A smart finger patch with coupled magnetoelastic and resistive bending sensors

Ziyi Dai; Mingrui Wang; Yu Wang; Zechuan Yu; Yan Li; Weidong Qin; Kai Qian

doi:10.1088/1674-4926/24080027

J. Semicond. > 2025, Volume 46 > Issue 1 > 012601

ARTICLES

A smart finger patch with coupled magnetoelastic and resistive bending sensors

Ziyi Dai¹, Mingrui Wang², Yu Wang¹, Zechuan Yu¹, Yan Li^{3, 4,}, Weidong Qin^5, and Kai Qian^{1, 4,}

+ Author Affiliations

1. School of Integrated Circuits, Shandong University, Jinan 250100, China
2. Department of Mechanical Engineering, University of Auckland, Auckland 1010, New Zealand
3. Department of Urology, Qilu Hospital of Shandong University, Jinan 250100, China
4. Shenzhen Research Institute of Shandong University, Shenzhen 518000, China
5. Department of Critical Care Medicine, Qilu hospital of Shandong university, Jinan 250100, China

Author Bio:

Ziyi Dai received her bachelor's degree in 2018 from the University of Electronic Science and Technology of China, and her master's degree in 2019 from the National University of Singapore. In 2023, she completed her doctoral studies at the University of Macau. She is now a faculty member at Shandong University’s School of Integrated Circuit, focus on wetting functionalization of surfaces for flexible electronics.

Mingrui Wang earned his bachelor's degree in 2021 from Wuhan University of Technology. He is currently a direct Ph.D. candidate at the School of Mechanical Engineering at the University of Auckland, where his research is centered on material identification and human-computer interaction based on triboelectric nanogenerators.

Yu Wang got his bachelor's degree in 2020 from Hangzhou Dianzi University. Now he is a master student at School of Integrated Circuit, Shandong University under the supervision of Prof. Kai Qian. His research focuses on manufacture and application of flexible magnetoelectric materials.

Zechuan Yu is currently an undergraduate student at the School of Integrated Circuits, Shandong University, under the guidance of Professor Kai Qian. His research interests are centered around human-computer interaction, with a particular focus on the development and application of flexible sensors.

Yan Li received his bachelor's and master's degrees from Shandong University. He completed his doctoral studies as a joint training program between Fudan University and Yale University. Currently, Yan Li is a deputy chief physician in the Department of Urology at Qilu Hospital of Shandong University, where he is engaged in interdisciplinary research combining medical and engineering approaches within the field of the urinary system.

Weidong Qin received his bachelor's, master's, and doctoral degrees from Shandong University. He is currently a deputy chief physician in the Department of Critical Care Medicine at Qilu Hospital of Shandong University. His research focuses on inflammatory and immune-related diseases, as well as basic research on vascular pathologies.

Kai Qian graduated with a bachelor's degree in 2009 from Anhui University, and obtained his master's degree in 2012 from the University of Science and Technology of China. He completed his doctoral studies in 2017 at Nanyang Technological University in Singapore. Currently, Qian Kai serves as a professor and doctoral supervisor at the School of Integrated Circuit of Shandong University, where he is engaged in research on intelligent flexible "sense-compute-storage integrated" electronic devices.

Corresponding author: Yan Li, yanli@sdu.edu.cn; Weidong Qin, icuqwd@163.com; Kai Qian, kaiqian@sdu.edu.cn

DOI: 10.1088/1674-4926/24080027CSTR: 32376.14.1674-4926.24080027

Abstract: In the era of Metaverse and virtual reality (VR)/augmented reality (AR), capturing finger motion and force interactions is crucial for immersive human-machine interfaces. This study introduces a flexible electronic skin for the index finger, addressing coupled perception of both state and process in dynamic tactile sensing. The device integrates resistive and giant magnetoelastic sensors, enabling detection of surface pressure and finger joint bending. This e-skin identifies three phases of finger action: bending state, dynamic normal force and tangential force (sweeping). The system comprises resistive carbon nanotubes (CNT)/polydimethylsiloxane (PDMS) films for bending sensing and magnetoelastic sensors (NdFeB particles, EcoFlex, and flexible coils) for pressure detection. The inward bending resistive sensor, based on self-assembled microstructures, exhibits directional specificity with a response time under 120 ms and bending sensitivity from 0° to 120°. The magnetoelastic sensors demonstrate specific responses to frequency and deformation magnitude, as well as sensitivity to surface roughness during sliding and material hardness. The system’s capability is demonstrated through tactile-based bread type and condition recognition, achieving 92% accuracy. This intelligent patch shows broad potential in enhancing interactions across various fields, from VR/AR interfaces and medical diagnostics to smart manufacturing and industrial automation.

