Flexible Strain Sensor-Based Data Glove for Gesture Interaction in the Metaverse: A Review

AbstractAbstractThe rise of the metaverse concept has brought about widespread attention in wearable gesture recognition devices. Data gloves based on flexible strain sensors have been favoured by researchers owing to their low cost, light weight, direct and continuous monitoring of finger movements. In this review, we first compare the advantages and disadvantages of four different approaches based on the vision sensors, myoelectric sensors, inertial and magnetic sensors, and flexible strain sensors in designing data gloves, and demonstrate the superiority of the flexible strain sensor-based data glove used for metaverse applications. Next, some latest commercial data gloves are exampled and the function modules of the data gloves are presented based on the flexible strain sensors. Meanwhile, the potential applications of gesture recognition in the metaverse are summarized in diversified fields. Finally, the existing problems and development prospects of the current data gloves based on flexible strain sensors are concluded. We are optimistic that novel flexible strain sensor-based data gloves will make transformational impact to realize accurate, low-latency, and immersive gesture interaction in the metaverse.Keywords: Flexible strain sensordata glovegesture interactionmetaverse AcknowledgementsWe express gratitude to all the study participants for their participation and perspectives in this review. We offer thanks for the support provided by the National Natural Science Foundation of China, Key Research and Development Program of Shaanxi, Shanghai Sailing Program and Natural Science Foundation of Chongqing.Disclosure statementNo potential conflict of interest was reported by the author(s).Additional informationFundingThis work was supported by the National Natural Science Foundation of China under Grant [52075454, 62076250, 62204204], Key Research and Development Program of Shaanxi under Grant [No. 2021GY-283, No. 2022GY-001], Shanghai Sailing Program under Grant [21YF1451000] and Natural Science Foundation of Chongqing [cstc2021jcyj-msxmX0825].Notes on contributorsBowen JiBowen Ji is an Associate Professor of the Unmanned System Research Institute at Northwestern Polytechnical University. He received his Ph.D. degree in Electronic Science and Technology at Shanghai Jiao Tong University in 2019. His research interests include wearable flexible sensors for human-computer interaction and implantable sensors as brain-computer interfaces.Xuanqi WangXuanqi Wang is currently pursuing master degree in the Unmanned System Research Institute at Northwestern Polytechnical University. He received his Bachelor’s degree in Electronic and Information Engineering at South-Central Minzu University in 2022. His research interests lie in wearable flexible sensors for human-computer interaction.Zekai LiangZekai Liang is currently pursuing master degree in the Unmanned System Research Institute at Northwestern Polytechnical University. He received his Bachelor’s degree in Taiyuan University of Technology in 2020. His research interests focus on wearable devices for human-computer interaction.Haoyang ZhangHaoyang Zhang is an assistant researcher of National Innovation Institute of Defense Technology, Academy of Military Sciences, Beijing, China. He received his Ph.D. degree from School of Precision Instrument and Opto-electronics Engineering, Tianjin University. His main research interests include human computer interaction, micro/nano manufacturing, etc.Qianchen XiaQianchen Xia is an assistant researcher at Tsinghua University, Beijing, China. She received her Ph.D. degree from School of Computer Science and Technology, Beijing University of Aeronautics and Astronautics. Her main research interests include human-computer interaction, human factors engineering, big data management and application, machine learning and software engineering.Liang XieLiang Xie is an assistant researcher of National Innovation Institute of Defense Technology, Academy of Military Sciences, Beijing, China. He received his Ph.D. degrees from National University of Defense Technology in 2018. His research interests include computer vision, human–machine interaction, and mixed reality.Huijiong YanHuijiong Yan is a senior engineer at Tianjin Artificial Intelligence Innovation Center (TAIIC), Tianjin, China. His main research interests include human factors, intelligent human-computer interaction, and industrial design.Fanqi SunFanqi Sun is currently pursuing master degree in the Unmanned System Research Institute at Northwestern Polytechnical University. She received her Bachelor’s degree in Mechanical Engineering at Beijing Forestry University. Her research interests focus on wearable flexible sensors for human-computer interaction and implantable sensors as brain-computer interface.Huicheng FengHuicheng Feng is an associate professor with the Unmanned System Research Institute, Northwestern Polytechnical University, Xi’an. He received his Ph.D. degree in mechanical engineering from Nanyang Technological University, Singapore in 2016. His research interests include microfluidics, microscale heat transfer, and two-phase cooling.Kai TaoKai Tao is an associate professor with the Department of Mechanical Engineering in Northwestern Polytechnical University. He received his M. Eng. in Shanghai Jiao Tong University and Ph.D. degree in Nanyang Technological University. His research interests include NEMS/MEMS fabrication, micro energy harvesting and self-powered MEMS devices.Qiang ShenQiang Shen is currently an associate professor with the MOE Key Laboratory of Micro and Nano Systems for Aerospace, Northwestern Polytechnical University. He received his M.S. and Ph.D. degrees in mechanical engineering from Northwestern Polytechnical University, respectively. His research interests include high-performance MEMS inertial chips and flexible integrated microsystem.Erwei YinErwei Yin is an associate professor of Defense Innovation Institute, Academy of Military Sciences (AMS). He received the M.S. and Ph.D. degrees from College of Mechatronic Engineering and Automation, National University of Defense Technology, respectively. His research interests include brain-computer interfaces and intelligent human-machine interaction technologies.