Luo, Y. et al. Learning human–environment interactions using conformal tactile textiles. Nat. Electron. 4, 193–201 (2021).
Moin, A. et al. A wearable biosensing system with in-sensor adaptive machine learning for hand gesture recognition. Nat. Electron. 4, 54–63 (2021).
Zhou, Z. et al. Sign-to-speech translation using machine-learning-assisted stretchable sensor arrays. Nat. Electron. 3, 571–578 (2020).
Chen, W. et al. A survey on hand pose estimation with wearable. Sensors 20, 1074 (2020).
Glauser, O. et al. Interactive hand pose estimation using a stretch-sensing soft glove. ACM Trans. Graph. 38, 41 (2019).
Wang, M. et al. Gesture recognition using a bioinspired learning architecture that integrates visual data with somatosensory data from stretchable sensors. Nat. Electron. 3, 563–570 (2020).
Zhu, M., Sun, Z. & Lee, C. Soft modular glove with multimodal sensing and augmented haptic feedback enabled by materials’ multifunctionalities. ACS Nano 16, 14097–14110 (2022).
Hughes, J. et al. A simple, inexpensive, wearable glove with hybrid resistive-pressure sensors for computational sensing, proprioception, and task identification. Adv. Intell. Syst. 2, 2000002 (2020).
Sun, Z., Zhu, M., Shan, X. & Lee, C. Augmented tactile-perception and haptic-feedback rings as human–machine interfaces aiming for immersive interactions. Nat. Commun. 13, 5224 (2022).
Sundaram, S. et al. Learning the signatures of the human grasp using a scalable tactile glove. Nature 569, 698–702 (2019).
Lei, Q. et al. A survey of vision-based human action evaluation methods. Sensors 19, 4129 (2019).
Wen, F., Zhang, Z., He, T. & Lee, C. AI enabled sign language recognition and VR space bidirectional communication using triboelectric smart glove. Nat. Commun. 12, 5378 (2021).
Henderson, J. et al. Review of wearable sensor-based health monitoring glove devices for rheumatoid arthritis. Sensors 21, 1576 (2021).
Hughes, J. & Iida, F. Multi-functional soft strain sensors for wearable physiological monitoring. Sensors 18, 3822 (2018).
Atiqur, M.A.R., Antar, A. & Shahid, O. Vision-based action understanding for assistive healthcare: a short review. In Proc. IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) Workshops, 1–11 (2019).
Yang, C. et al. Perspectives of users for a future interactive wearable system for upper extremity rehabilitation following stroke: a qualitative study. J. Neuroeng. Rehabil. 20, 1–10 (2023).
Moin, A. et al. An EMG gesture recognition system with flexible high-density sensors and brain-inspired high-dimensional classifier. In IEEE International Symposium on Circuits and Systems (ISCAS), 1–5 (2018).
Karunratanakul, K. et al. Grasping field: learning implicit representations for human grasps. International Conference on 3D Vision (3DV), 333–344 (2020).
Smith, B. et al. Constraining dense hand surface tracking with elasticity. ACM Trans. Graph. 39, 219 (2020).
Xie, K. et al. Physics-based human motion estimation and synthesis from videos. In Proc. IEEE/CVF International Conference on Computer Vision 11532–11541 (IEEE, 2021).
Jiang, L., Xia, H. & Guo, C. A model-based system for real-time articulated hand tracking using a simple data glove and a depth camera. Sensors 19, 4680 (2019).
Guzov, V. et al. Human POSEitioning System (HPS): 3D human pose estimation and self-localization in large scenes from body-mounted sensors. IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 4316–4327 (2021).
Ehsani, K. et al. Use the force, Luke! Learning to predict physical forces by simulating effects. IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 13–19 (2020).
Ge, L. et al. 3D hand shape and pose estimation from a single RGB image. In Proc. IEEE/CVF Conference on Computer Vision and Pattern Recognition 10833–10842 (IEEE, 2019).
Wu, E. et al. Back-hand-pose: 3D hand pose estimation for a wrist-worn camera via dorsum deformation network. In UIST 2020—Proc. 33rd Annual ACM Symposium on User Interface Software and Technology 1147–1160 (ACM, 2020).
Kocabas, M., Athanasiou, N. & Black, M. VIBE: video inference for human body pose and shape estimation. In Proc. IEEE Computer Society Conference on Computer Vision and Pattern Recognition 5252–5262 (IEEE, 2020).
Hu, F. et al. FingerTrak: continuous 3D hand pose tracking by deep learning hand silhouettes captured by miniature thermal cameras on wrist. Proc. ACM Interact. Mob. Wearable Ubiquitous Technol. 4, 1–24 (2020).
Cao, Z., Hidalgo, G., Simon, T., Wei, S. & Sheikh, Y. OpenPose: realtime multi-person 2D pose estimation using part affinity fields. IEEE Trans. Pattern Anal. Mach. Intell. 43, 172–186 (2021).
