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Abstract(s)
Gait analysis (GA) is crucial for understanding age-related changes, falls and
instability in active older adults. Traditional GA methods have significant limitations,
particularly related to marker/sensor positioning, calibration and controlled environment,
prompting the exploration of alternative approaches. Therefore, there is a growing interest
in markerless (ML) analysis methods for tridimensional gait analysis (3DGA) in active
older adults.
Although the ML system seems appealing due to its ability to overcome the
limitations of other methods, the exact influence of clothing on the collected data is still
unknown. Therefore, the aim of this study is to investigate the influence of clothing on
the kinetic and kinematic data obtained from the gait of active healthy elderly individuals.
This cross-sectional observational study included thirty participants and compared
two types of clothing conditions: Minimal Clothing (MC) (tight shirt and lycra shorts)
and Self-selected Clothing (SSC) (unrestricted casual clothing) while the participants
walked back and forth in a walkway of 12m long at their desired and comfortable speed.
The main variables analyzed were lower limb joint angles and moments.
The results obtained showed almost no differences between clothing conditions. The
overall kinematic and kinetic curve patterns, across all joints and axes, were similar. The
Root Mean Squared Difference (RMSD) values ranged between 1.6º to 3.7º for joint
angles and 0.02 Nm/Kg to 0.11 Nm/Kg for joint moments, reinforcing the overall low
deviation between the clothing conditions.
In conclusion, the output of this work shows that what was thought to be a limiting
factor for this type of analysis did not prove to be one, since the results were positive and
within expectations, following previous studies, highlighting the potential of validity of
this kind of system.
Description
Keywords
Gait analysis Aging Active older adults Kinetics and Kinematics