Data-driven combinatorial optimization for sensor-based assessment of near falls

• Published in: Annals of operations research Vol. 276; no. 1-2; pp. 137 - 153
• Main Authors: Kammerdiner, Alla R., Guererro, Andre N.
• Format: Journal Article
• Language: English
• Published: New York Springer US 01.05.2019; Springer; Springer Nature B.V
• Subjects: Accidental falls; Age; Analysis; Assignment problem; Business and Management; Care and treatment; Combinatorial analysis; Combinatorial optimization; Combinatorics; Computational Biomedicine; Economic aspects; Elderly; Experiments; Falls; False alarms; Human subjects; Management science; Operations research; Operations Research/Decision Theory; Optimization; Public health; Ratings & rankings; Sensors; Theory of Computation; Time series; United States; Systems of wearable sensors; The multidimensional assignment problem; Falls and near falls

Falls represent a considerable public health problem, especially in older population. We describe and evaluate data-driven operations research models for detection and situational assessment of falls and near falls with a system of wearable sensors. The models are formulated as instances of the mult...