title: Fall detection of elderly through floor vibrations and sound.
abstract: Falls are very prevalent among the elderly especially in their home. The statistics show that approximately one in every three adults 65 years old or older falls each year. Almost 30% of those falls result in serious injuries. Studies have shown that the medical outcome of a fall is largely dependent upon the response and rescue time. Therefore, reliable and immediate fall detection system is important so that adequate medical support could be delivered. We have developed a unique and inexpensive solution that does not require subjects to wear anything. The solution is based on floor vibration and acoustic sensing, and uses a pattern recognition algorithm to discriminate between human or inanimate object fall events. Using the proposed system we can detect human falls with a sensitivity of 95% and specificity of 95%.
authors.affiliation: Department of Biomedical Engineering, Faculty of Engineering, Tel-Aviv University, 69978, Israel. litvakdi@post.tau.ac.it
authors.forename: Dima
authors.initials: D
authors.lastname: Litvak
authors.forename: Yaniv
authors.initials: Y
authors.lastname: Zigel
authors.forename: Israel
authors.initials: I
authors.lastname: Gannot
mesh_terms: D000058:Accidental Falls / Q000517:prevention & control*; D000061:Accidents, Home / Q000517:prevention & control; D000162:Acoustics; D000368:Aged; D000465:Algorithms; D003201:Computers; D004779:Environment Design; D004867:Equipment Design; D015444:Exercise; D006801:Humans; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D013016:Sound; D017216:Telemedicine / Q000295:instrumentation / Q000379:methods*; D014741:Video Recording