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Electromyogram-strain synergetic intelligent artificial throat
Chemical Engineering Journal ( IF 15.1 ) Pub Date : 2022-06-22 , DOI: 10.1016/j.cej.2022.137741
Yancong Qiao , Guangyang Gou , Hua Shuai , Fei Han , Haidong Liu , Hao Tang , Xiaoshi Li , Jinming Jian , Yuhong Wei , Yuanfang Li , Chenglin Xie , Xinyi He , Zhiyuan Liu , Rong Song , Bingpu Zhou , He Tian , Yi Yang , Tian-Ling Ren , Jianhua Zhou

Assisting the disabled to speak is a meaningful activity and attracts much attention in the recent years. In this work, an intelligent artificial throat has been realized based on the nanomesh, which can not only emit the sound, but also detect the voice or throat vibration generated by using the electromyogram (EMG)-strain synergetic method. The Au/PVA nanomesh with good thermoacoustic effect can be used as sound source. By theorical analyzing, the porous nanomesh structure plays an important role during the sound emitting process. The Au/PU nanomesh can also be used as the strain sensor, which shows high sensitivity, large work range, and good stability. A finite element model containing six paralleled resistance layers was proposed to explain the performance of strain sensor, which reveals the nonlinear origin of the device. The Au nanomesh can be applied as the physiological electrodes whose impendence is even lower than the commercial gel electrodes, which can be used to detect the electrocardiogram and EMG signal. In addition, the nanomesh has good water permeability, stability, and conformal property with skin. Finally, a synergetic convolution neural network (SCNN) algorithm built by ResNet18 (EMG part) and two-layers CNN (strain part) is demonstrated to distinguish the transitory voice signals detected by the nanomesh strain sensor and electrodes with the high accuracy of 98.9%. This work has great potential in the language function reconstruction.



中文翻译:

肌电-应变协同智能人工喉

帮助残疾人说话是一项有意义的活动,近年来备受关注。在这项工作中,基于纳米网实现了一种智能人工喉咙,它不仅可以发出声音,还可以通过肌电图(EMG)-应变协同方法检测产生的声音或喉咙振动。具有良好热声效果的Au/PVA纳米网可作为声源。通过理论分析,多孔纳米网结构在发声过程中起着重要作用。Au/PU纳米网也可用作应变传感器,具有灵敏度高、工作范围大、稳定性好等特点。提出了一个包含六个并联电阻层的有限元模型来解释应变传感器的性能,揭示了器件的非线性起源。Au纳米网可用作生理电极,其阻抗甚至低于市售的凝胶电极,可用于检测心电图和EMG信号。此外,纳米网具有良好的透水性、稳定性和与皮肤的保形性。最后,展示了一种由 ResNet18(EMG 部分)和两层 CNN(应变部分)构建的协同卷积神经网络(SCNN)算法,能够以 98.9% 的高精度区分纳米网应变传感器和电极检测到的瞬时语音信号。 . 这项工作在语言功能重建方面具有很大的潜力。纳米网具有良好的透水性、稳定性和与皮肤的保形性。最后,展示了一种由 ResNet18(EMG 部分)和两层 CNN(应变部分)构建的协同卷积神经网络(SCNN)算法,能够以 98.9% 的高精度区分纳米网应变传感器和电极检测到的瞬时语音信号。 . 这项工作在语言功能重建方面具有很大的潜力。纳米网具有良好的透水性、稳定性和与皮肤的保形性。最后,展示了一种由 ResNet18(EMG 部分)和两层 CNN(应变部分)构建的协同卷积神经网络(SCNN)算法,能够以 98.9% 的高精度区分纳米网应变传感器和电极检测到的瞬时语音信号。 . 这项工作在语言功能重建方面具有很大的潜力。

更新日期:2022-06-22
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