Inertial sensor based method for identifying spherical joint center of rotation

Area of Science:

• Biomechanics
• Medical Devices
• Robotics

Background:

• Estimating the center-of-rotation (CoR) for ball/spherical joints is crucial in biomechanics and robotics.
• Existing methods for CoR estimation using inertial measurement units (IMUs) often rely on velocity and position estimations, which can be prone to errors.
• There is a need for rapid, accurate, and non-invasive methods for CoR determination in diverse settings.

Purpose of the Study:

• To develop and validate a novel algorithm for rapid and accurate prediction of the center-of-rotation (CoR) in ball/spherical joints using miniaturized wireless inertial measurement unit (IMU) technology.
• To improve upon existing IMU-based CoR estimation techniques by directly utilizing acceleration and angular velocity data.
• To assess the accuracy of the proposed method compared to precision measurement equipment.

Main Methods:

• Development of a new algorithm that directly processes acceleration and angular velocity data from a miniaturized wireless IMU.
• Implementation of the algorithm to predict the CoR of ball/spherical joints.
• Validation of the predicted CoR against measurements obtained from a precision coordinate measuring machine.

Main Results:

• The proposed IMU-based algorithm accurately predicts the CoR of ball/spherical joints.
• The method resolves the CoR position within a 3mm sphere of the true CoR, as verified by a precision coordinate measuring machine.
• The algorithm avoids the need for potentially error-prone velocity and position estimations inherent in other IMU-based approaches.

Conclusions:

• The developed IMU technology and algorithm offer a significant advancement in the rapid and accurate prediction of joint CoR.
• The high accuracy achieved makes this method suitable for broad application in field, laboratory, and clinical settings.
• This non-invasive technique provides a valuable tool for applications requiring precise joint CoR estimation.