| Literature DB >> 34223178 |
Shengshun Duan1, Yucheng Lin1, Zhehan Wang2,3, Junyi Tang1, Yinhui Li1, Di Zhu1, Jun Wu1, Li Tao2,3,4, Chang-Hwan Choi5, Litao Sun3,4,6,7, Jun Xia1, Lei Wei1, Baoping Wang1.
Abstract
Reliable, wide range, and highly sensitive joint movement monitoring is essential for training activities, human behavior analysis, and human-machine interfaces. Yet, most current motion sensors work on the nano/microcracks induced by the tensile deformation on the convex surface of joints during joint movements, which cannot satisfy requirements of ultrawide detectable angle range, high angle sensitivity, conformability, and consistence under cyclic movements. In nature, scorpions sense small vibrations by allowing for compression strain conversion from external mechanical vibrations through crack-shaped slit sensilla. Here, we demonstrated that ultraconformal sensors based on controlled slit structures, inspired by the geometry of a scorpion's slit sensilla, exhibit high sensitivity (0.45%deg-1), ultralow angle detection threshold (~15°), fast response/relaxation times (115/72 ms), wide range (15° ~120°), and durability (over 1000 cycles). Also, a user-friendly, hybrid sign language system has been developed to realize Chinese and American sign language recognition and feedback through video and speech broadcasts, making these conformal motion sensors promising candidates for joint movement monitoring in wearable electronics and robotics technology.Entities:
Year: 2021 PMID: 34223178 PMCID: PMC8212815 DOI: 10.34133/2021/9861467
Source DB: PubMed Journal: Research (Wash D C) ISSN: 2639-5274
Figure 1Illustration of the bioinspired sensor and its potential application. (a, b) Schematic of the analogy between the motion sensor and the scorpion. (c) Monitoring of training action for material arts training (Tai-chi). (d) Conformal contact between the motion sensor and the human skin.
Figure 2Fabrication and structural characterization of motion sensors. (a) The fabrication process of the motion sensor. (b) Optical images of PU blocks and MXene-coated PU blocks. Inset is an SEM image for MXene-coated PU blocks. (c, d) The SEM image of the slit sensilla of the scorpion. (e) The SEM image of the lateral wall of the blocks. (f) The SEM image of MXene-coated keel structures, showing the uniform distribution and tight interfacial contacts between MXene and PU keel structures. (g) Corresponding energy-dispersive X-ray spectroscopy (EDS) mapping of C, Ti, and O in the MXene-coated PU keel structures. (h) A tight interfacial contact is formed between the PVA gel and the MXene-coated PU blocks. The inset shows the details of the tight interfacial contact.
Figure 3Working mechanism and electrical performance of motion sensors. (a) The equivalent resistance model of the as-prepared sensor. (b) The equivalent circuit diagram of the motion sensor. (c) The schematic diagram of compression strain in the motion sensor during bending. (d) The mathematic model shows the minimal angle where the adjacent blocks connect with each other. (e) The relative changes of electrical conductance for sensors with different slit ratios when the bending angle increases from 0 to 120°. (f) The electrical conductance of sensors with different slit ratios when the bending angle only increases from 0 to 30°. (g) The current-angle response of the sensor exhibits bending-rate-independent sensing behavior. (h) The response/relaxation times of the motion sensor with 1/2 slit ratio when bent from 90° to 120°. (i) The response/relaxation times of the motion sensor with 1/4 slit ratio when bent from 0° to 30°. (j) The durability test under continuous bending–unbending cycles at 120°.
Figure 4Optical feedback for finger motions. (a) Circuit diagram of the optical feedback system. (b) Voltage–current characteristics of the green LED with 0.06 W rated power. (c) The brightness of the green LED gradually increases with the bending angle.
Figure 5Real-time gesture information acquisition. (a) Circuit diagram showing the signal flow in the real-time gesture information acquisition system, from the acquired analog signals to the digital signals. (b) The current-time curve as the index finger bends, with a distinct linear region. The inset indicates the current changes in small bending angles (<30°). (c) Dependence of the acquisition current signals on index finger motion statuses. The insets, labeled I, II, III, IV, and V, show photographs of the five bending statuses. (d, e) Acquired current signals from (d) elbow bending and (e) ankle bending.
Figure 6Demonstration of the human-machine interaction. (a) The voltage dividing circuit. (b) Schematic of the sign language recognition and feedback system. (c) Photographs of the sign language hand gestures (A, E, M, N, and S) according to American Sign Language. (d) The corresponding voltage profiles. (e) A high recognition rate was obtained for Chinese gestures. (f) Photographs showing that the gestures were translated into images and displayed through the LED lattice screen. (g) Sound signal for speech playing. The amplitude was normalized.