Hand Pose Estimation by Fusion of Inertial and Magnetic Sensing Aided by a Permanent Magnet

Kortier, H.G.; Antonsson, Jacob; Schepers, H. Martin; Gustafsson, Fredrik; Veltink, Petrus H.

doi:10.1109/tnsre.2014.2357579

Cited by 43 publications

(25 citation statements)

References 29 publications

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“…The applications include walking speed estimation [1], hand pose and kinematics estimation [2,3], knee-joint kinematics [4] and daily-life activity assessment [5]. Generally, a typical magnetic/inertial measurement unit (MIMU) consists of a tri-axial accelerometer, a tri-axial gyroscope and a tri-axial magnetometer.…”

Section: Introductionmentioning

confidence: 99%

An Adaptive Orientation Estimation Method for Magnetic and Inertial Sensors in the Presence of Magnetic Disturbances

Fan

Wang

et al. 2017

Sensors

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Magnetic and inertial sensors have been widely used to estimate the orientation of human segments due to their low cost, compact size and light weight. However, the accuracy of the estimated orientation is easily affected by external factors, especially when the sensor is used in an environment with magnetic disturbances. In this paper, we propose an adaptive method to improve the accuracy of orientation estimations in the presence of magnetic disturbances. The method is based on existing gradient descent algorithms, and it is performed prior to sensor fusion algorithms. The proposed method includes stationary state detection and magnetic disturbance severity determination. The stationary state detection makes this method immune to magnetic disturbances in stationary state, while the magnetic disturbance severity determination helps to determine the credibility of magnetometer data under dynamic conditions, so as to mitigate the negative effect of the magnetic disturbances. The proposed method was validated through experiments performed on a customized three-axis instrumented gimbal with known orientations. The error of the proposed method and the original gradient descent algorithms were calculated and compared. Experimental results demonstrate that in stationary state, the proposed method is completely immune to magnetic disturbances, and in dynamic conditions, the error caused by magnetic disturbance is reduced by 51.2% compared with original MIMU gradient descent algorithm.

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Section: Introductionmentioning

confidence: 99%

An Adaptive Orientation Estimation Method for Magnetic and Inertial Sensors in the Presence of Magnetic Disturbances

Fan

Wang

et al. 2017

Sensors

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“…Finally, in 2015 Kortier et al [22] explored a system for tracking neodymium magnet paired with accelerometer and gyroscope with respect to array of four magnetometers in parallel with inertial sensor.…”

Section: Introductionmentioning

confidence: 99%

Position tracking using inertial and magnetic sensing aided by permanent magnet

Meina

Rykaczewski

Rutkowski

2016

Annals of Computer Science and Information Systems

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Abstract-This paper describes a method for spatial tracking of a strapdown device that can be used for design of humancomputer interfaces. Inertial Measurement Unit (IMU) is used to obtain 6-dof position exploiting the so-called ZUPT technique by the means of the Kalman Filter. Additional corrections of position are done using magnetometer readings in the presence of static magnetic field induced by permanent magnet that overshadow geomagnetic field. This correction allows us to overcome drifting errors of integration of IMU readings. We have also presented comparisons of different models for magnetic field reconstruction that is crucial for this system.

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“…Disadvantage is the relatively large size and weight of the magnetic source (21 cm diameter, 11 cm height, 450 g), making it unsuitable for placing it on a foot. More recently, Kortier et al [34] presented a method to estimate the relative position and orientation of a permanent magnet placed on the hand, with respect to four magnetometers placed at the trunk. Although in the presented method a small magnet is used (2 mm radius and 7 mm length), to cover distances over 70 cm the magnet needs to be larger (the field strength decreases cubically with distance) or more then four magnetometers, rigidly attached to each other, are needed.…”

Section: Problem Descriptionmentioning

confidence: 99%

“…Disadvantage of the systems they presented is the need for stationary transmitters or receivers on the floor. Alternatively, the magnetic method of Kortier et al [34], as described in section 1.2, could be used for estimating relative foot positions. However, it should be noted that magnetic fields could be disturbed by ferromagnetic materials, which are often present in the floor.…”

Section: Relative Foot Position and Orientation Estimation And Balancmentioning

confidence: 99%

Click-on-and-Play human motion capture using wearable sensors

Weenk¹

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SummaryHuman motion capture is often used in rehabilitation clinics for diagnostics and monitoring the effects of treatment. Traditionally, camera based systems are used. However, with these systems the measurements are restricted to a lab with expensive cameras. Motion capture outside a lab, using inertial sensors, is becoming increasingly popular to obtain insight in daily-life activity patterns.There are two main disadvantages of inertial sensor systems. Preparing the measurement system is often a complex and time consuming task. Moreover, it is prone to errors, because each sensor has to be attached to a predefined body segment. Another disadvantage is that inertial sensors cannot measure relative segment positions directly. Especially relative foot positions are very important to be estimated. Together with the center of mass, these positions can be used to assess the balance of a subject. From these two main disadvantages, the goal of this thesis was derived: Contribute to the development of a click-onand-play human motion capture system. This should be a system in which the user attaches (clicks) the sensors to the body segments and can start measuring (play) immediately. Therefore, the following sub-goals were defined. The first goal is to develop an algorithm for the automatic identification of the body segments to which inertial sensors are attached. The second goal is to develop a new sensor system, with a minimal number of sensors, for the estimation of relative foot positions and orientations and the assessment of balance during gait.The first goal is addressed in chapters 2 and 3. Chapter 2 presents a method for the automatic identification of body segments on which inertial sensors are positioned. This identification is performed on the basis of a walking trial, assuming the use of a known sensor configuration. Using this method it is possible to distinguish left and right segments. Cross correlations of signals from different measurement units were used and the features were ranked. A decision tree was used for classification of the body segments. When using a full-body configuration (17 different sensor locations), 97.5% of the sensors were correctly classified. Chapter 3 presents a method that identifies the location of a sensor, without making assumptions about the applied sensor configuration or the activity the user is performing. For a full-body configuration 83.3% of the sensor locations were correctly classified. Subsequently, for each sensor location a model was developed for activity classification, resulting in a maximum vii accuracy of 91.7%.The second goal is addressed in the chapters 4, 5 and 6. In chapter 4, ultrasound time of flight is used to estimate the distance between the feet. This system was validated using an optical reference and showed an average error in distance estimation of 7.0 mm. In chapter 5, 3D relative foot positions are estimated by fusing ultrasound and inertial sensor data measured on the shoes in an extended Kalman filter.Step lengths and step widths were ca...

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Hand Pose Estimation by Fusion of Inertial and Magnetic Sensing Aided by a Permanent Magnet

Cited by 43 publications

References 29 publications

An Adaptive Orientation Estimation Method for Magnetic and Inertial Sensors in the Presence of Magnetic Disturbances

An Adaptive Orientation Estimation Method for Magnetic and Inertial Sensors in the Presence of Magnetic Disturbances

Position tracking using inertial and magnetic sensing aided by permanent magnet

Click-on-and-Play human motion capture using wearable sensors

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