Key words: human machine interface, flexible sensor, wearable sensor, giant magnetoelastic effect, inward bending sensor

References

[1]	Yin R Y, Wang D P, Zhao S F et al. Wearable sensors-enabled human-machine interaction systems: from design to application. Adv Funct Mater, 2021, 31, 2008936 doi: 10.1002/adfm.202008936
[2]	Si Y Y, Chen S J, Li M, et al. Flexible strain sensors for wearable hand gesture recognition: from devices to systems. Adv Intell Syst, 2022, 4, 2100046 doi: 10.1002/aisy.202100046
[3]	Ji B W, Wang X Q, Liang Z K, et al. Flexible strain sensor-based data glove for gesture interaction in the metaverse: a review. Int J Hum, 2023, 1 doi: 10.1080/10447318.2023.2212232
[4]	Jiang C P, Zhang Z, Pan J, et al. Finger-skin-inspired flexible optical sensor for force sensing and slip detection in robotic grasping. Adv Mater Technol, 2021, 6, 2100285 doi: 10.1002/admt.202100285
[5]	Fang H, Guo J J, Wu H. Wearable triboelectric devices for haptic perception and VR/AR applications. Nano Energy, 2022, 96, 107112 doi: 10.1016/j.nanoen.2022.107112
[6]	Lee K T, Chee P S, Lim E H, et al. Development of flexible glove sensors for virtual reality (VR) applications. Mater Today Proc, 2023 doi: 10.1016/j.matpr.2023.04.423
[7]	Constant N, Cay G, Ravichandran V, et al. Data analytics for wearable IoT-based telemedicine. Wearable Sensors Amsterdam: Elsevier, 2021, 357 doi: 10.1016/B978-0-12-819246-7.00013-9
[8]	Gratz-Kelly S, Philippi D, Fasolt B, et al. Gesture and force sensing based on dielectric elastomers for intelligent gloves in the digital production. Tm-Technisches Messen, 2024, 91, 195 doi: 10.1515/teme-2024-0003
[9]	Luo Y, Wang Z H, Wang J Y, et al. Triboelectric bending sensor based smart glove towards intuitive multi-dimensional human-machine interfaces. Nano Energy, 2021, 89, 106330 doi: 10.1016/j.nanoen.2021.106330
[10]	Brook N, Mizrahi J, Shoham M, et al. A biomechanical model of index finger dynamics. Med Eng Phys, 1995, 17, 54 doi: 10.1016/1350-4533(95)90378-O
[11]	Maas R, Leyendecker S. Structure preserving optimal control simulation of index finger dynamics. The 1st Joint International Conference on Multibody System Dynamics, 2010
[12]	Asakawa D S, Dennerlein J T, Jindrich D L. Index finger and thumb kinematics and performance measurements for common touchscreen gestures. Appl Ergon, 2017, 58, 176 doi: 10.1016/j.apergo.2016.06.004
[13]	Chansri C, Srinonchat J. Utilizing gramian angular fields and convolution neural networks in flex sensors glove for human–computer interaction. IEEE Trans Hum Mach Syst, 2024, 54, 475 doi: 10.1109/THMS.2024.3404101
[14]	Rocha R P, Lopes P A, de Almeida A T, et al. Fabrication and characterization of bending and pressure sensors for a soft prosthetic hand. J Micromech Microeng, 2018, 28, 034001 doi: 10.1088/1361-6439/aaa1d8
[15]	Yuan Y B, Xu H C, Zheng W H, et al. Bending and stretching-insensitive, crosstalk-free, flexible pressure sensor arrays for human-machine interactions. Adv Mater Technol, 2024, 9, 2301615 doi: 10.1002/admt.202301615
[16]	Zhu B, Xu Z J, Liu X, et al. High-linearity flexible pressure sensor based on the gaussian-curve-shaped microstructure for human physiological signal monitoring. ACS Sens, 2023, 8, 3127 doi: 10.1021/acssensors.3c00818
[17]	Lin Q P, Huang J, Yang J L, et al. Highly sensitive flexible iontronic pressure sensor for fingertip pulse monitoring. Adv Healthcare Mater, 2020, 9, 2001023 doi: 10.1002/adhm.202001023
[18]	Das P S, Chhetry A, Maharjan P, et al. A laser ablated graphene-based flexible self-powered pressure sensor for human gestures and finger pulse monitoring. Nano Res, 2019, 12, 1789 doi: 10.1007/s12274-019-2433-5
