## 3 LIG-Based Wearable Systems for Multifunctional and Intelligent HCI
### Bioinspired Dual-Channel Speech Recognition System  
Acoustic HCI systems based on microphones are often susceptible to interference from noisy environments, resulting in poor signal quality and further affecting the accuracy of HCI. To address this issue, [PERSON] et al. designed a dual-channel speech recognition system using LIG that combined both EMG and mechanical signals [25]. When an expression is about to be produced, an action potential is generated in the motor cortex, and the electrical signal is transmitted to the epidermal muscles through the neurons and stimulates muscle fibers to contract. Ion channels in the muscle are opened to release the ions, and EMG electrodes attached to the skin can convert the ion current into the electrical current to  
Figure 13: Intelligent artificial throat based on LIG. (**a**) One-step fabrication process of LIG. PI is directly converted into LIG by the irradiation of the 450 nm laser. Scale bar, 2.5 cm. (**b**) LIG has the ability of emitting and detecting sound in one device. (**c**) The artificial throat can detect the movement of throat and generate controllable sound, respectively. Reproduced with permission from [28]. Copyright 2017 Springer Nature. acquire the EMG signal, while the deformation of the skin caused by the muscle contraction can be picked up by mechanical sensors. Therefore, both the EMG signal and the muscle movement signal of the larynx contain speech information, and combining the two signals for speech recognition can greatly improve the accuracy of speech analysis. Figure 14 depicts the structure of the speech recognition system, which comprises six layers. These layers include a hydrogel layer that reduces skin-electrode contact impedance and eliminates noise interference on EMG signals, a LIG-based EMG electrode, a PI separation layer that separates the EMG electrode and the mechanical sensor to prevent mutual interference, a LIG-based mechanical sensor, a PI substrate layer, and a thin-film PU tape to encapsulate and attach the system to the skin. Each patch contains a pair of EMG electrodes and two mechanical sensors that monitor one-channel EMG signals and two-channel strain signals. Furthermore, in addition to the good electrical and mechanical properties, the system had excellent durability (the performance remained good after 10 million fatigue tests). During the experiments, two patches were applied to the chin and throat to collect speech information. A recommended approach for this study is not to trace the source of EMG signals (because the epidermal EMG signals are often superimposed by many subcutaneous muscle activity signals), but to focus on the relevant features of the EMG signals and speech information. To give the system intelligence, the research team constructed the largest dataset of isolated words, which included information on 71 words and 10 numbers, using EMG electrodes and mechanical sensors to study the connection between speech, epidermal EMG, and strain signals. A neural network was trained to recognize these signals using the dataset. The intelligent speech recognition system, through the combination of the patch and intelligent algorithm, could achieve 100% accuracy in recognizing digits and 96.86% accuracy in recognizing 71 words. Despite being in a noisy environment with 68.8 dB, the system still maintained a recognition accuracy above 95%. The research team showcased the potential of the system in human-computer interaction (HCI) applications by using voice control to play the Snake game (the snake's movements are controlled by speaking directions). In conclusion, the dual-channel speech recognition system is suitable for high-quality speech HCI in a noisy environment, voice reconstruction for disabled people, silent communication, and many other application  
Figure 14: The bioinspired dual-channel speech recognition system. Reproduced with permission from [25]. Copyright 2022 Cell Press. scenarios. It serves as a valuable reference for the development of multifunctional and intelligent HCI systems.