Object recognition in performed basic daily activities with a handcrafted data glove prototype

Maître, Julien; Rendu, Clément; Bouchard, Kévin; Bouchard, Bruno; Gaboury, Sébastien

doi:10.1016/j.patrec.2021.04.017

Cited by 13 publications

(5 citation statements)

References 26 publications

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“…The highest test classification accuracy achieved by our system is 99.7%. Maitre et al [ 146 , 147 ] proposed a new prototype of a data glove that is simple, cheap, reproducible, and efficient (∼100% correct predictions) for object recognition by abstracting the entire theory of gesture recognition. In real life, such a device could be very useful to monitor the evolution of hand dysfunction in Alzheimer’s disease.…”

Section: Application Of Flexible Sensor Technology To Manipulator Con...mentioning

confidence: 99%

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Manipulator Control System Based on Flexible Sensor Technology

Chen,

Wang,

Chen

et al. 2023

Micromachines

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The research on the remote control of manipulators based on flexible sensor technology is gradually extensive. In order to achieve stable, accurate, and efficient control of the manipulator, it is necessary to reasonably design the structure of the sensor with excellent tensile strength and flexibility. The acquisition of manual information by high-performance sensors is the basis of manipulator control. This paper starts with the manufacturing of materials of the flexible sensor for the manipulator, introduces the substrate, sensor, and flexible electrode materials, respectively, and summarizes the performance of different flexible sensors. From the perspective of manufacturing, it introduces their basic principles and compares their advantages and disadvantages. Then, according to the different ways of wearing, the two control methods of data glove control and surface EMG control are respectively introduced, the principle, control process, and detection accuracy are summarized, and the problems of material microstructure, reducing the cost, optimizing the circuit design and so on are emphasized in this field. Finally, the commercial application in this field is explained and the future research direction is proposed from two aspects: how to ensure real-time control and better receive the feedback signal from the manipulator.

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Section: Application Of Flexible Sensor Technology To Manipulator Con...mentioning

confidence: 99%

“…( b ) reprinted from [ 144 ], copyright (2023), with permission from Elsevier. ( c ) reprinted from [ 147 ], copyright (2021), with permission from Elsevier. ( d ) reprinted from [ 152 ], copyright (2019), with permission from Sensors.…”

Section: Figurementioning

confidence: 99%

Manipulator Control System Based on Flexible Sensor Technology

Chen,

Wang,

Chen

et al. 2023

Micromachines

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“…If the angle data would directly calculated from the acceleration data by using Kinematics, there would be a problem due to poor dynamic accuracy because the dynamic data of an accelerometer are not accurate when an object moves, but the advantage is that there is no long-term drift or error accumulation [ 31 ]. Dynamically and precisely measuring a three-axis attitude angle is possible by integrating the angular velocity obtained with a gyroscope, but the disadvantage is that error accumulation and drift occur, and the accumulated error increases with time.…”

Section: Data Calibrationmentioning

confidence: 99%

Master–Slave Control System for Virtual–Physical Interactions Using Hands

Liu

Sun

2023

Sensors

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Among the existing technologies for hand protection, master–slave control technology has been extensively researched and applied within the field of safety engineering to mitigate the occurrence of safety incidents. However, it has been identified through research that traditional master–slave control technologies no longer meet current production and lifestyle needs, and they have even begun to pose new safety risks. To resolve the safety risks exposed by traditional master–slave control, this research fuses master–slave control technology for hands with virtual reality technology, and the design of a master–slave control system for hands based on virtual reality technology is investigated. This study aims to realize the design of a master–slave control system for virtual–physical interactions using hands that captures the position, orientation, and finger joint angles of the user’s hand in real time and synchronizes the motion of the slave interactive device with that of a virtual hand. With amplitude limiting, jitter elimination, and a complementary filtering algorithm, the original motion data collected by the designed glove are turned into a Kalman-filtering-algorithm-based driving database, which drives the synchronous interaction of the virtual hand and a mechanical hand. As for the experimental results, the output data for the roll, pitch, and yaw were in the stable ranges of −0.1° to 0.1°, −0.15° to 0.15°, and −0.15° to 0.15°, respectively, which met the accuracy requirements for the system’s operation under different conditions. More importantly, these data prove that, in terms of accuracy and denoising, the data-processing algorithm was relatively compatible with the hardware platform of the system. Based on the algorithm for the virtual–physical interaction model, the authors introduced the concept of an auxiliary hand into the research, put forward an algorithmic process and a judgement condition for the stable grasp of the virtual hand’s, and solved a model-penetrating problem while enhancing the immersive experience during virtual–physical interactions. In an interactive experiment, a dynamic accuracy test was run on the system. As shown by the experimental data and the interactive effect, the system was satisfactorily stable and interactive.

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“…Data gloves are one of the most commonly used wearable devices in VR. The gesture recognition based on wearable devices involve collecting finger posture data, extracting spatiotemporal parameters, selecting effective parameters, and model training [17] or identification by an intelligent algorithm [18]. The gesture recognition based on touch technology can be further divided into single touch and multitouch recognition.…”

Section: Gesture Interactions and Recognition In Virtual Realitymentioning

confidence: 99%

Using Machine Learning Algorithms to Predict Failure on the Pcb Surface Under Corrosive Conditions

Bahrebar,

Homayoun,

Ambat

2022

SSRN Journal

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Object recognition in performed basic daily activities with a handcrafted data glove prototype

Cited by 13 publications

References 26 publications

Manipulator Control System Based on Flexible Sensor Technology

Manipulator Control System Based on Flexible Sensor Technology

Master–Slave Control System for Virtual–Physical Interactions Using Hands

Using Machine Learning Algorithms to Predict Failure on the Pcb Surface Under Corrosive Conditions

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