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Related Experiment Video

Updated: Jul 16, 2026

An Inertial Measurement Unit Based Method to Estimate Hip and Knee Joint Kinematics in Team Sport Athletes on the Field

An Inertial Measurement Unit Based Method to Estimate Hip and Knee Joint Kinematics in Team Sport Athletes on the Field

Published on: May 26, 2020

IMU Error Propagation in Position Reconstruction and Its Mitigation Through Task-Informed Dual-IMU Constrained

Rachele Rossanigo¹, Diletta Balta¹, Niccolò Tortarolo¹

¹Department of Electronics and Telecommunications, Politecnico di Torino, 10129 Torino, Italy.

Sensors (Basel, Switzerland)

|July 15, 2026

Summary

This study introduces a new Constrained Redundant Optimization Pipeline (CROP) for golf putting analysis using inertial measurement units (IMUs). CROP significantly improves putter trajectory reconstruction accuracy by reducing errors.

Keywords:

IMU double integration IMU drift constrained optimization drift reduction golf putting inertial measurement units kinematic constraints orientation estimation sensor fusion trajectory reconstruction

Related Experiment Videos

Last Updated: Jul 16, 2026

An Inertial Measurement Unit Based Method to Estimate Hip and Knee Joint Kinematics in Team Sport Athletes on the Field

An Inertial Measurement Unit Based Method to Estimate Hip and Knee Joint Kinematics in Team Sport Athletes on the Field

Published on: May 26, 2020

Area of Science:

Sports Science
Biomechanics
Sensor Technology

Background:

Inertial measurement units (IMUs) offer a low-cost solution for analyzing golf putting.
However, IMU-based putter trajectory reconstruction faces limitations due to sensor errors, fusion tuning, and integration drift.

Purpose of the Study:

To analyze error propagation in standard IMU reconstruction pipelines.
To propose and evaluate a novel Constrained Redundant Optimization Pipeline (CROP) for enhanced accuracy.

Main Methods:

A standard IMU pipeline involving orientation estimation and double integration was analyzed.
The proposed CROP pipeline utilized redundant IMU data and kinematic constraints for optimization.
23 putting strokes were recorded using two IMUs and a stereophotogrammetric system.

Main Results:

CROP reduced median RMS error in velocity by approximately 40% (16.5 to 9.9 cm/s).
CROP reduced median RMS error in position by approximately 63% (23.2 to 8.5 cm).
The proposed method demonstrated reduced drift and improved trajectory reconstruction compared to standard methods.

Conclusions:

The Constrained Redundant Optimization Pipeline (CROP) significantly enhances IMU-based golf putting analysis.
The findings suggest CROP offers improved accuracy and reduced drift for trajectory reconstruction.
Further advancements are needed for precise real-world field applications.