Angle estimation of a single-axis rotation: a practical inertial-measurement-unit-based method

2017 ◽  
Vol 11 (7) ◽  
pp. 892-899 ◽  
Author(s):  
Shuaiyong Zheng ◽  
Hongxin Dong ◽  
Ruifeng Zhang ◽  
Zhigang Huang ◽  
Jiawu Wang
Keyword(s):  
Inertial Measurement Unit ◽  
Measurement Unit ◽  
Angle Estimation ◽  
Inertial Measurement ◽  
Axis Rotation ◽  
Single Axis Rotation

Error Auto-Compensation Methods of Improved Single-Axial Rotation INS

2013 ◽  
Vol 791-793 ◽  
pp. 1046-1049
Author(s):  
Guo Ping Li ◽  
Yan Bin Gao ◽  
Ting Jun Wang ◽  
Lian Wu Guan
Keyword(s):  
Inertial Measurement Unit ◽  
Inertial Navigation System ◽  
Rotation Axis ◽  
Axial Rotation ◽  
Measurement Unit ◽  
Inertial Measurement ◽  
Compensation Methods ◽  
Axis Rotation ◽  
System Errors ◽  
Single Axis Rotation

An Auto-Compensation of inertial navigation system (INS) based on improved single-axis rotation has been proposed in the paper. Inertial Measurement Unit (IMU) is tilt mounted, e.g. neither perpendicularly, nor coaxially, with the rotation axis. Analysis and derivation show that this angle arrangement of IMU can restrain the expansion of the system errors caused by IMU. Simulations demonstrated the coincidence of the theoretical analysis and the system performances

New method to evaluate three-dimensional push-off angle during short-track speed skating using wearable inertial measurement unit sensors

2019 ◽  
Vol 233 (4) ◽  
pp. 476-480 ◽  
Author(s):  
Kyungsoo Kim ◽  
Jun Seok Kim ◽  
Tserenchimed Purevsuren ◽  
Batbayar Khuyagbaatar ◽  
SuKyoung Lee ◽  
...  
Keyword(s):  
Motion Analysis ◽  
Inertial Measurement Unit ◽  
High Speed ◽  
Three Dimensional ◽  
Analysis Data ◽  
New Method ◽  
Measurement Unit ◽  
Angle Estimation ◽  
Inertial Measurement ◽  
Speed Skating

The push-off mechanism to generate forward movement in skating has been analyzed by using high-speed cameras and specially designed skates because it is closely related to skater performance. However, using high-speed cameras for such an investigation, it is hard to measure the three-dimensional push-off force, and a skate with strain gauges is difficult to implement in the real competitions. In this study, we provided a new method to evaluate the three-dimensional push-off angle in short-track speed skating based on motion analysis using a wearable motion analysis system with inertial measurement unit sensors to avoid using a special skate or specific equipment insert into the skate for measurement of push-off force. The estimated push-off angle based on motion analysis data was very close to that based on push-off force with a small root mean square difference less than 6% when using the lateral marker in the left leg and the medial marker in the right leg regardless of skating phase. These results indicated that the push-off angle estimation based on motion analysis data using a wearable motion capture system of inertial measurement unit sensors could be acceptable for realistic situations. The proposed method was shown to be feasible during short-track speed skating. This study is meaningful because it can provide a more acceptable push-off angle estimation in real competitive situations.

scholarly journals Automatically evaluating balance using machine learning and data from a single inertial measurement unit

2021 ◽  
Vol 18 (1) ◽  
Author(s):  
Fahad Kamran ◽  
Kathryn Harrold ◽  
Jonathan Zwier ◽  
Wendy Carender ◽  
Tian Bao ◽  
...  
Keyword(s):  
Machine Learning ◽  
Inertial Measurement Unit ◽  
Physical Therapists ◽  
Physical Therapist ◽  
Model Performance ◽  
Machine Learning Techniques ◽  
Measurement Unit ◽  
Balance Performance ◽  
Inertial Measurement ◽  
Self Assessments

Abstract Background Recently, machine learning techniques have been applied to data collected from inertial measurement units to automatically assess balance, but rely on hand-engineered features. We explore the utility of machine learning to automatically extract important features from inertial measurement unit data for balance assessment. Findings Ten participants with balance concerns performed multiple balance exercises in a laboratory setting while wearing an inertial measurement unit on their lower back. Physical therapists watched video recordings of participants performing the exercises and rated balance on a 5-point scale. We trained machine learning models using different representations of the unprocessed inertial measurement unit data to estimate physical therapist ratings. On a held-out test set, we compared these learned models to one another, to participants’ self-assessments of balance, and to models trained using hand-engineered features. Utilizing the unprocessed kinematic data from the inertial measurement unit provided significant improvements over both self-assessments and models using hand-engineered features (AUROC of 0.806 vs. 0.768, 0.665). Conclusions Unprocessed data from an inertial measurement unit used as input to a machine learning model produced accurate estimates of balance performance. The ability to learn from unprocessed data presents a potentially generalizable approach for assessing balance without the need for labor-intensive feature engineering, while maintaining comparable model performance.

scholarly journals Inertial Measurement Unit Sensors in Assistive Technologies for Visually Impaired People, a Review

Sensors ◽  
2021 ◽  
Vol 21 (14) ◽  
pp. 4767
Author(s):  
Karla Miriam Reyes Leiva ◽  
Milagros Jaén-Vargas ◽  
Benito Codina ◽  
José Javier Serrano Olmedo
Keyword(s):  
Inertial Measurement Unit ◽  
Visually Impaired ◽  
Inertial Sensors ◽  
Assistive Technologies ◽  
Biomechanical Analysis ◽  
Measurement Unit ◽  
Inertial Measurement ◽  
Visually Impaired People ◽  
Impaired People ◽  
Application Fields

A diverse array of assistive technologies have been developed to help Visually Impaired People (VIP) face many basic daily autonomy challenges. Inertial measurement unit sensors, on the other hand, have been used for navigation, guidance, and localization but especially for full body motion tracking due to their low cost and miniaturization, which have allowed the estimation of kinematic parameters and biomechanical analysis for different field of applications. The aim of this work was to present a comprehensive approach of assistive technologies for VIP that include inertial sensors as input, producing results on the comprehension of technical characteristics of the inertial sensors, the methodologies applied, and their specific role in each developed system. The results show that there are just a few inertial sensor-based systems. However, these sensors provide essential information when combined with optical sensors and radio signals for navigation and special application fields. The discussion includes new avenues of research, missing elements, and usability analysis, since a limitation evidenced in the selected articles is the lack of user-centered designs. Finally, regarding application fields, it has been highlighted that a gap exists in the literature regarding aids for rehabilitation and biomechanical analysis of VIP. Most of the findings are focused on navigation and obstacle detection, and this should be considered for future applications.

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