title: An automatic fall detection framework using data fusion of Doppler radar and motion sensor network.
abstract: This paper describes the ongoing work of detecting falls in independent living senior apartments. We have developed a fall detection system with Doppler radar sensor and implemented ceiling radar in real senior apartments. However, the detection accuracy on real world data is affected by false alarms inherent in the real living environment, such as motions from visitors. To solve this issue, this paper proposes an improved framework by fusing the Doppler radar sensor result with a motion sensor network. As a result, performance is significantly improved after the data fusion by discarding the false alarms generated by visitors. The improvement of this new method is tested on one week of continuous data from an actual elderly person who frequently falls while living in her senior home.
authors.forename: Liang
authors.initials: L
authors.lastname: Liu
authors.forename: Mihail
authors.initials: M
authors.lastname: Popescu
authors.forename: Marjorie
authors.initials: M
authors.lastname: Skubic
authors.forename: Marilyn
authors.initials: M
authors.lastname: Rantz
mesh_terms: D000058:Accidental Falls; D019540:Area Under Curve; D006801:Humans; D008991:Monitoring, Physiologic / Q000295:instrumentation; D012372:ROC Curve; D011825:Radar