300 Section - Upper and lower trunk accelerometer-based metrics during gait as predictors of physical function in older adults

Tuesday, May 19, 2026

6:00 PM - 7:30 PM PT

Presenting Author/Autor expositor(s)

TO

Takahiro Oki, MD

Graduate Student
The University of Tokyo Hospital
Bunkyo-ku, Tokyo, Japan

Co-Author/Coautor(s)

KY

Keiko Yamada, PhD

Associate Professor
Saitama Prefectural University
Koshigaya-shi, Saitama, Japan
RN

Ryoki Nishimoto, MD

Assistant Professor
The University of Tokyo Hospital
Bunkyo-ku, Tokyo, Japan
SF

Sayaka Fujiwara, PhD

Associate professor
The University of Tokyo Hospital
Bunkyo-ku, Tokyo, Japan
TO

Toru Ogata, PhD

professor
The University of Tokyo Hospital
Bunkyo-ku, Tokyo, Japan

Objectives : As many countries face an aging society, there is a need to extend the period during which older adults remain healthy and independent. Physical function and activities of daily living (ADLs) are key determinants of independence in older adults, with walking being an essential component of ADLs. Given that gait function declines with age, early detection of functional decline and provision of cause-specific interventions is important, and appropriate gait assessment is required.

Design:

We conducted a gait analysis in older adults with declining mobility, using accelerometers attached to the upper and lower trunk to determine optimal metrics for assessing gait impairment. Gait assessment was performed using accelerometer-based metrics from the acceleration waveform. Physical function was evaluated using the five-repetition sit-to-stand test, single-leg standing time, three-meter Timed Up and Go Test, preferred gait speed, and the locomotive syndrome risk test. Univariate, multiple regression, and principal component regression analyses were performed to determine the relationship between performance and accelerometer-based metrics.

Results: Accelerometer-based metrics, specifically upper Root Mean Square (RMS) in the vertical direction and upper improved Harmonic Ratio in the anteroposterior direction, were strongly associated with performance metrics. Each metric reflected different aspects of gait.

Conclusion: Accelerometer-based metrics obtained by attaching sensors to the upper and lower trunk reflect physical function and can detect subtle changes in the locomotor system that conventional spatiotemporal parameters or clinical assessments may overlook. Their application enables detailed assessment of gait characteristics and holds promise in rehabilitation therapy.