[19]	Fu X Y, Li L, Chen S, et al. Knitted Ti₃C₂T_x MXene based fiber strain sensor for human–computer interaction. J Colloid Interface Sci, 2021, 604, 643 doi: 10.1016/j.jcis.2021.07.025
[20]	Shu Q, Xu Z B, Liu S, et al. Magnetic flexible sensor with tension and bending discriminating detection. Chem Eng J, 2022, 433, 134424 doi: 10.1016/j.cej.2021.134424
[21]	Li Z D, Hu F M, Chen Z M, et al. Fiber-junction design for directional bending sensors. NPJ Flex Electron, 2021, 5, 4 doi: 10.1038/s41528-021-00102-2
[22]	Bai J, Gu W, Bai Y Y, et al. Multifunctional flexible sensor based on PU-TA@MXene janus architecture for selective direction recognition. Adv Mater, 2023, 35, 2302847 doi: 10.1002/adma.202302847
[23]	Bin Choi S, Noh T, Jung S B, et al. Stretchable piezoresistive pressure sensor array with sophisticated sensitivity, strain-insensitivity, and reproducibility. Adv Sci, 2024, 2405374 doi: 10.1002/advs.202405374
[24]	He J, Zhou R H, Zhang Y F, et al. Strain-insensitive self-powered tactile sensor arrays based on intrinsically stretchable and patternable ultrathin conformal wrinkled graphene-elastomer composite. Adv Funct Mater, 2022, 32, 2107281 doi: 10.1002/adfm.202107281
[25]	Zhao X, Chen G R, Zhou Y H, et al. Giant magnetoelastic effect enabled stretchable sensor for self-powered biomonitoring. ACS Nano, 2022, 16, 6013 doi: 10.1021/acsnano.1c11350
[26]	Zhou Y H, Zhao X, Xu J, et al. Giant magnetoelastic effect in soft systems for bioelectronics. Nat Mater, 2021, 20, 1670 doi: 10.1038/s41563-021-01093-1
[27]	Ding S, Wang M R, Yang H, et al. Sweeping-responsive interface using the intrinsic polarity of magnetized micropillars for self-powered and high-capacity human-machine interaction. Nano Energy, 2022, 102, 107671 doi: 10.1016/j.nanoen.2022.107671
[28]	Wang Y C, Dai S Q, Mei D Q, et al. A flexible tactile sensor with dual-interlocked structure for broad range force sensing and gaming applications. IEEE Trans Instrum Meas, 2022, 71, 9502710
[29]	Amit M, Chukoskie L, Skalsky A J, et al. Flexible pressure sensors for objective assessment of motor disorders. Adv Funct Mater, 2020, 30, 1905241 doi: 10.1002/adfm.201905241
[30]	Ozioko O, Dahiya R. Smart tactile gloves for haptic interaction, communication, and rehabilitation. Adv Intell Syst, 2022, 4, 2100091 doi: 10.1002/aisy.202100091
[31]	Keller M, Barnes R, Brandt C. Evaluation of grip strength and finger forces while performing activities of daily living. Occupational Health Southern Africa, 2022, 187
[32]	Zhou Q, Ji B, Hu F M, et al. Magnetized microcilia array-based self-powered electronic skin for micro-scaled 3D morphology recognition and high-capacity communication. Adv Funct Mater, 2022, 32, 2208120 doi: 10.1002/adfm.202208120
[33]	Dai Z Y, Chen G, Ding S, et al. Facile formation of hierarchical textures for flexible, translucent, and durable superhydrophobic film. Adv Funct Mater, 2021, 31, 2008574 doi: 10.1002/adfm.202008574
[34]	Dai Z Y, Feng K, Wang M R, et al. Optimization of bidirectional bending sensor as flexible ternary terminal for high-capacity human-machine interaction. Nano Energy, 2022, 97, 107173 doi: 10.1016/j.nanoen.2022.107173

Fig. 1. (Color online) Schematic illustration of the main fabrication process for the smart finger patch (SFP). (a) Manufacturing process of the microcilia-based inward bending resistive sensor, including spin-coating, magnetic field-guided microcilia self-assembly, and carbon black spray coating. (b) Fabrication of the magnetoelectric generator (MEG) based on magnetized micropillars, including template method and magnetization. (c) Integration and encapsulation of the SFP.

