Sen-Glove: A Lightweight Wearable Glove for Hand Assistance with Soft Joint Sensing

Deng, Linan; Shen, Yi; Yang, Hong; Dong, Yunlong; He, Xin; Yuan, Ye; Li, Zhi; Ding, Han‐Fei

doi:10.1109/icra46639.2022.9812412

Cited by 6 publications

(2 citation statements)

References 25 publications

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“…In addition, the bulky actuators on the fingers may cause interference between fingers upon actuation. In contrast, the motor-tendon driven method is much lighter, where a small motor can be connected to the fingertip via a tendon and the finger can be driven by the rotation of the motor [ 7 , 8 , 9 ]. This method has a much simpler glove design, which makes the hand-wearable part more comfortable and lighter.…”

Section: Introductionmentioning

confidence: 99%

Lightweight Soft Robotic Glove with Whole-Hand Finger Motion Tracking for Hand Rehabilitation in Virtual Reality

Li,

Chen,

Zhou

et al. 2023

Biomimetics

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Soft robotic gloves have attracted significant interest in hand rehabilitation in the past decade. However, current solutions are still heavy and lack finger-state monitoring and versatile treatment options. To address this, we present a lightweight soft robotic glove actuated by twisted string actuators (TSA) that provides whole-hand finger motion tracking. We have developed a virtual reality environment for hand rehabilitation training, allowing users to interact with various virtual objects. Fifteen small inertial measurement units are placed on the glove to predict finger joint angles and track whole-hand finger motion. We performed TSA experiments to identify design and control rules, by understanding how their response varies with input load and voltages. Grasping experiments were conducted to determine the grasping force and range of motion. Finally, we showcase an application of the rehabilitation glove in a Unity-based VR interface, which can actuate the operator’s fingers to grasp different virtual objects.

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Section: Introductionmentioning

confidence: 99%

Lightweight Soft Robotic Glove with Whole-Hand Finger Motion Tracking for Hand Rehabilitation in Virtual Reality

Li,

Chen,

Zhou

et al. 2023

Biomimetics

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“…Firstly, sensor signals exhibit extremely weak variations. For instance, recently proposed sensors made of flexible materials such as liquid metal demonstrate their potential for detecting human motion through wearable resistive strain sensors, where the change in resistance is less than 1 Ω when the finger bends [8]. Similarly, the output voltage of the wearable tactile sensor varies by only a few millivolts with changes in contact force [9].…”

Section: Introductionmentioning

confidence: 99%

Design of a Wide-Range and High-Precision Analog Front-End Circuit for Multi-Parameter Sensors

Yang

Zheng

et al. 2023

Electronics

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This article presents a wide-range and high-precision analog front-end circuit for multi-parameter sensors that can handle sensor outputs of different types (R, C, V). A rail-to-rail baseline compensation method has been proposed, which further incorporates a fine offset elimination of 0.6 mV/step. Additionally, self-zeroing and correlated double-sampling techniques are integrated to reduce low-frequency noise and offset, prevent sensor signal saturation, and enhance the precision of the analog front-end circuit. By incorporating variable components in the sensor signal acquisition circuit and integrating them with the baseline compensation circuit, the applicability range of the sensor has been expanded (R: 7 Ω–1.7 MΩ, C: 50 fF–35 pF, V: 0.05–1.7 V). Test results show all interface circuits exhibit significant total conversion gains (C: 45 mV/fF, R: 14.5 mV/Ω, V: 144 V/V), achieving high precision. Meanwhile, a coefficient of determination (R2) greater than 0.998 indicates high conversion linearity of the circuit.

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Capturing complex hand movements and object interactions using machine learning-powered stretchable smart textile gloves

Tashakori,

Jiang,

Servati

et al. 2024

Nat Mach Intell

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Sen-Glove: A Lightweight Wearable Glove for Hand Assistance with Soft Joint Sensing

Cited by 6 publications

References 25 publications

Lightweight Soft Robotic Glove with Whole-Hand Finger Motion Tracking for Hand Rehabilitation in Virtual Reality

Lightweight Soft Robotic Glove with Whole-Hand Finger Motion Tracking for Hand Rehabilitation in Virtual Reality

Design of a Wide-Range and High-Precision Analog Front-End Circuit for Multi-Parameter Sensors

Capturing complex hand movements and object interactions using machine learning-powered stretchable smart textile gloves

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