Velocity and acceleration analysis from kinematics linear punch using optical motion capture

Dharmayanti,; Suhendra, Adang; Mutiara, Achmad Benny

doi:10.1109/iac.2017.8280581

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Cited by 2 publications

(2 citation statements)

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“…In sports science, athletes, trainers and scientists utilise MOCAP systems to analyse a particular motion and identify errors and improvements in the execution of the technique [26] [27] [28]. Furthermore, MOCAP systems are utilised to pre-determine and prevent risks and possible injuries due to incorrect execution of the technique [28].…”

Section: Background and Motivation To The Studymentioning

confidence: 99%

Kinematic State Estimation Using Multiple DGPS/MEMS-IMU Sensors

Patel

2020

IEEE Sens. Lett.

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Section: Background and Motivation To The Studymentioning

confidence: 99%

Kinematic State Estimation Using Multiple DGPS/MEMS-IMU Sensors

Patel

2020

IEEE Sens. Lett.

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“…Optical motion capture based on image information is currently the most popular method for acquiring motion data in biomechanics applications [8][9][10][11]. However, it also has many problems, such as the marker blockage and unnecessary reflections [12], which will have a great impact on the accuracy of the experiment.…”

Section: Introductionmentioning

confidence: 99%

Human joint pose estimation based on the Kalman filter

Wang

Zhao²

2022

Second International Conference on Advanced Algorithms and Signal Image Processing (AASIP 2022)

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With the development of Internet of Things(IoT) and artificial intelligence, people's demand for location-based services is increasingly urgent. Aim at recognize human lower limb posture accurately, posture recognition based on image information and sensor information such as magnetometer, accelerometer, and rate gyro, MARG sensors, has been the research hot spot. However, the image methods require higher computing resources and will be affected by environmental factors such as fiber optics, shading, etc; the sensor methods have low accuracy with traditional arithmetic. Kalman filter and Attitude and Heading Reference System(AHRS) is used to extract accurate posture information from sensors' raw data. The corresponding testing platform is set up based on MPU9250, which is a typical and low-cost motion tracking integrating circuit (IC) of MARG sensors and a ZigBee wireless communication module called E18-MS1-PCB.

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Velocity and acceleration analysis from kinematics linear punch using optical motion capture

Cited by 2 publications

References 11 publications

Kinematic State Estimation Using Multiple DGPS/MEMS-IMU Sensors

Kinematic State Estimation Using Multiple DGPS/MEMS-IMU Sensors

Human joint pose estimation based on the Kalman filter

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