A nurse-driven method for developing artificial intelligence in "smart" homes for aging-in-place

被引：51

作者：

Fritz, Roschelle L. ^{[1
]}

Dermody, Gordana ^{[2
]}

机构：

[1] Washington State Univ, Coll Nursing, 14204 NE Salmon Creek Ave,VLIB210E, Vancouver, WA 98686 USA

[2] Edith Cowan Univ, Sch Nursing & Midwifery, Joondalup Campus, Perth, WA, Australia

来源：

NURSING OUTLOOK | 2019年 / 67卷 / 02期

基金：

美国国家卫生研究院;

关键词：

Smart home; Sensors; Artificial intelligence; Ground truth; Mixed methods; Data processing; Conceptual model; Aging-in-place; INFORMATION-TECHNOLOGY; CARE COORDINATION; IMPLEMENTATION;

D O I：

10.1016/j.outlook.2018.11.004

中图分类号：

R47 [护理学];

学科分类号：

1011 ;

摘要：

Objectives: To offer practical guidance to nurse investigators interested in multidisciplinary research that includes assisting in the development of artificial intelligence (AI) algorithms for "smart" health management and aging-in-place. Methods: Ten health-assistive Smart Homes were deployed to chronically ill older adults from 2015 to 2018. Data were collected using five sensor types (infrared motion, contact, light, temperature, and humidity). Nurses used telehealth and home visitation to collect health data and provide ground truth annotation for training intelligent algorithms using raw sensor data containing health events. Findings: Nurses assisting with the development of health-assistive AI may encounter unique challenges and opportunities. We recommend: (a) using a practical and consistent method for collecting field data, (b) using nurse-driven measures for data analytics, (c) multidisciplinary communication occur on an engineering-preferred platform. Conclusions: Practical frameworks to guide nurse investigators integrating clinical data with sensor data for training machine learning algorithms may build capacity for nurses to make significant contributions to developing AI for health-assistive Smart Homes.

引用

页码：140 / 153

页数：14

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