Efficient and flexible interactions require precisely converting human intentions into computer-recognizable signals,which is critical to the breakthrough development of metaverse.Interactive electronics face common d...Efficient and flexible interactions require precisely converting human intentions into computer-recognizable signals,which is critical to the breakthrough development of metaverse.Interactive electronics face common dilemmas,which realize highprecision and stable touch detection but are rigid,bulky,and thick or achieve high flexibility to wear but lose precision.Here,we construct highly bending-insensitive,unpixelated,and waterproof epidermal interfaces(BUW epidermal interfaces)and demonstrate their interactive applications of conformal human–machine integration.The BUW epidermal interface based on the addressable electrical contact structure exhibits high-precision and stable touch detection,high flexibility,rapid response time,excellent stability,and versatile“cut-and-paste”character.Regardless of whether being flat or bent,the BUW epidermal interface can be conformally attached to the human skin for real-time,comfortable,and unrestrained interactions.This research provides promising insight into the functional composite and structural design strategies for developing epidermal electronics,which offers a new technology route and may further broaden human–machine interactions toward metaverse.展开更多
The inculcation of bioinspiration in sensing and human–machine interface(HMI)technologies can lead to distinctive characteristics such as conformability,low power consumption,high sensitivity,and unique properties li...The inculcation of bioinspiration in sensing and human–machine interface(HMI)technologies can lead to distinctive characteristics such as conformability,low power consumption,high sensitivity,and unique properties like self-healing,self-cleaning,and adaptability.Both sensing and HMI are fields rife with opportunities for the application of bioinspired nanomaterials,particularly when it comes to wearable sensory systems where biocompatibility is an additional requirement.This review discusses recent development in bioinspired nanomaterials for wearable sensing and HMIs,with a specific focus on state-of-the-art bioinspired capacitive sensors,piezoresistive sensors,piezoelectric sensors,triboelectric sensors,magnetoelastic sensors,and electrochemical sensors.We also present a comprehensive overview of the challenges that have hindered the scientific advancement in academia and commercialization in the industry.展开更多
We outline problems and potential solutions for feasible human-machine interfaces using cable-based parallel manipulators for physiotherapy applications.From an engineering perspective,we discuss the design constraint...We outline problems and potential solutions for feasible human-machine interfaces using cable-based parallel manipulators for physiotherapy applications.From an engineering perspective,we discuss the design constraints related to acceptance by patients and physiotherapist users.To date,most designs have focused on mobile platforms that are designed to be operated as an end-effector connected to human limbs for direct patient interaction.Some specific examples are illustrated from the authors' experience with prototypes available at Laboratory of Robotics and Mechatronics (LARM),Italy.展开更多
Current stretchable surface electrodes have attracted increasing attention owing to their potential applications in biological signal monitoring, wearable human-machine interfaces（HMIs） and the Internet of Things. T...Current stretchable surface electrodes have attracted increasing attention owing to their potential applications in biological signal monitoring, wearable human-machine interfaces（HMIs） and the Internet of Things. The paper proposed a stretchable HMI based on a surface electromyography（sEMG） electrode with a self-similar serpentine configuration. The sEMG electrode was transfer-printed onto the skin surface conformally to monitor biological signals, followed by signal classification and controlling of a mobile robot. Such electrodes can bear rather large deformation（such as 〉30%） under an appropriate areal coverage. The sEMG electrodes have been used to record electrophysiological signals from different parts of the body with sharp curvature, such as the index finger,back of the neck and face, and they exhibit great potential for HMI in the fields of robotics and healthcare. The electrodes placed onto the two wrists would generate two different signals with the fist clenched and loosened. It is classified to four kinds of signals with a combination of the gestures from the two wrists, that is, four control modes. Experiments demonstrated that the electrodes were successfully used as an HMI to control the motion of a mobile robot remotely.展开更多
