Search research articles

Search research articles

Related Experiment Videos

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

Roschelle L Fritz¹, Gordana Dermody²

¹College of Nursing, Washington State University - Vancouver Vancouver, WA.

Nursing Outlook

|December 16, 2018

Summary

This summary is machine-generated.

Related Concept Videos

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by

Same author

Beyond innovation: Reimagining inclusive and ethical technologies for ageing populations.

Digital health·2026

Same author

Building trust to enhance community-engaged research and attain health equity.

Nursing outlook·2026

Same author

Interpretation of Health-Smart Home Data and Implications for Clinical Decision-Making: Inductive Content Analysis.

JMIR nursing·2025

Same author

Need for a Shared Responsibility for Developing Digital Expertise in the Nursing Profession.

Studies in health technology and informatics·2025

Same author

A Global Gerontechnology Center for Nursing Science for improving aging-in-place technologies.

Nursing outlook·2025

Same author

Positional release technique in the management of low back pain: A systematic review and meta-analysis.

Journal of bodywork and movement therapies·2025

ABOUT JoVE

Overview Leadership Blog JoVE Help Center

AUTHORS

Publishing Process Editorial Board Scope & Policies Peer Review FAQ Submit

LIBRARIANS

Testimonials Subscriptions Access Resources Library Advisory Board FAQ

RESEARCH

JoVE Journal Methods Collections JoVE Encyclopedia of Experiments Archive

EDUCATION

JoVE Core JoVE Business JoVE Science Education JoVE Lab Manual Faculty Resource Center Faculty Site

Terms & Conditions of Use

Nurses can contribute to developing artificial intelligence (AI) for smart health management by collecting field data and using nurse-driven analytics. This research provides practical guidance for integrating clinical and sensor data to train AI algorithms for aging-in-place technologies.

Area of Science:

Nursing Research
Artificial Intelligence
Gerontology

Background:

Smart Home technologies offer potential for enhanced health management and aging-in-place.
Integrating artificial intelligence (AI) into healthcare requires robust data collection and analysis.
Nurse investigators play a crucial role in bridging clinical insights with technological development.

Purpose of the Study:

To provide practical guidance for nurse investigators involved in developing AI algorithms for smart health management.
To support the integration of clinical data with sensor data for AI model training in aging-in-place solutions.
To enhance nurse capacity in contributing to AI-driven healthcare innovations.

Main Methods:

Deployment of ten health-assistive Smart Homes for chronically ill older adults (2015-2018).

Keywords:

Aging-in-place Artificial intelligence Conceptual model Data processing Ground truth Mixed methods Sensors Smart home

Related Experiment Videos

Collection of data using five sensor types (infrared motion, contact, light, temperature, humidity).

Utilization of telehealth and home visitation by nurses for data collection and ground truth annotation for AI training.

Main Results:

Nurses face unique challenges and opportunities when developing health-assistive AI.
Recommendations include consistent field data collection methods and nurse-driven data analytics.
Effective multidisciplinary communication on engineering-preferred platforms is crucial.

Conclusions:

Developing practical frameworks for nurse investigators is essential for integrating clinical and sensor data.
This integration builds capacity for nurses to significantly contribute to AI development for smart health-assistive environments.
AI holds promise for improving health management and supporting aging-in-place.