TY - JOUR
T1 - Fully Flexible Smart Gloves and Deep Learning Motion Intention Prediction for Ultralow Latency VR Interactions
AU - Li, Yang
AU - Jiang, Jiacheng
AU - Wang, Ruoqin
AU - Mao, Zanxiang
AU - Fang, Lin
AU - Qi, Yirui
AU - Zhang, Junsheng
AU - Wu, Chili
AU - Yu, Hongyu
N1 - Publisher Copyright:
© 2017 IEEE.
PY - 2023/9/1
Y1 - 2023/9/1
N2 - Most reported flexible smart gloves are complex in mass processing and have stability problems in the interface with the circuit, which seriously limits their wide application. Moreover, the communication latency caused by wireless transmission is also a factor that seriously restricts remote interaction and simply improving the signal transmission speed has a bottleneck. Here, an integrated full print production flexible smart glove and an advanced response method based on deep learning motion intention prediction were developed to overcome these shortcomings. All device components are integrated on a flexible printed circuit board, including a topological carbon-silver strain sensor, a serpentine stretchable wire, and a wireless signal circuit board, which is suitable for mass production and has specific stability and stretchability. An optimized model based on long short-term memory is designed to predict finger motion intention and respond 100-600 ms in advance to reduce communication latency. This letter proposes a flexible smart glove that is suitable for mass production and provides a new way to solve the remote interaction latency.
AB - Most reported flexible smart gloves are complex in mass processing and have stability problems in the interface with the circuit, which seriously limits their wide application. Moreover, the communication latency caused by wireless transmission is also a factor that seriously restricts remote interaction and simply improving the signal transmission speed has a bottleneck. Here, an integrated full print production flexible smart glove and an advanced response method based on deep learning motion intention prediction were developed to overcome these shortcomings. All device components are integrated on a flexible printed circuit board, including a topological carbon-silver strain sensor, a serpentine stretchable wire, and a wireless signal circuit board, which is suitable for mass production and has specific stability and stretchability. An optimized model based on long short-term memory is designed to predict finger motion intention and respond 100-600 ms in advance to reduce communication latency. This letter proposes a flexible smart glove that is suitable for mass production and provides a new way to solve the remote interaction latency.
KW - Sensor systems
KW - flexible wearable gloves
KW - long short-term memory (LSTM)
KW - motion intention prediction
KW - strain sensor
KW - wireless interaction
UR - https://www.webofscience.com/wos/woscc/full-record/WOS:001049919800012
UR - https://openalex.org/W4385819810
UR - https://www.scopus.com/pages/publications/85168667957
U2 - 10.1109/LSENS.2023.3303068
DO - 10.1109/LSENS.2023.3303068
M3 - Journal Article
SN - 2475-1472
VL - 7
JO - IEEE Sensors Letters
JF - IEEE Sensors Letters
IS - 9
M1 - 5502104
ER -