Development of Algorithms for Automated Timed Up-and-Go Test Subtask and Step Frequency Analysis

Area of Science:

• Gerontology
• Biomedical Engineering
• Rehabilitation Technology

Background:

• Aging societies face significant challenges with frailty.
• Early detection and autonomous monitoring of frailty status are crucial.
• The Timed Up-and-Go test is a key functional assessment for the elderly.

Purpose of the Study:

• To develop and validate algorithms for autonomous frailty assessment using an ultrasound-based Timed Up-and-Go system.
• To enable accurate detection of subtasks within the Timed Up-and-Go test.
• To achieve precise estimation of step frequency for enhanced frailty monitoring.

Main Methods:

• Development of algorithms for detecting subtasks: stand up, walk, turn around, sit down.
• Implementation of algorithms for step frequency estimation from ultrasound signals.
• Validation of algorithms using an annotated dataset from 8 healthy subjects.

Main Results:

• Subtask transition detection algorithms achieved a mean error between 0.22 and 0.35 seconds.
• Step frequency estimation demonstrated a mean error of 0.15 Hz.
• Algorithms showed promising accuracy in preliminary testing with healthy individuals.

Conclusions:

• The developed algorithms enable autonomous and accurate assessment of the Timed Up-and-Go test using ultrasound technology.
• This technology supports early frailty detection and monitoring in an aging population.
• Future work will focus on prospective evaluation with elderly individuals to confirm clinical utility.