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

被引：3
|
作者：
Kammerdiner, Alla R. [1 ]
Guererro, Andre N. [1 ]
机构：
[1] New Mexico State Univ, POB 30001,MSC 4230, Las Cruces, NM 88003 USA
来源：
ANNALS OF OPERATIONS RESEARCH | 2019年 / 276卷 / 1-2期
基金：
美国国家科学基金会;
关键词：
The multidimensional assignment problem; Falls and near falls; Systems of wearable sensors; RATER;
D O I：
10.1007/s10479-017-2585-1
中图分类号：
C93 [管理学]; O22 [运筹学];
学科分类号：
070105 ; 12 ; 1201 ; 1202 ; 120202 ;
摘要：
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 multidimensional assignment problem. Our computational studies provide some initial empirical evidence of the potential usefulness of this new application of the multidimensional assignment problem.
引用
收藏
页码：137 / 153
页数：17
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