No clue.
B-Spline Modeling of Inertial Measurements for Evaluating Stroke Rehabilitation Effectiveness
Yi-Ting Hwang, Yu-Qian Tung, Chun-Shu Chen, and Bor-Shing Lin, Senior Member, IEEE
Abstract— Patients who experience upper-limb paralysis
after stroke require continual rehabilitation. Rehabilitation
must be evaluated for appropriate treatment adjustment;
such evaluation can be performed using inertial measure-
ment units (IMUs) instead of standard scales or subjective
evaluations. However, IMUs produce large quantities of dis-
cretized data, and using these data directly is challenging.
In this study, B-splines were used to estimate IMU trajectory
data for objective evaluations of hand function and stability
by using machine learning classifiers and mathematical in-
dices. IMU trajectory data from a 2018 study on upper-limb
rehabilitation were used to validate the proposed method.
Features extracted from B-spline trajectories could be used
to classify individuals in the 2018 study with high accuracy,
and the proposed indices revealed differences between
these groups. Compared with conventional rehabilitation
evaluation methods, the proposed method is more objec-
tive and effective.
Abstract— Patients who experience upper-limb paralysis
after stroke require continual rehabilitation. Rehabilitation
must be evaluated for appropriate treatment adjustment;
such evaluation can be performed using inertial measure-
ment units (IMUs) instead of standard scales or subjective
evaluations. However, IMUs produce large quantities of dis-
cretized data, and using these data directly is challenging.
In this study, B-splines were used to estimate IMU trajectory
data for objective evaluations of hand function and stability
by using machine learning classifiers and mathematical in-
dices. IMU trajectory data from a 2018 study on upper-limb
rehabilitation were used to validate the proposed method.
Features extracted from B-spline trajectories could be used
to classify individuals in the 2018 study with high accuracy,
and the proposed indices revealed differences between
these groups. Compared with conventional rehabilitation
evaluation methods, the proposed method is more objec-
tive and effective.
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