DownLoad: Full-Size Img PowerPoint

Fig. 2. (Color online) (a) Schematic diagram of the application of smart finger patch (SFP) in the field of human-computer interaction. (b) Three common phases of index finger sensing, contact-based drip, contact based command input and self-bending. (c) Schematic diagram of SFP corresponding to the three functional phases and (d) the partition mechanism.

DownLoad: Full-Size Img PowerPoint

Fig. 3. (Color online) (a) Resistive response of the microcilia-based bending sensor during the flexion process from −120° to 0° to 120°. (b) Resistance change rate when performing 50 cycles of inward bending at 5°, 10°, 20°, 40°, 60°, 80°, 90°, and 120° in the direction shown in the inset. (c) The response time and recovery time of the bending sensor. (d) Characteristic resistance response signals of two bending sensors equipped on the two joints of the index finger under four grasping states, indicating the bending conditions at the two joints.

DownLoad: Full-Size Img PowerPoint

Fig. 4. (Color online) (a) Schematic diagram and optical images of the MEG sensor based on micropillar arrays under normal pressure deformation and (b) schematic diagram of the relative magnetic flux change during the process. (c) Output voltage in the copper coil under pressure loading at different frequencies. (d) Output voltage in the copper coil under different indenter displacements. (e) Comparison of output voltage when sliding on smooth and the surface of artificial steps. (f) Comparison of output voltage when pressing on materials with different hardness.

DownLoad: Full-Size Img PowerPoint

Fig. 5. (Color online) Robotic tactile methods for bread identification using non-visual sensing techniques. (a) Signal recordings from the M1, R1, R2, and M2 sensors of the SFP-based system during a 5-s grasping cycle for five types of bread (donut, small soft bread, large soft bread, small hard bread, large hard bread). (b) Diagram of the deep learning network based on the transformer architecture. (c) Schematic representation of the robot's application of SFP tactile technology for the discrimination of bread types and quality assessment. (d) Graph of training and validation accuracy for the deep learning network. (e) Confusion matrix illustrating the classification outcomes of the deep learning network.

