Measuring orientation of human body segments using miniature gyroscopes and accelerometers

By Henk Luinge, P. H. Veltink. Medical and Biological Engineering and Computing, 2005

657 citations recorded by the source corpus.

Subfields: Aerospace Engineering, Biomedical Engineering, Physical Therapy, Sports Therapy and Rehabilitation

View Paper: https://www.semanticscholar.org/paper/12f372239ddeac649535448d93622ab5991e728a

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In Aerospace Engineering

In Biomedical Engineering

In Physical Therapy, Sports Therapy and Rehabilitation

Citations in the corpus

Survey of Motion Tracking Methods Based on Inertial Sensors: A Focus on Upper Limb Human Motion (2017, methodology): “More than a decade ago, Luinge and Veltink in [95] exploited IMUs to track the orientation of the upper limbs by modelling the accelerometer and gyroscope measurements as a function of attitude, biases and noises and using a KF to estimate orientation errors and biases based on these models.”
Trends Supporting the In-Field Use of Wearable Inertial Sensors for Sport Performance Evaluation: A Systematic Review (2018, positive): “Therefore, to improve the accuracy of 2D orientation estimation, gyroscopes and accelerometers are commonly combined in an Inertial Measurement Unit (IMU) [22,23], where the term “inertial” is used because both sensors exploit the principle of inertia to provide either angular velocities or accelera”
An efficient orientation filter for inertial and inertial / magnetic sensor arrays (2010, background): “They can be complicated to implement which is reflected by the numerous solutions seen in the subject literature [3, 4, 15, 16, 17, 24, 25, 26, 27, 28, 29, 30, 31, 32].”
Complementary Observer for Body Segments Motion Capturing by Inertial and Magnetic Sensors (2014, positive): “In [2] and [14], the authors describe an attitude estimation algorithm based on a three-axis gyroscope and three-axis accelerometer data.”
Accelerometry: a technique for quantifying movement patterns during walking. (2008, background): “However, concurrent data collection with rate gyroscopes can provide added detail on the orientation of the accelerometer [14–19], and thus enhances the possibility of correcting for the effects of gravity.”
Full body gait analysis with Kinect (2012, background): “Sensors must be placed correctly and securely [12], and must account for gravity, noise and signal drift [13].”
Activity identification using body-mounted sensors—a review of classification techniques (2009, methodology): “…been proposed to overcome this problem including the use of a state estimator with input from a tri-axial gyroscope and a tri-axial accelerometer (Luinge and Veltink 2005) and the use of wavelet analysis (Section 4.4) to remove both drift and high frequency noise from gyroscope signals (Najafi…”
IMU-Based Joint Angle Measurement for Gait Analysis (2014, methodology): “The drift in the inclination part of the IMU’s orientation is eliminated using the assumption that the measured acceleration is dominated by gravitational acceleration [4].”
Compensation of magnetic disturbances improves inertial and magnetic sensing of human body segment orientation (2005, methodology): “The Vicon system was considered to have an accuracy of 1 rms [29], [30].”
Wearable soft sensing suit for human gait measurement (2014, background): “A common approach to body-worn sensors is through the use of inertial measurement units (IMUs) (Giansanti et al., 2003; Luinge and Veltink, 2005), but these sensors require extensive filtering (Yun and Bachmann, 2006) or sensor fusion with external systems (Tao et al., 2007) to eliminate…”
Using Inertial Sensors for Position and Orientation Estimation (2017, neutral): “6 1.3 Tutorial content and its outline . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7”
Estimation of IMU and MARG orientation using a gradient descent algorithm (2011, background): “They can be complicated to implement which is reflected by the numerous solutions seen in the subject literature [2], [10], [11], [12], [19], [20], [21], [22], [23].”