A Feasibility Study to Quantify Gait Performance in the Elderly Using Markerless Motion Capture Systems

Gen-Yan Lin, Ni Chong, Tzu-Ming Chang, Chich-Haung Richard Yang
Purpose:

This study aimed to assess the feasibility of using OpenCap to quantify age-related gait alterations by comparing kinematic parameters between older and young adults.

Methods:

Thirteen old subjects (age: 73.46 ± 6.98 years, height: 1.58 ± 0.09 m, 57.65 ± 7.76 kg, BMI: 22.95 ± 2.26 kg/m2) and 13 young controls (age: 21.15 ± 2.27 years, height: 1.64 ± 0.09 m, 56.85 ± 12.97 kg, BMI: 21.05 ± 3.27 kg/m2) were required and instructed to complete three walking trials at a self-selected speed on the 10 m walkway. Two iPhones (iPhone 15 Pro Max and iPhone SE2) were mounted on 1.5 m-height tripods at the end of the walkway (spaced 3 m apart and inclined at 5 degrees) and recorded the videos for OpenCap. The stride length, step width, gait speed, cadence, single and double support time percentages, and lower extremity joint range of motion (ROM) were kinematic outcomes for analysis. The Shapiro-Wilk test was used to determine the normal distribution. Aligned rank transform (ART) ANOVA and post hoc Tukey adjustments were used to determine age and gender effects and age x gender interactions. Statistical significance was set at p 0.05.

Results:

The results showed significant age-related decreases in pelvis sagittal ROM  (F=15.46, p 0.00), hip sagittal ROM (F=11.96, p0.00), and knee sagittal ROM (F=24.13, p0.00) compared to the young controls; A most significant age x gender interaction was found in pelvis transverse ROM (F=15.78, p 0.00), and post hoc result revealed the most crucial difference in the young male group (23.22 ° ± 8.88°) versus the old male group ( 10.72 ° ± 4.00°, p 0.00).

Although the gait speed was similar between the groups, the elderly groups showed the age-related extended single support time percentage (F=81.25, p 0.00) and shorter double support time percentage (F=81.25, p 0.00), suggesting compensatory mechanisms to maintain stability.

Conclusion(s):

OpenCap effectively quantified age-related gait alterations. This confirms the feasibility of using OpenCap for quantitative gait analysis in elderly populations.

Implications:

AI-based Markerless Motion Capture systems (i.e., OpenCap) may improve access to quantitative gait assessments for elderly populations. It would help clinical staff facilitate the detection of gait abnormalities and the promptness of interventions for elderly populations.

Funding acknowledgements:
This work was unfunded.
Keywords:
Markerless Motion Capture Systems
Quantify Gait Analysis
OpenCap
Primary topic:
Innovative technology: information management, big data and artificial intelligence
Second topic:
Older people
Third topic:
Health promotion and wellbeing/healthy ageing/physical activity
Did this work require ethics approval?:
Yes
Name the institution and ethics committee that approved your work:
Research Ethics Committee, Hualien Tzu Chi Hospital, Buddhist Tzu Chi Foundation
Provide the ethics approval number:
IRB110-084-A
Has any of this material been/due to be published or presented at another national or international conference prior to the World Physiotherapy Congress 2025?:
No

Back to the listing