应变-磁场双感知磁致伸缩柔性传感系统与手势交互

Strain-magnetic field dual-sensing magnetostrictive flexible sensing system with gesture interaction

具有人体关节弯曲状态和空间位置感知相结合的柔性应变-磁场双模传感器可提供一种响应迅速、界面友好和应用灵活的人机交互方法。受传感结构制约、小型化可穿戴平台算力及功耗的限制,这类器件目前难以实现人体姿态、位置等多信息的同时感知,以及多信息交互所需复杂模型的部署。为了实现高灵敏度和快速响应的力-磁双感知,提出了一种由Co-Fe薄膜和平面磁场传感线圈组成的磁致伸缩柔性传感器。在10~65 mm的弯曲半径ρ作用下,传感器的最大灵敏度为22 mV/mm。在1~11 kA/m的磁场H作用下,传感器的最大灵敏度为1.78 mV/(kA/m)。在1~4 Hz的不同ρ和H下,传感器灵敏度变化均小于1.6%,具有较好的动态输出稳定性。通过分析双感知传感器的输入/输出信号特征,构建了支持传感器信号处理和传输的传感系统,实现了双感知数据的采集。利用自适应模糊神经网络分析手势和位置信息用于手势识别,对传统应力或弯曲传感器易混淆的12种手势进行分类识别,准确率达到90.1%。此外,结合触觉反馈方法增强系统的信息交互能力,通过产生不同幅度和持续时间的振动反馈,帮助用户更好地掌握虚拟环境中的动作效果和相对位置。传感系统推理用户的手势动作和指令,并触觉反馈设备的响应结果,实现了人与设备之间的双向信息交互。

Flexible sensors capable of detecting both pressure and magnetic fields serve as the cornerstone for merging the real and virtual worlds and facilitate the advancement of wearable devices by providing a rapid response,user-friendly interface,and flexible humanmachine interaction method.Constrained by the sensing structure,the arithmetic power of miniaturized wearable platforms and power consumption,these devices are currently difficult to realize the simultaneous sensing of multiple information such as human posture and position,as well as the deployment of complex models required for multi-information interaction.In order to bi-perceptive of high sensitivity and fast response,we proposed the magnetostrictive flexible sensor,which consists of the Co-Fe film and plane magnetic field sensing coils.The maximal sensitivity of the sensor is 22 mV/mm in the bending of 10~65 mm.The maximal sensitivity of the sensor is 1.78 mV/(kA/m)in the magnetic field of 1~11 kA/m.The sensor demonstrates excellent dynamic output stability,with sensitivity variations of less than 1.6%under differentρand H conditions at frequencies of 1 to 4 Hz.By analyzing the input/output signal characteristics of the dual-sensing sensor,a sensing system supporting sensor signal processing and transmission is constructed to realize dual-sensing data acquisition.Adaptive fuzzy neural network is used to analyze the gesture and position information for gesture recognition,achieving a classification accuracy of 90.1%for 12 gestures that are commonly confused by traditional stress or bending sensors.In addition,the information interaction capability of the system is enhanced by combining the haptic feedback method,which helps the user to better grasp the effect of movement and relative position in the virtual environment by generating vibration feedback with different amplitudes and durations.The sensing system infers the user′s gesture movements and commands,and haptic feedback device response results,enabling a bidirectional information exchange between the user and the device.