Motion intention recognition is considered the key technology for enhancing the training effectiveness of upper limb rehabilitation robots for stroke patients,but traditional recognition systems are difficult to simul...Motion intention recognition is considered the key technology for enhancing the training effectiveness of upper limb rehabilitation robots for stroke patients,but traditional recognition systems are difficult to simultaneously balance real-time performance and reliability.To achieve real-time and accurate upper limb motion intention recognition,a multi-modal fusion method based on surface electromyography(sEMG)signals and arrayed flexible thin-film pressure(AFTFP)sensors was proposed.Through experimental tests on 10 healthy subjects(5 males and 5 females,age 23±2 years),sEMG signals and human-machine interaction force(HMIF)signals were collected during elbow flexion,extension,and shoulder internal and external rotation.The AFTFP signals based on dynamic calibration compensation and the sEMG signals were processed for feature extraction and fusion,and the recognition performance of single signals and fused signals was compared using a support vector machine(SVM).The experimental results showed that the sEMG signals consistently appeared 175±25 ms earlier than the HMIF signals(p<0.01,paired t-test).In offline conditions,the recognition accuracy of the fused signals exceeded 99.77%across different time windows.Under a 0.1 s time window,the real-time recognition accuracy of the fused signals was 14.1%higher than that of the single sEMG signal,and the system’s end-to-end delay was reduced to less than 100 ms.The AFTFP sensor is applied to motion intention recognition for the first time.And its low-cost,high-density array design provided an innovative solution for rehabilitation robots.The findings demonstrate that the AFTFP sensor adopted in this study effectively enhances intention recognition performance.The fusion of its output HMIF signals with sEMG signals combines the advantages of both modalities,enabling real-time and accurate motion intention recognition.This provides efficient command output for human-machine interaction in scenarios such as stroke rehabilitation.展开更多
Multimodal information sensing becomes increasingly critical under the rapid development of automation and information technology.With the ability to provide high-density and high-sensitivity pressure detection,pressu...Multimodal information sensing becomes increasingly critical under the rapid development of automation and information technology.With the ability to provide high-density and high-sensitivity pressure detection,pressure sensor arrays have been applied to a variety of fields,including intelligent robotics,medical monitoring,and industrial automation.This study proposes a pressure sensor array system based on the Minecraft game platform.The simulation and testing of the pressure sensor arrays system have been conducted using redstone circuits and pressure plates in Minecraft to simulate real-world piezoelectric pressure sensor arrays.A series of experiments verified the feasibility and effectiveness of the system.展开更多
Distributed pressure sensor array is a promising approach for the estimation of flight parameters for small unmanned aerial vehicles.Current flexible pressure sensor arrays are conventionally subjected to limited sens...Distributed pressure sensor array is a promising approach for the estimation of flight parameters for small unmanned aerial vehicles.Current flexible pressure sensor arrays are conventionally subjected to limited sensor resolution,poor bending flexibility,and inadequate packaging protection,resulting in insufficient precision for flight parameter estimation.Here we present a high-resolution differential pressure sensor array using a calorimetric measurement method and a multilayer polyimide bonding technique.The proposed differential pressure sensor array reaches a detection limit of 36.5 mPa over a range of 500 Pa and shows high repeatability when attached to varying curved surfaces.In addition,a superhydrophobic packaging is integrated into the sensor fabrication process,endowing it with waterproof capability.Utilizing a multilayer perceptron neural network,we demonstrated the function of the sensor array in estimating airspeeds and angle of attacks,achieving average solving errors of 0.15 m/s and 0.37°,respectively.展开更多
