ensure home environments safe and foster healthy lifestyles, it is still necessary to provide methodologies that can be used at home for detect risk factors associated with falls....