Improving Fall Detection Devices for Older Adults Using Quality Function Deployment (QFD) Approach.

Area of Science:

• Engineering
• Gerontology
• Human-Computer Interaction

Background:

• Increasing fall prevalence among older adults presents a significant global health challenge.
• Existing fall detection devices often lack features prioritized by consumers.
• Engineering solutions must align with public demands for effective technological advancements.

Purpose of the Study:

• To develop an improved fall detection device by integrating consumer perspectives.
• To identify and incorporate essential features for fall prevention technology based on user needs.
• To enhance existing fall detection devices with user-centric design principles.

Main Methods:

• A three-phase design process was employed: Questionnaire, Ishikawa Method, and Quality Function Deployment (QFD).
• Customer needs were identified through requirement analysis.
• Needs were translated into design specifications for the fall detection device using QFD.

Main Results:

• Quality Function Deployment (QFD) was utilized to translate customer needs into actionable design specifications.
• Balance monitoring was identified as the top priority feature by consumers.
• The study outlines the integration of these prioritized features into an improved fall detection device.

Conclusions:

• Incorporating consumer perspectives through QFD leads to more relevant and effective technological solutions.
• The developed fall detection device, with enhanced balance monitoring, can significantly aid older adults in assessing and mitigating fall risks.
• Future engineering inventions should prioritize user demands to address critical societal challenges like fall prevention.