Flexible sensing array integrated with multiple sensors is an attractive approach for flight parameter detection.However,the poor resolution of flexible sensors and time-consuming neural network processes mitigate the...Flexible sensing array integrated with multiple sensors is an attractive approach for flight parameter detection.However,the poor resolution of flexible sensors and time-consuming neural network processes mitigate their accuracy and adaptability in predicting flight parameters.Here we present an ultra-thin flexible sensing patch with a new configuration,comprising a differential pressure sensor array and a vector flow velocity sensor.The capacitive differential pressure sensor array is fabricated by a multilayer polyimide bonding technique,reaching a resolution of 0.14 Pa.To solve flight parameters with the flexible sensing patch,we develop an analytical pressure-velocity fusion algorithm,enabling fast response and high accuracy in flight parameter detection.The average errors in calculating the angle of attack,angle of sideslip,and airspeed are 0.22°,0.35°,and 0.73 m s^(-1),respectively.The high-resolution flexible sensors and novel analytical pressure-velocity fusion algorithm pave the way for flexible sensing patch-based air data sensing techniques.展开更多
The development of pressure sensor arrays capable of distinguishing the shape and texture details of objects is of considerable interest in the emerging fields of smart robots,prostheses,human-machine interfaces,and a...The development of pressure sensor arrays capable of distinguishing the shape and texture details of objects is of considerable interest in the emerging fields of smart robots,prostheses,human-machine interfaces,and artificial intelligence(AI).Here we report an integrated pressure sensor array,by combining solution-processed two-dimensional(2D)MoS2 van der Waals(vdW)thin film transistor(TFT)active matrix and conductive micropyramidal pressure-sensitive rubber(PSR)electrodes made of polydimethylsiloxane/carbon nanotube composites,to achieve spatially revolved pressure mapping with excellent contrast and low power consumption.We demonstrate a 10×10 active matrix by using the 2D MoS2 vdW-TFTs with high on-off ratio>10^(6),minimal hysteresis,and excellent device-to-device uniformity.The combination of the vdW-TFT active matrix with the highly uniform micropyramidal PSR electrodes creates an integrated pressure sensing array for spatially resolved pressure mapping.This study demonstrates that the solution-processed 2D vdW-TFTs offer a solution for active-matrix control of pressure sensor arrays,and could be extended for other active-matrix arrays of electronic or optoelectronic devices.展开更多
基金supported by Guangdong Basic and Applied Basic Research Foundation(No.2024A1515012810).
文摘Motion intention recognition is considered the key technology for enhancing the training effectiveness of upper limb rehabilitation robots for stroke patients,but traditional recognition systems are difficult to simultaneously balance real-time performance and reliability.To achieve real-time and accurate upper limb motion intention recognition,a multi-modal fusion method based on surface electromyography(sEMG)signals and arrayed flexible thin-film pressure(AFTFP)sensors was proposed.Through experimental tests on 10 healthy subjects(5 males and 5 females,age 23±2 years),sEMG signals and human-machine interaction force(HMIF)signals were collected during elbow flexion,extension,and shoulder internal and external rotation.The AFTFP signals based on dynamic calibration compensation and the sEMG signals were processed for feature extraction and fusion,and the recognition performance of single signals and fused signals was compared using a support vector machine(SVM).The experimental results showed that the sEMG signals consistently appeared 175±25 ms earlier than the HMIF signals(p<0.01,paired t-test).In offline conditions,the recognition accuracy of the fused signals exceeded 99.77%across different time windows.Under a 0.1 s time window,the real-time recognition accuracy of the fused signals was 14.1%higher than that of the single sEMG signal,and the system’s end-to-end delay was reduced to less than 100 ms.The AFTFP sensor is applied to motion intention recognition for the first time.And its low-cost,high-density array design provided an innovative solution for rehabilitation robots.The findings demonstrate that the AFTFP sensor adopted in this study effectively enhances intention recognition performance.The fusion of its output HMIF signals with sEMG signals combines the advantages of both modalities,enabling real-time and accurate motion intention recognition.This provides efficient command output for human-machine interaction in scenarios such as stroke rehabilitation.