Si, Y. et al. Flexible strain sensors for wearable hand gesture recognition: from devices to systems. Adv. Intell. Syst. 4, 2100046 (2022).
Zhang, Q. et al. Dynamic modeling of hand-object interactions via tactile sensing. In IEEE International Conference on Intelligent Robots and Systems 2874–2881 (IEEE, 2021).
Wang, S. et al. Hand gesture recognition framework using a lie group based spatio-temporal recurrent network with multiple hand-worn motion sensors. Inf. Sci. 606, 722–741 (2022).
Deng, L. et al. Sen-Glove: a lightweight wearable glove for hand assistance with soft joint sensing. In International Conference on Robotics and Automation (ICRA), 5170–5175 (IEEE, 2022).
Pan, J. et al. Hybrid-flexible bimodal sensing wearable glove system for complex hand gesture recognition. ACS Sens. 6, 4156–4166 (2021).
Liu, Y., Zhang, S. & Gowda, M. NeuroPose: 3D hand pose tracking using EMG wearables. In Proc. of the Web Conference (WWW 2021), 1471–1482 (2021).
Denz, R. et al. A high-accuracy, low-budget sensor glove for trajectory model learning. In 2021 20th International Conference on Advanced Robotics, ICAR 2021 1109–1115 (2021).
Luo, Y. Discovering the Patterns of Human–Environment Interactions Using Scalable Functional Textiles (Massachusetts Institute of Technology, 2020).
Côté-Allard, U. et al. Deep learning for electromyographic hand gesture signal classification using transfer learning. IEEE Trans. Neural Syst. Rehabil. Eng. 27, 760–771 (2019).
Zhang, W. et al. Intelligent knee sleeves: a real-time multimodal dataset for 3d lower body motion estimation using smart textile. IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) (2023).
Luo, Y. et al. Intelligent carpet: inferring 3D human pose from tactile signals. In Proc. IEEE/CVF Conference on Computer Vision and Pattern Recognition 11255–11265 (IEEE, 2021).
Zhou, L., Shen, W., Liu, Y. & Zhang, Y. A scalable durable and seamlessly integrated knitted fabric strain sensor for human motion tracking. Adv. Mater. Technol. 7, 2200082 (2022).
Brahmbhatt, S. et al. ContactPose: a dataset of grasps with object contact and hand pose. in Computer Vision—ECCV 2020 12358, 361–378 (Springer, 2020).
Lei, X., Sun, L. & Xia, Y. Lost data reconstruction for structural health monitoring using deep convolutional generative adversarial networks. Struct. Health Monit. 20, 2069–2087 (2021).
Soltanian, S. et al. Highly piezoresistive compliant nanofibrous sensors for tactile and epidermal electronic applications. J. Mater. Res. 30, 121–129 (2015).
Soltanian, S. et al. Highly stretchable, sparse, metallized nanofiber webs as thin, transferrable transparent conductors. Adv. Energy Mater. 3, 1332–1337 (2013).
Konku-Asase, Y., Yaya, A. & Kan-Dapaah, K. Curing temperature effects on the tensile properties and hardness of γ-Fe2O3 reinforced PDMS nanocomposites. Adv. Mater. Sci. Eng. 2020, 6562373 (2020).
Liu, Z. et al. Functionalized fiber-based strain sensors: pathway to next-generation wearable electronics. Nanomicro Lett. 14, 61 (2022).
Ho, D. et al. Multifunctional smart textronics with blow-spun nonwoven fabrics. Adv. Funct. Mater. 29, 1900025 (2019).
Vu, C. & Kim, J. Highly sensitive e-textile strain sensors enhanced by geometrical treatment for human monitoring. Sensors 20, 2383 (2020).
Tang, Z. et al. Highly stretchable core-sheath fibers via wet-spinning for wearable strain sensors. ACS Appl. Mater. Interfaces 10, 6624–6635 (2018).
Gao, Y. et al. 3D-printed coaxial fibers for integrated wearable sensor skin. Adv. Mater. Technol. 4, 1900504 (2019).
Cai, G. et al. Highly stretchable sheath-core yarns for multifunctional wearable electronics. ACS Appl. Mater. Interfaces 12, 29717–29727 (2020).
Xu, L. et al. Moisture-resilient graphene-dyed wool fabric for strain sensing. ACS Appl. Mater. Interfaces 12, 13265–13274 (2020).
Tashakori, A. arvintashakori/SmartTextileGlove: v1.0.0. Zenodo https://doi.org/10.5281/zenodo.10128938 (2023).
![[2305.08845] Large Language Models are Zero-Shot Rankers for Recommender Systems](https://aigumbo.com/wp-content/uploads/2023/12/arxiv-logo-fb-235x190.png "[2305.08845] Large Language Models are Zero-Shot Rankers for Recommender Systems"){kind=logo}
