Sensor Glove Based on Novel Inertial Sensor Fusion Control Algorithm for 3-D Real-Time Hand Gestures Measurements

In recent years, there has been an increasing interest in hand movements in various application fields. However, the human hand is too dexterous and only has limited space. Developing a proper method to monitor and capture hand motion is meaningful. Conventionally, an optical measurement method is w...

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Published in:	IEEE transactions on industrial electronics (1982) Vol. 67; no. 1; pp. 658 - 666
Main Authors:	Chang, Hsien-Ting, Chang, Jen-Yuan
Format:	Journal Article
Language:	English
Published:	New York IEEE 01.01.2020 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects:	Acceleration Accelerometers Algorithms Angular speed attitude heading reference system (AHRS) Control algorithms Control theory Feedback control Field strength Gyroscopes IIR filters inertial measurement unit (IMU) Inertial platforms Inertial sensing devices Magnetic field measurement Magnetic shielding Magnetometers Mathematical analysis motion capture Optical measurement Quaternions Sensor fusion Sensors wearable sensors
ISSN:	0278-0046, 1557-9948
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Abstract	In recent years, there has been an increasing interest in hand movements in various application fields. However, the human hand is too dexterous and only has limited space. Developing a proper method to monitor and capture hand motion is meaningful. Conventionally, an optical measurement method is widely used to capture hand gestures. Nevertheless, this method is costly and has the problem of line-of-sight shielding. In this paper, a sensor fusion algorithm is proposed to calculate a more accurate result by calculating acceleration, magnetic field strength, and angular speed from the inertial measurement unit (IMU). The core concept of this algorithm is based on the idea of feedback control. To validate the performance, the active rotary platform is set up to compare the measured results to the references directly. Most of the error results are less than 3°, and the standard deviations are less than 1°. The measurement results ensure the feasibility of the inertial measurement method with the sensor fusion algorithm proposed in this paper.
AbstractList	In recent years, there has been an increasing interest in hand movements in various application fields. However, the human hand is too dexterous and only has limited space. Developing a proper method to monitor and capture hand motion is meaningful. Conventionally, an optical measurement method is widely used to capture hand gestures. Nevertheless, this method is costly and has the problem of line-of-sight shielding. In this paper, a sensor fusion algorithm is proposed to calculate a more accurate result by calculating acceleration, magnetic field strength, and angular speed from the inertial measurement unit (IMU). The core concept of this algorithm is based on the idea of feedback control. To validate the performance, the active rotary platform is set up to compare the measured results to the references directly. Most of the error results are less than 3°, and the standard deviations are less than 1°. The measurement results ensure the feasibility of the inertial measurement method with the sensor fusion algorithm proposed in this paper.
Author	Chang, Jen-Yuan Chang, Hsien-Ting
Author_xml	– sequence: 1 givenname: Hsien-Ting surname: Chang fullname: Chang, Hsien-Ting email: htchang@gapp.nthu.edu.tw organization: Department of Power Mechanical Engineering, National Tsing Hua University, Hsinchu, Taiwan – sequence: 2 givenname: Jen-Yuan surname: Chang fullname: Chang, Jen-Yuan email: jychang@pme.nthu.edu.tw organization: Department of Power Mechanical Engineering, National Tsing Hua University, Hsinchu, Taiwan
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SubjectTerms	Acceleration Accelerometers Algorithms Angular speed attitude heading reference system (AHRS) Control algorithms Control theory Feedback control Field strength Gyroscopes IIR filters inertial measurement unit (IMU) Inertial platforms Inertial sensing devices Magnetic field measurement Magnetic shielding Magnetometers Mathematical analysis motion capture Optical measurement Quaternions Sensor fusion Sensors wearable sensors
Title	Sensor Glove Based on Novel Inertial Sensor Fusion Control Algorithm for 3-D Real-Time Hand Gestures Measurements
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