文摘Multimodal information sensing becomes increasingly critical under the rapid development of automation and information technology.With the ability to provide high-density and high-sensitivity pressure detection,pressure sensor arrays have been applied to a variety of fields,including intelligent robotics,medical monitoring,and industrial automation.This study proposes a pressure sensor array system based on the Minecraft game platform.The simulation and testing of the pressure sensor arrays system have been conducted using redstone circuits and pressure plates in Minecraft to simulate real-world piezoelectric pressure sensor arrays.A series of experiments verified the feasibility and effectiveness of the system.
基金supported financially by National Natural Science Foundation of China(Nos.T2121003,U23A20638.)the National Key Research and Development Program of China(2023YFB3208000,2023YFB3208001).
文摘Distributed pressure sensor array is a promising approach for the estimation of flight parameters for small unmanned aerial vehicles.Current flexible pressure sensor arrays are conventionally subjected to limited sensor resolution,poor bending flexibility,and inadequate packaging protection,resulting in insufficient precision for flight parameter estimation.Here we present a high-resolution differential pressure sensor array using a calorimetric measurement method and a multilayer polyimide bonding technique.The proposed differential pressure sensor array reaches a detection limit of 36.5 mPa over a range of 500 Pa and shows high repeatability when attached to varying curved surfaces.In addition,a superhydrophobic packaging is integrated into the sensor fabrication process,endowing it with waterproof capability.Utilizing a multilayer perceptron neural network,we demonstrated the function of the sensor array in estimating airspeeds and angle of attacks,achieving average solving errors of 0.15 m/s and 0.37°,respectively.
基金supported financially by the National Natural Science Foundation of China(T2121003 received by X.D.,and U23A20638 received by Y.J.)the National Key Research and Development Program of China(2023YFB3208000 and 2023YFB3208001 received by Y.J.).
文摘Flexible sensing array integrated with multiple sensors is an attractive approach for flight parameter detection.However,the poor resolution of flexible sensors and time-consuming neural network processes mitigate their accuracy and adaptability in predicting flight parameters.Here we present an ultra-thin flexible sensing patch with a new configuration,comprising a differential pressure sensor array and a vector flow velocity sensor.The capacitive differential pressure sensor array is fabricated by a multilayer polyimide bonding technique,reaching a resolution of 0.14 Pa.To solve flight parameters with the flexible sensing patch,we develop an analytical pressure-velocity fusion algorithm,enabling fast response and high accuracy in flight parameter detection.The average errors in calculating the angle of attack,angle of sideslip,and airspeed are 0.22°,0.35°,and 0.73 m s^(-1),respectively.The high-resolution flexible sensors and novel analytical pressure-velocity fusion algorithm pave the way for flexible sensing patch-based air data sensing techniques.
基金Y.H.acknowledges the financial support from the Office of Naval Research through award N00014-18-1-2491.X.F.D.acknowledged the support from the US Department of Energy,Office of Basic Energy Sciences,Division of Materials Science and Engineering through award DE-SC0018828(material preparation).
文摘The development of pressure sensor arrays capable of distinguishing the shape and texture details of objects is of considerable interest in the emerging fields of smart robots,prostheses,human-machine interfaces,and artificial intelligence(AI).Here we report an integrated pressure sensor array,by combining solution-processed two-dimensional(2D)MoS2 van der Waals(vdW)thin film transistor(TFT)active matrix and conductive micropyramidal pressure-sensitive rubber(PSR)electrodes made of polydimethylsiloxane/carbon nanotube composites,to achieve spatially revolved pressure mapping with excellent contrast and low power consumption.We demonstrate a 10×10 active matrix by using the 2D MoS2 vdW-TFTs with high on-off ratio>10^(6),minimal hysteresis,and excellent device-to-device uniformity.The combination of the vdW-TFT active matrix with the highly uniform micropyramidal PSR electrodes creates an integrated pressure sensing array for spatially resolved pressure mapping.This study demonstrates that the solution-processed 2D vdW-TFTs offer a solution for active-matrix control of pressure sensor arrays,and could be extended for other active-matrix arrays of electronic or optoelectronic devices.
