ArticleMicromachines2021
Development of a Low-Cost Wearable Data Glove for Capturing Finger Joint Angles.
Article in Micromachines, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
8 citing papers in PubMed.
- Article
- Quasi-Static and Dynamic Measurement Capabilities Provided by an Electromagnetic Field-Based Sensory Glove.Biosensors · 2025Article
- Machine Learning-Based Gesture Recognition Glove: Design and Implementation.Sensors (Basel, Switzerland) · 2024Article
- Manipulator Control System Based on Flexible Sensor Technology.Micromachines · 2023Review
- A Novel Human Intention Prediction Approach Based on Fuzzy Rules through Wearable Sensing in Human-Robot Handover.Biomimetics (Basel, Switzerland) · 2023Article
- Dynamic Analysis and Experimental Study of Lasso Transmission for Hand Rehabilitation Robot.Micromachines · 2023Article
- Data glove-based gesture recognition using CNN-BiLSTM model with attention mechanism.PloS one · 2023Article
- Interactive Application of Data Glove Based on Emotion Recognition and Judgment System.Sensors (Basel, Switzerland) · 2022Article
Corrections and comments
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Authors and funding
9 authors.
Funding
Abstract
Capturing finger joint angle information has important applications in human-computer interaction and hand function evaluation. In this paper, a novel wearable data glove is proposed for capturing finger joint angles. A sensing unit based on a grating strip and an optical detector is specially designed for finger joint angle measurement. To measure the angles of finger joints, 14 sensing units are arranged on the back of the glove. There is a sensing unit on the back of each of the middle phalange, proximal phalange, and metacarpal of each finger, except for the thumb. For the thumb, two sensing units are distributed on the back of the proximal phalange and metacarpal, respectively. Sensing unit response tests and calibration experiments are conducted to evaluate the feasibility of using the designed sensing unit for finger joint measurement. Experimental results of calibration show that the comprehensive precision of measuring the joint angle of a wooden finger model is 1.67%. Grasping tests and static digital gesture recognition experiments are conducted to evaluate the performance of the designed glove. We achieve a recognition accuracy of 99% by using the designed glove and a generalized regression neural network (GRNN). These preliminary experimental results indicate that the designed data glove is effective in capturing finger joint angles.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.