2014
DOI: 10.1109/tmech.2013.2240312
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Human Hand Motion Analysis With Multisensory Information

Abstract: In order to study and analyse human hand motions which contain multimodal information, a generalised framework integrating multiple sensors is proposed and consists of modules of sensor integration, signal preprocessing, correlation study of sensory information and motion identification. Three types of sensors are integrated to simultaneously capture the finger angle trajectories, the hand contact forces and the forearm electromyography (EMG) signals. To facilitate the rapid acquisition of human hand tasks, me… Show more

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Cited by 104 publications
(56 citation statements)
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“…Arkenbout et al [18] researched an immersive hand motion control method incorporating the Kinect-based Nimble VR system using a fifth dimension technologies (5DT) data glove and a Kalman filter. Furthermore, studies [19][20][21][22] on various approaches for analyzing motion by capturing the human hand have been carried out, including a study on articulated hand motion and graphic presentation of data generated from the interaction between objects in certain time intervals [23]. These studies enable users to interact more directly in a virtual environment, but research has not yet been developed into a VR system.…”
Section: Related Workmentioning
confidence: 99%
“…Arkenbout et al [18] researched an immersive hand motion control method incorporating the Kinect-based Nimble VR system using a fifth dimension technologies (5DT) data glove and a Kalman filter. Furthermore, studies [19][20][21][22] on various approaches for analyzing motion by capturing the human hand have been carried out, including a study on articulated hand motion and graphic presentation of data generated from the interaction between objects in certain time intervals [23]. These studies enable users to interact more directly in a virtual environment, but research has not yet been developed into a VR system.…”
Section: Related Workmentioning
confidence: 99%
“…It has been extensively demonstrated that user's motion intention can be accurately detected by surface electromyographic recordings (sEMG) [4]. Different sEMG-based systems were proposed for the estimation of hand and wrist movements, and consequently used as noninvasive interfaces for controlling exoskeletons [5,6], prosthetic devices [7][8][9], computer-animated hands in a virtual environment [10], or for teleoperating robotic arms [9,11]. The previous studies focused on the investigation of discrete classifications of wrist abduction/adduction [9,11], flexion/extension [7,10,12,13] as well as of a different combination of finger motions [9,11,14].…”
Section: Introductionmentioning
confidence: 99%
“…The discrepancy between MCP H X and MCP h shown in Fig. 13(a) is quite small (a few decimals of millimeter) and repetitive along all trials, meaning that the formulation (12) used for the calculation of the two MCP positions is consistent with the device. Other subjects showed similar results.…”
Section: Resultsmentioning
confidence: 94%