DownLoad: Full-Size Img PowerPoint

[1]	Yin R Y, Wang D P, Zhao S F et al. Wearable sensors-enabled human-machine interaction systems: from design to application. Adv Funct Mater, 2021, 31, 2008936 doi: 10.1002/adfm.202008936
[2]	Si Y Y, Chen S J, Li M, et al. Flexible strain sensors for wearable hand gesture recognition: from devices to systems. Adv Intell Syst, 2022, 4, 2100046 doi: 10.1002/aisy.202100046
[3]	Ji B W, Wang X Q, Liang Z K, et al. Flexible strain sensor-based data glove for gesture interaction in the metaverse: a review. Int J Hum, 2023, 1 doi: 10.1080/10447318.2023.2212232
[4]	Jiang C P, Zhang Z, Pan J, et al. Finger-skin-inspired flexible optical sensor for force sensing and slip detection in robotic grasping. Adv Mater Technol, 2021, 6, 2100285 doi: 10.1002/admt.202100285
[5]	Fang H, Guo J J, Wu H. Wearable triboelectric devices for haptic perception and VR/AR applications. Nano Energy, 2022, 96, 107112 doi: 10.1016/j.nanoen.2022.107112
[6]	Lee K T, Chee P S, Lim E H, et al. Development of flexible glove sensors for virtual reality (VR) applications. Mater Today Proc, 2023 doi: 10.1016/j.matpr.2023.04.423
[7]	Constant N, Cay G, Ravichandran V, et al. Data analytics for wearable IoT-based telemedicine. Wearable Sensors Amsterdam: Elsevier, 2021, 357 doi: 10.1016/B978-0-12-819246-7.00013-9
[8]	Gratz-Kelly S, Philippi D, Fasolt B, et al. Gesture and force sensing based on dielectric elastomers for intelligent gloves in the digital production. Tm-Technisches Messen, 2024, 91, 195 doi: 10.1515/teme-2024-0003
[9]	Luo Y, Wang Z H, Wang J Y, et al. Triboelectric bending sensor based smart glove towards intuitive multi-dimensional human-machine interfaces. Nano Energy, 2021, 89, 106330 doi: 10.1016/j.nanoen.2021.106330
[10]	Brook N, Mizrahi J, Shoham M, et al. A biomechanical model of index finger dynamics. Med Eng Phys, 1995, 17, 54 doi: 10.1016/1350-4533(95)90378-O
[11]	Maas R, Leyendecker S. Structure preserving optimal control simulation of index finger dynamics. The 1st Joint International Conference on Multibody System Dynamics, 2010
[12]	Asakawa D S, Dennerlein J T, Jindrich D L. Index finger and thumb kinematics and performance measurements for common touchscreen gestures. Appl Ergon, 2017, 58, 176 doi: 10.1016/j.apergo.2016.06.004
[13]	Chansri C, Srinonchat J. Utilizing gramian angular fields and convolution neural networks in flex sensors glove for human–computer interaction. IEEE Trans Hum Mach Syst, 2024, 54, 475 doi: 10.1109/THMS.2024.3404101
[14]	Rocha R P, Lopes P A, de Almeida A T, et al. Fabrication and characterization of bending and pressure sensors for a soft prosthetic hand. J Micromech Microeng, 2018, 28, 034001 doi: 10.1088/1361-6439/aaa1d8
[15]	Yuan Y B, Xu H C, Zheng W H, et al. Bending and stretching-insensitive, crosstalk-free, flexible pressure sensor arrays for human-machine interactions. Adv Mater Technol, 2024, 9, 2301615 doi: 10.1002/admt.202301615
[16]	Zhu B, Xu Z J, Liu X, et al. High-linearity flexible pressure sensor based on the gaussian-curve-shaped microstructure for human physiological signal monitoring. ACS Sens, 2023, 8, 3127 doi: 10.1021/acssensors.3c00818
[17]	Lin Q P, Huang J, Yang J L, et al. Highly sensitive flexible iontronic pressure sensor for fingertip pulse monitoring. Adv Healthcare Mater, 2020, 9, 2001023 doi: 10.1002/adhm.202001023
[18]	Das P S, Chhetry A, Maharjan P, et al. A laser ablated graphene-based flexible self-powered pressure sensor for human gestures and finger pulse monitoring. Nano Res, 2019, 12, 1789 doi: 10.1007/s12274-019-2433-5
[19]	Fu X Y, Li L, Chen S, et al. Knitted Ti₃C₂T_x MXene based fiber strain sensor for human–computer interaction. J Colloid Interface Sci, 2021, 604, 643 doi: 10.1016/j.jcis.2021.07.025
[20]	Shu Q, Xu Z B, Liu S, et al. Magnetic flexible sensor with tension and bending discriminating detection. Chem Eng J, 2022, 433, 134424 doi: 10.1016/j.cej.2021.134424
[21]	Li Z D, Hu F M, Chen Z M, et al. Fiber-junction design for directional bending sensors. NPJ Flex Electron, 2021, 5, 4 doi: 10.1038/s41528-021-00102-2
[22]	Bai J, Gu W, Bai Y Y, et al. Multifunctional flexible sensor based on PU-TA@MXene janus architecture for selective direction recognition. Adv Mater, 2023, 35, 2302847 doi: 10.1002/adma.202302847
[23]	Bin Choi S, Noh T, Jung S B, et al. Stretchable piezoresistive pressure sensor array with sophisticated sensitivity, strain-insensitivity, and reproducibility. Adv Sci, 2024, 2405374 doi: 10.1002/advs.202405374
[24]	He J, Zhou R H, Zhang Y F, et al. Strain-insensitive self-powered tactile sensor arrays based on intrinsically stretchable and patternable ultrathin conformal wrinkled graphene-elastomer composite. Adv Funct Mater, 2022, 32, 2107281 doi: 10.1002/adfm.202107281
[25]	Zhao X, Chen G R, Zhou Y H, et al. Giant magnetoelastic effect enabled stretchable sensor for self-powered biomonitoring. ACS Nano, 2022, 16, 6013 doi: 10.1021/acsnano.1c11350
[26]	Zhou Y H, Zhao X, Xu J, et al. Giant magnetoelastic effect in soft systems for bioelectronics. Nat Mater, 2021, 20, 1670 doi: 10.1038/s41563-021-01093-1
[27]	Ding S, Wang M R, Yang H, et al. Sweeping-responsive interface using the intrinsic polarity of magnetized micropillars for self-powered and high-capacity human-machine interaction. Nano Energy, 2022, 102, 107671 doi: 10.1016/j.nanoen.2022.107671
[28]	Wang Y C, Dai S Q, Mei D Q, et al. A flexible tactile sensor with dual-interlocked structure for broad range force sensing and gaming applications. IEEE Trans Instrum Meas, 2022, 71, 9502710
[29]	Amit M, Chukoskie L, Skalsky A J, et al. Flexible pressure sensors for objective assessment of motor disorders. Adv Funct Mater, 2020, 30, 1905241 doi: 10.1002/adfm.201905241
[30]	Ozioko O, Dahiya R. Smart tactile gloves for haptic interaction, communication, and rehabilitation. Adv Intell Syst, 2022, 4, 2100091 doi: 10.1002/aisy.202100091
[31]	Keller M, Barnes R, Brandt C. Evaluation of grip strength and finger forces while performing activities of daily living. Occupational Health Southern Africa, 2022, 187
[32]	Zhou Q, Ji B, Hu F M, et al. Magnetized microcilia array-based self-powered electronic skin for micro-scaled 3D morphology recognition and high-capacity communication. Adv Funct Mater, 2022, 32, 2208120 doi: 10.1002/adfm.202208120
[33]	Dai Z Y, Chen G, Ding S, et al. Facile formation of hierarchical textures for flexible, translucent, and durable superhydrophobic film. Adv Funct Mater, 2021, 31, 2008574 doi: 10.1002/adfm.202008574
[34]	Dai Z Y, Feng K, Wang M R, et al. Optimization of bidirectional bending sensor as flexible ternary terminal for high-capacity human-machine interaction. Nano Energy, 2022, 97, 107173 doi: 10.1016/j.nanoen.2022.107173

