A Wearable Hand Rehabilitation System With Soft Gloves

Chen, Xiaoshi; Gong, Li; Wei, Liang; Yeh, Shih-Ching; Xu, Li Da; Zheng, Lirong; Zou, Zhuo

doi:10.1109/tii.2020.3010369

Cited by 130 publications

(77 citation statements)

References 47 publications

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“…This is potentially a consequence of the added uncertainty and complexity involved with grasping, reaching, and lifting tasks compared to the relatively consistent motions seen in walking and running. In addition to the force or pressure sensors used to determine the force of a cable or pressure of a fluid within a textile pouch, researchers have begun to employ additional sensors to estimate the position of the limb, [ 14,20,69,70 ] acquire environmental cues, [ 5 ] obtain wearer inputs, [ 53,71 ] and detect intent. [ 20,72,73 ] For these applications, textiles have been used as a substrate to hold IMUs to obtain the position of the arm.…”

Section: Applications For Textile‐based Wearable Robotsmentioning

confidence: 99%

Textile Technology for Soft Robotic and Autonomous Garments

Sánchez¹,

Walsh²,

Wood³

2020

Adv Funct Materials

178

123

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Textiles have emerged as a promising class of materials for developing wearable robots that move and feel like everyday clothing. Textiles represent a favorable material platform for wearable robots due to their flexibility, low weight, breathability, and soft hand‐feel. Textiles also offer a unique level of programmability because of their inherent hierarchical nature, enabling researchers to modify and tune properties at several interdependent material scales. With these advantages and capabilities in mind, roboticists have begun to use textiles, not simply as substrates, but as functional components that program actuation and sensing. In parallel, materials scientists are developing new materials that respond to thermal, electrical, and hygroscopic stimuli by leveraging textile structures for function. Although textiles are one of humankind's oldest technologies, materials scientists and roboticists are just beginning to tap into their potential. This review provides a textile‐centric survey of the current state of the art in wearable robotic garments and highlights metrics that will guide materials development. Recent advances in textile materials for robotic components (i.e., as sensors, actuators, and integration components) are described with a focus on how these materials and technologies set the stage for wearable robots programmed at the material level.

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Section: Applications For Textile‐based Wearable Robotsmentioning

confidence: 99%

Textile Technology for Soft Robotic and Autonomous Garments

Sánchez¹,

Walsh²,

Wood³

2020

Adv Funct Materials

178

123

View full text Add to dashboard Cite

show abstract

“…Recognition of hand gestures has been studied using wearable sensors (bending and force sensors) and SVM, kNN and DT methods. SVM achieved the highest recognition accuracy in real-time mode, although it required the longest training and prediction time compared to kNN and DT methods [77]. SVM has also outperformed kNN, logistic regression and RF methods for recognition of grip action from an assistive tactile arm brace (TAB) worn on the forearm of participants [78].…”

Section: Traditional Machine Learning Methodsmentioning

confidence: 99%

Wearable Assistive Robotics: A Perspective on Current Challenges and Future Trends

Martinez-Hernandez

Metcalfe

Assaf

et al. 2021

Sensors

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Wearable assistive robotics is an emerging technology with the potential to assist humans with sensorimotor impairments to perform daily activities. This assistance enables individuals to be physically and socially active, perform activities independently, and recover quality of life. These benefits to society have motivated the study of several robotic approaches, developing systems ranging from rigid to soft robots with single and multimodal sensing, heuristics and machine learning methods, and from manual to autonomous control for assistance of the upper and lower limbs. This type of wearable robotic technology, being in direct contact and interaction with the body, needs to comply with a variety of requirements to make the system and assistance efficient, safe and usable on a daily basis by the individual. This paper presents a brief review of the progress achieved in recent years, the current challenges and trends for the design and deployment of wearable assistive robotics including the clinical and user need, material and sensing technology, machine learning methods for perception and control, adaptability and acceptability, datasets and standards, and translation from lab to the real world.

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“…As described in [ 1 ], “hand movement data acquisition is used in many engineering applications”. The use of sensory gloves has been considered for many purposes, such as sign language recognition [ 2 , 3 ], hand posture monitoring [ 4 , 5 ], computer-generated (typically virtual reality or augmented vision) environments [ 6 ], tactile sensing [ 7 , 8 , 9 , 10 ], force-sensing for biomedical purposes [ 11 , 12 , 13 ], fitness exercises tracking [ 14 ], Sensing Finger Tapping in Piano Playing [ 15 ], teleoperation [ 16 ], rehabilitation [ 17 , 18 , 19 ] and many others. However, the use of convolutional neural networks (CNNs) to provide intelligence to these gloves is indeed a significant improvement in the recognition capacity of these devices.…”

Section: Related Workmentioning

confidence: 99%

Smart System with Artificial Intelligence for Sensory Gloves

Cerro¹,

Latasa²,

Guerra³

et al. 2021

Sensors

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This paper presents a new sensory system based on advanced algorithms and machine learning techniques that provides sensory gloves with the ability to ensure real-time connection of all connectors in the cabling of a cockpit module. Besides a microphone, the sensory glove also includes a gyroscope and three accelerometers that provide valuable information to allow the selection of the appropriate signal time windows recorded by the microphone of the glove. These signal time windows are subsequently analyzed by a convolutional neural network, which indicates whether the connection of the components has been made correctly or not. The development of the system, its implementation in a production industry environment and the results obtained are analyzed.

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A Wearable Hand Rehabilitation System With Soft Gloves

Cited by 130 publications

References 47 publications

Textile Technology for Soft Robotic and Autonomous Garments

Textile Technology for Soft Robotic and Autonomous Garments

Wearable Assistive Robotics: A Perspective on Current Challenges and Future Trends

Smart System with Artificial Intelligence for Sensory Gloves

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