Purpose–Connected vehicle-based variable speed limit(CV-VSL)systems in fog area use multi-source detection data to indicate drivers to make uniform change in speed when low visibility conditions suddenly occur.The pu...Purpose–Connected vehicle-based variable speed limit(CV-VSL)systems in fog area use multi-source detection data to indicate drivers to make uniform change in speed when low visibility conditions suddenly occur.The purpose of the speed limit is to make the driver’s driving behavior more consistent,so as to improve traffic safety and relieve traffic congestion.The on-road dynamic message sign(DMS)and on-board human–machine interface(HMI)are two types of warning technologies for CV-VSL systems.This study aims to analyze drivers’acceptance of the two types of warning technologies in fog area and its influencing factors.Design/methodology/approach–This study developed DMS and on-board HMI for the CV-VSL system in fog area on a driving simulator.The DMS and on-board HMI provided the driver with weather and speed limit information.In all,38 participants participated in the experiment and completed questionnaires on drivers’basic information,perceived usefulness and ease of use of the CV-VSL systems.Technology acceptance model(TAM)was developed to evaluate the drivers’acceptance of CV-VSL systems.A variance analysis method was used to study the influencing factors of drivers’acceptance including drivers’characteristics,technology types and fog density.Findings–The results showed that drivers’acceptance of on-road DMS was significantly higher than that of on-board HMI.The fog density had no significant effect on drivers’acceptance of on-road DMS or on-board HMI.Drivers’gender,age,driving year and driving personality were associated with the acceptance of the two CV-VSL technologies differently.This study is beneficial to the functional improvement of on-road DMS,on-board HMI and their market prospects.Originality/value–Previous studies have been conducted to evaluate the effectiveness of CV-VSL systems.However,there were rare studies focused on the drivers’attitude toward using which was also called as acceptance of the CV-VSL systems.Therefore,this research calculated the drivers’acceptance of two normally used CV-VSL systems including on-road DMS and on-board HMI using TAM.Furthermore,variance analysis was conducted to explore whether the factors such as drivers’characteristics(gender,age,driving year and driving personality),technology types and fog density affected the drivers’acceptance of the CV-VSL systems.展开更多
In recent years,Brain-Computer Interface(BCI)system gained much popularity since it aims at establishing the communication between human brain and computer.BCI systems are applied in several research areas such as neu...In recent years,Brain-Computer Interface(BCI)system gained much popularity since it aims at establishing the communication between human brain and computer.BCI systems are applied in several research areas such as neuro-rehabilitation,robots,exoeskeletons,etc.Electroencephalography(EEG)is a technique commonly applied in capturing brain signals.It is incorporated in BCI systems since it has attractive features such as noninvasive nature,high time-resolution output,mobility and cost-effective.EEG classification process is highly essential in decision making process and it incorporates different processes namely,feature extraction,feature selection,and classification.With this motivation,the current research paper presents an Intelligent Optimal Fuzzy Support Vector Machine-based EEC recognition(IOFSVM-EEG)model for BCI system.Independent Component Analysis(ICA)technique is applied onto the proposed IOFSVM-EEG model to remove the artefacts that exist in EEG signal and to retain the meaningful EEG information.Besides,Common Spatial Pattern(CSP)-based feature extraction technique is utilized to derive a helpful set of feature vectors from the preprocessed EEG signals.Moreover,OFSVM method is applied in the classification of EEG signals,in which the parameters involved in FSVM are optimally tuned using Grasshopper Optimization Algorithm(GOA).In order to validate the enhanced EEG recognition outcomes of the proposed IOFSVM-EEG model,an extensive set of experiments was conducted.The outcomes were examined under distinct aspects.The experimental results highlighted the enhanced performance of the presented IOFSVM-EEG model over other state-of-the-art methods.展开更多
This paper describes the design and evaluation of a user interface for a remotely supervised autonomous agricultural sprayer. The interface was designed to help the remote supervisor to instruct the autonomous sprayer...This paper describes the design and evaluation of a user interface for a remotely supervised autonomous agricultural sprayer. The interface was designed to help the remote supervisor to instruct the autonomous sprayer to commence operation, monitor the status of the sprayer and its operation in the field, and intervene when needed (i.e., to stop or shut down). Design principles and guidelines were carefully selected to help develop a human-centered automation interface. Evaluation of the interface using a combination of heuristic, cognitive walkthrough, and user testing techniques revealed several strengths of the design as well as areas that needed further improvement. Overall, this paper provides guidelines that will assist other researchers to develop an ergonomic user interface for a fully autonomous agricultural machine.展开更多
基金supported by National Natural Science Foundation of China(52202117,52232006,52072029,and 12102256)Collaborative Innovation Platform Project of Fu-Xia-Quan National Independent Innovation Demonstration Zone(3502ZCQXT2022005)+3 种基金Natural Science Foundation of Fujian Province of China(2022J01065)State Key Lab of Advanced Metals and Materials(2022-Z09)Fundamental Research Funds for the Central Universities(20720220075)the Ministry of Education,Singapore,under its MOE ARF Tier 2(MOE2019-T2-2-179).