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Received: 19 August 2024 Revised: 30 August 2024 Online: Accepted Manuscript: 14 September 2024Uncorrected proof: 18 September 2024Published: 15 January 2025

Article Navigation > Journal of Semiconductors > 2025 > 46(1): 012601

Ziyi Dai, Mingrui Wang, Yu Wang, Zechuan Yu, Yan Li, Weidong Qin, Kai Qian. A smart finger patch with coupled magnetoelastic and resistive bending sensors[J]. Journal of Semiconductors, 2025, 46(1): 012601. doi: 10.1088/1674-4926/24080027 ****Z Y Dai, M R Wang, Y Wang, Z C Yu, Y Li, W D Qin, and K Qian, A smart finger patch with coupled magnetoelastic and resistive bending sensors[J]. J. Semicond., 2025, 46(1), 012601 doi: 10.1088/1674-4926/24080027

Citation:

Ziyi Dai, Mingrui Wang, Yu Wang, Zechuan Yu, Yan Li, Weidong Qin, Kai Qian. A smart finger patch with coupled magnetoelastic and resistive bending sensors[J]. Journal of Semiconductors, 2025, 46(1): 012601. doi: 10.1088/1674-4926/24080027 ****

Z Y Dai, M R Wang, Y Wang, Z C Yu, Y Li, W D Qin, and K Qian, A smart finger patch with coupled magnetoelastic and resistive bending sensors[J]. J. Semicond., 2025, 46(1), 012601 doi: 10.1088/1674-4926/24080027

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A smart finger patch with coupled magnetoelastic and resistive bending sensors

DOI: 10.1088/1674-4926/24080027

CSTR: 32376.14.1674-4926.24080027

Ziyi Dai¹,
Mingrui Wang²,
Yu Wang¹,
Zechuan Yu¹,
Yan Li^{3, 4,},
Weidong Qin^5,,
Kai Qian^{1, 4,}

