Association of Gait Quality With Daily-Life Mobility: An Actigraphy and Global Positioning System Based Analysis in Older Adults

被引：0

作者：

Suri, Anisha ^{[1
]}

VanSwearingen, Jessie ^{[2
]}

Baillargeon, Emma M. ^{[3
,4
]}

Crane, Breanna M. ^{[5
]}

Moored, Kyle D. ^{[5
]}

Carlson, Michelle C. ^{[5
]}

Dunlap, Pamela M. ^{[2
]}

Donahue, Patrick T. ^{[5
]}

Redfern, Mark S. ^{[6
]}

Brach, Jennifer S.

Sejdic, Ervin ^{[1
,7
]}

Rosso, Andrea L. ^{[8
]}

机构：

[1] Univ Pittsburgh, Dept Elect & Comp Engn, Swanson Sch Engn, Pittsburgh, PA USA

[2] Univ Pittsburgh, Dept Phys Therapy, Sch Hlth & Rehabil Sci, Pittsburgh, PA USA

[3] Univ Pittsburgh, Div Geriatr Med, Dept Med, Sch Med, Pittsburgh, PA USA

[4] Univ Pittsburgh, Dept Epidemiol, Sch Publ Hlth, Pittsburgh, PA USA

[5] Johns Hopkins Univ, Dept Mental Hlth, Johns Hopkins Bloomberg Sch Publ Hlth, Baltimore, MD USA

[6] Univ Pittsburgh, Dept Bioengn, Swanson Sch Engn, Pittsburgh, PA USA

[7] Univ Toronto, Dept Elect & Comp Engn, Toronto, ON, Canada

[8] Univ Pittsburgh, Dept Epidemiol, Sch Publ Hlth, Pittsburgh, PA 15261 USA

来源：

IEEE TRANSACTIONS ON BIOMEDICAL ENGINEERING | 2024年 / 71卷 / 01期

关键词：

Particle measurements; Atmospheric measurements; Global Positioning System; Legged locomotion; Biomedical measurement; Older adults; Correlation; Mobility behavior; gait analysis; wearables; physical activity; PHYSICAL-ACTIVITY; MOTOR SKILL; FALL-RISK; WALKING; VALIDITY; HEALTH; SPEED; RELIABILITY; VALIDATION; GUIDELINES;

D O I：

10.1109/TBME.2023.3293752

中图分类号：

R318 [生物医学工程];

学科分类号：

0831 ;

摘要：

Objective: Walking is a key component of daily-life mobility. We examined associations between laboratory-measured gait quality and daily-life mobility through Actigraphy and Global Positioning System (GPS). We also assessed the relationship between two modalities of daily-life mobility i.e., Actigraphy and GPS.Methods: In community-dwelling older adults (N = 121, age = 77 +/- 5 years, 70% female, 90% white), we obtained gait quality from a 4-m instrumented walkway (gait speed, walk-ratio, variability) and accelerometry during 6-Minute Walk (adaptability, similarity, smoothness, power, and regularity). Physical activity measures of step-count and intensity were captured from an Actigraph. Time out-of-home, vehicular time, activity-space, and circularity were quantified using GPS. Partial Spearman correlations between laboratory gait quality and daily-life mobility were calculated. Linear regression was used to model step-count as a function of gait quality. ANCOVA and Tukey analysis compared GPS measures across activity groups [high, medium, low] based on step-count. Age, BMI, and sex were used as covariates.Results: Greater gait speed, adaptability, smoothness, power, and lower regularity were associated with higher step-counts (0.20<|rho(p)| < 0.26, p < .05). Age(beta = -0.37), BMI(beta = -0.30), speed(beta = 0.14), adaptability(beta = 0.20), and power(beta = 0.18), explained 41.2% variance in step-count. Gait characteristics were not related to GPS measures. Participants with high (>4800 steps) compared to low activity (steps<3100) spent more time out-of-home (23 vs 15%), more vehicular travel (66 vs 38 minutes), and larger activity-space (5.18 vs 1.88 km(2)), all p < .05.Conclusions: Gait quality beyond speed contributes to physical activity. Physical activity and GPS-derived measures capture distinct aspects of daily-life mobility. Wearable-derived measures should be considered in gait and mobility-related interventions.

引用

页码：130 / 138

页数：9