文摘Efficient and flexible interactions require precisely converting human intentions into computer-recognizable signals,which is critical to the breakthrough development of metaverse.Interactive electronics face common dilemmas,which realize highprecision and stable touch detection but are rigid,bulky,and thick or achieve high flexibility to wear but lose precision.Here,we construct highly bending-insensitive,unpixelated,and waterproof epidermal interfaces(BUW epidermal interfaces)and demonstrate their interactive applications of conformal human–machine integration.The BUW epidermal interface based on the addressable electrical contact structure exhibits high-precision and stable touch detection,high flexibility,rapid response time,excellent stability,and versatile“cut-and-paste”character.Regardless of whether being flat or bent,the BUW epidermal interface can be conformally attached to the human skin for real-time,comfortable,and unrestrained interactions.This research provides promising insight into the functional composite and structural design strategies for developing epidermal electronics,which offers a new technology route and may further broaden human–machine interactions toward metaverse.
基金support.J.C.also acknowledges the Hellman Fellows Research Grant,the UCLA Pandemic Resources Program Research Award,the Research Recovery Grant by the UCLA Academic Senate,and the Brain&Behavior Research Foundation Young Investigator Grant(Grant Number:30944)the Catalyzing Pediatric Innovation Grant(Grant Number:47744)from the West Coast Consortium for Technology&Innovation in Pediatrics,Children’s Hospital Los Angeles.
文摘The inculcation of bioinspiration in sensing and human–machine interface(HMI)technologies can lead to distinctive characteristics such as conformability,low power consumption,high sensitivity,and unique properties like self-healing,self-cleaning,and adaptability.Both sensing and HMI are fields rife with opportunities for the application of bioinspired nanomaterials,particularly when it comes to wearable sensory systems where biocompatibility is an additional requirement.This review discusses recent development in bioinspired nanomaterials for wearable sensing and HMIs,with a specific focus on state-of-the-art bioinspired capacitive sensors,piezoresistive sensors,piezoelectric sensors,triboelectric sensors,magnetoelastic sensors,and electrochemical sensors.We also present a comprehensive overview of the challenges that have hindered the scientific advancement in academia and commercialization in the industry.
基金supported by the research project RORAS 2 of the Mediterranean Program funded by INRIA,France
文摘We outline problems and potential solutions for feasible human-machine interfaces using cable-based parallel manipulators for physiotherapy applications.From an engineering perspective,we discuss the design constraints related to acceptance by patients and physiotherapist users.To date,most designs have focused on mobile platforms that are designed to be operated as an end-effector connected to human limbs for direct patient interaction.Some specific examples are illustrated from the authors' experience with prototypes available at Laboratory of Robotics and Mechatronics (LARM),Italy.
基金supported by the National Natural Science Foundation of China(Nos.51635007,91323303)
文摘Current stretchable surface electrodes have attracted increasing attention owing to their potential applications in biological signal monitoring, wearable human-machine interfaces（HMIs） and the Internet of Things. The paper proposed a stretchable HMI based on a surface electromyography（sEMG） electrode with a self-similar serpentine configuration. The sEMG electrode was transfer-printed onto the skin surface conformally to monitor biological signals, followed by signal classification and controlling of a mobile robot. Such electrodes can bear rather large deformation（such as 〉30%） under an appropriate areal coverage. The sEMG electrodes have been used to record electrophysiological signals from different parts of the body with sharp curvature, such as the index finger,back of the neck and face, and they exhibit great potential for HMI in the fields of robotics and healthcare. The electrodes placed onto the two wrists would generate two different signals with the fist clenched and loosened. It is classified to four kinds of signals with a combination of the gestures from the two wrists, that is, four control modes. Experiments demonstrated that the electrodes were successfully used as an HMI to control the motion of a mobile robot remotely.