1.
School of Integrated Circuits, Shandong University, Jinan 250100, China
2.
Department of Mechanical Engineering, University of Auckland, Auckland 1010, New Zealand
3.
Department of Urology, Qilu Hospital of Shandong University, Jinan 250100, China
4.
Shenzhen Research Institute of Shandong University, Shenzhen 518000, China
5.
Department of Critical Care Medicine, Qilu hospital of Shandong university, Jinan 250100, China

More Information

Ziyi Dai received her bachelor's degree in 2018 from the University of Electronic Science and Technology of China, and her master's degree in 2019 from the National University of Singapore. In 2023, she completed her doctoral studies at the University of Macau. She is now a faculty member at Shandong University’s School of Integrated Circuit, focus on wetting functionalization of surfaces for flexible electronics
Mingrui Wang earned his bachelor's degree in 2021 from Wuhan University of Technology. He is currently a direct Ph.D. candidate at the School of Mechanical Engineering at the University of Auckland, where his research is centered on material identification and human-computer interaction based on triboelectric nanogenerators
Yu Wang got his bachelor's degree in 2020 from Hangzhou Dianzi University. Now he is a master student at School of Integrated Circuit, Shandong University under the supervision of Prof. Kai Qian. His research focuses on manufacture and application of flexible magnetoelectric materials
Zechuan Yu is currently an undergraduate student at the School of Integrated Circuits, Shandong University, under the guidance of Professor Kai Qian. His research interests are centered around human-computer interaction, with a particular focus on the development and application of flexible sensors
Yan Li received his bachelor's and master's degrees from Shandong University. He completed his doctoral studies as a joint training program between Fudan University and Yale University. Currently, Yan Li is a deputy chief physician in the Department of Urology at Qilu Hospital of Shandong University, where he is engaged in interdisciplinary research combining medical and engineering approaches within the field of the urinary system
Weidong Qin received his bachelor's, master's, and doctoral degrees from Shandong University. He is currently a deputy chief physician in the Department of Critical Care Medicine at Qilu Hospital of Shandong University. His research focuses on inflammatory and immune-related diseases, as well as basic research on vascular pathologies
Kai Qian graduated with a bachelor's degree in 2009 from Anhui University, and obtained his master's degree in 2012 from the University of Science and Technology of China. He completed his doctoral studies in 2017 at Nanyang Technological University in Singapore. Currently, Qian Kai serves as a professor and doctoral supervisor at the School of Integrated Circuit of Shandong University, where he is engaged in research on intelligent flexible "sense-compute-storage integrated" electronic devices
Corresponding author: yanli@sdu.edu.cn; icuqwd@163.com; kaiqian@sdu.edu.cn
Received Date: 2024-08-19
Revised Date: 2024-08-30

Available Online: 2024-09-14

Abstract

Abstract

In the era of Metaverse and virtual reality (VR)/augmented reality (AR), capturing finger motion and force interactions is crucial for immersive human-machine interfaces. This study introduces a flexible electronic skin for the index finger, addressing coupled perception of both state and process in dynamic tactile sensing. The device integrates resistive and giant magnetoelastic sensors, enabling detection of surface pressure and finger joint bending. This e-skin identifies three phases of finger action: bending state, dynamic normal force and tangential force (sweeping). The system comprises resistive carbon nanotubes (CNT)/polydimethylsiloxane (PDMS) films for bending sensing and magnetoelastic sensors (NdFeB particles, EcoFlex, and flexible coils) for pressure detection. The inward bending resistive sensor, based on self-assembled microstructures, exhibits directional specificity with a response time under 120 ms and bending sensitivity from 0° to 120°. The magnetoelastic sensors demonstrate specific responses to frequency and deformation magnitude, as well as sensitivity to surface roughness during sliding and material hardness. The system’s capability is demonstrated through tactile-based bread type and condition recognition, achieving 92% accuracy. This intelligent patch shows broad potential in enhancing interactions across various fields, from VR/AR interfaces and medical diagnostics to smart manufacturing and industrial automation.
- human machine interface,
- flexible sensor,
- wearable sensor,
- giant magnetoelastic effect,
- inward bending sensor

Supplementary materials to this article can be found online at https://doi.org/10.1088/1674-4926/24080027.

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