title: Unobtrusive monitoring and identification of fall accidents.
abstract: Falls are a societal and economic problem of great concern with large parts of the population, in particular older citizens, at significant risk and the result of a fall often being grave. It has long been established that it is of importance to provide help to a faller soon after the event to prevent complications and this can be achieved with a fall monitor. Yet, the practical use of currently available fall monitoring solutions is limited due to accuracy, usability, cost, and, not in the least, the stigmatising effect of many solutions. This paper proposes a fall sensor concept that can be embedded in the user's footwear and discusses algorithms, software and hardware developed. Sensor performance is illustrated using results of a series of functional tests. These show that the developed sensor can be used for the accurate measurement of various mobility and gait parameters and that falls are detected accurately.
authors.affiliation: Department of Electronic and Computer Engineering, University of Limerick, Limerick, Ireland . Electronic address: pepijn.vandeven@ul.ie.
authors.forename: Pepijn
authors.initials: P
authors.lastname: van de Ven
authors.affiliation: Department of Electronic and Computer Engineering, University of Limerick, Limerick, Ireland.
authors.forename: Hugh
authors.initials: H
authors.lastname: O'Brien
authors.affiliation: Department of Electronic and Computer Engineering, University of Limerick, Limerick, Ireland.
authors.forename: John
authors.initials: J
authors.lastname: Nelson
authors.affiliation: Department of Clinical Therapies, University of Limerick, Limerick, Ireland.
authors.forename: Amanda
authors.initials: A
authors.lastname: Clifford
mesh_terms: D061725:Accelerometry / Q000295:instrumentation* / Q000379:methods*; D000058:Accidental Falls / Q000517:prevention & control; D000203:Activities of Daily Living; D004867:Equipment Design; D006801:Humans; D000069550:Machine Learning; D018670:Monitoring, Ambulatory / Q000295:instrumentation* / Q000379:methods*; D011187:Posture; D012775:Shoes; D012984:Software
keywords: Accelerometry; Ambient assisted living; Fall sensing; Falls prevention; Mobile health