文摘Purpose–Connected vehicle-based variable speed limit(CV-VSL)systems in fog area use multi-source detection data to indicate drivers to make uniform change in speed when low visibility conditions suddenly occur.The purpose of the speed limit is to make the driver’s driving behavior more consistent,so as to improve traffic safety and relieve traffic congestion.The on-road dynamic message sign(DMS)and on-board human–machine interface(HMI)are two types of warning technologies for CV-VSL systems.This study aims to analyze drivers’acceptance of the two types of warning technologies in fog area and its influencing factors.Design/methodology/approach–This study developed DMS and on-board HMI for the CV-VSL system in fog area on a driving simulator.The DMS and on-board HMI provided the driver with weather and speed limit information.In all,38 participants participated in the experiment and completed questionnaires on drivers’basic information,perceived usefulness and ease of use of the CV-VSL systems.Technology acceptance model(TAM)was developed to evaluate the drivers’acceptance of CV-VSL systems.A variance analysis method was used to study the influencing factors of drivers’acceptance including drivers’characteristics,technology types and fog density.Findings–The results showed that drivers’acceptance of on-road DMS was significantly higher than that of on-board HMI.The fog density had no significant effect on drivers’acceptance of on-road DMS or on-board HMI.Drivers’gender,age,driving year and driving personality were associated with the acceptance of the two CV-VSL technologies differently.This study is beneficial to the functional improvement of on-road DMS,on-board HMI and their market prospects.Originality/value–Previous studies have been conducted to evaluate the effectiveness of CV-VSL systems.However,there were rare studies focused on the drivers’attitude toward using which was also called as acceptance of the CV-VSL systems.Therefore,this research calculated the drivers’acceptance of two normally used CV-VSL systems including on-road DMS and on-board HMI using TAM.Furthermore,variance analysis was conducted to explore whether the factors such as drivers’characteristics(gender,age,driving year and driving personality),technology types and fog density affected the drivers’acceptance of the CV-VSL systems.
文摘In recent years,Brain-Computer Interface(BCI)system gained much popularity since it aims at establishing the communication between human brain and computer.BCI systems are applied in several research areas such as neuro-rehabilitation,robots,exoeskeletons,etc.Electroencephalography(EEG)is a technique commonly applied in capturing brain signals.It is incorporated in BCI systems since it has attractive features such as noninvasive nature,high time-resolution output,mobility and cost-effective.EEG classification process is highly essential in decision making process and it incorporates different processes namely,feature extraction,feature selection,and classification.With this motivation,the current research paper presents an Intelligent Optimal Fuzzy Support Vector Machine-based EEC recognition(IOFSVM-EEG)model for BCI system.Independent Component Analysis(ICA)technique is applied onto the proposed IOFSVM-EEG model to remove the artefacts that exist in EEG signal and to retain the meaningful EEG information.Besides,Common Spatial Pattern(CSP)-based feature extraction technique is utilized to derive a helpful set of feature vectors from the preprocessed EEG signals.Moreover,OFSVM method is applied in the classification of EEG signals,in which the parameters involved in FSVM are optimally tuned using Grasshopper Optimization Algorithm(GOA).In order to validate the enhanced EEG recognition outcomes of the proposed IOFSVM-EEG model,an extensive set of experiments was conducted.The outcomes were examined under distinct aspects.The experimental results highlighted the enhanced performance of the presented IOFSVM-EEG model over other state-of-the-art methods.
文摘This paper describes the design and evaluation of a user interface for a remotely supervised autonomous agricultural sprayer. The interface was designed to help the remote supervisor to instruct the autonomous sprayer to commence operation, monitor the status of the sprayer and its operation in the field, and intervene when needed (i.e., to stop or shut down). Design principles and guidelines were carefully selected to help develop a human-centered automation interface. Evaluation of the interface using a combination of heuristic, cognitive walkthrough, and user testing techniques revealed several strengths of the design as well as areas that needed further improvement. Overall, this paper provides guidelines that will assist other researchers to develop an ergonomic user interface for a fully autonomous agricultural machine.
