Intracortical neural interfaces directly connect brain neurons with external devices to achieve high temporal resolution and spatially precise sampling of neural activity.When applied to freely moving animals,this tec...Intracortical neural interfaces directly connect brain neurons with external devices to achieve high temporal resolution and spatially precise sampling of neural activity.When applied to freely moving animals,this technology provides in-depth insight into the underlying neural mechanisms for their movement and cognition in real-world scenarios.However,the application of implanted devices in freely moving animals is limited by restrictions on their behavioral freedom and physiologic impact.In this paper,four technological directions for ideal implantable neural interface devices are analyzed:higher spatial density,improved biocompatibility,enhanced multimodal detection of electrical/neurotransmitter signals,and more effective neural modulation.Finally,we discuss how these technological developments have been applied to freely moving animals to provide better insight into neuroscience and clinical medicine.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
The fusion of VlSI （visual identity system Internet）, digital maps and Web GIS is presented. Web GIS interface interactive design with VISI needs to consider more new factors. VISI can provide the design principle, ...The fusion of VlSI （visual identity system Internet）, digital maps and Web GIS is presented. Web GIS interface interactive design with VISI needs to consider more new factors. VISI can provide the design principle, elements and contents for the Web GIS. The design of the Wuhan Bus Search System is fulfilled to confirm the validity and practicability of the fusion.展开更多
Background With an increasing number of vehicles becoming autonomous,intelligent,and connected,paying attention to the future usage of car human-machine interface with these vehicles should become more relevant.Severa...Background With an increasing number of vehicles becoming autonomous,intelligent,and connected,paying attention to the future usage of car human-machine interface with these vehicles should become more relevant.Several studies have addressed car HMI but were less attentive to designing and implementing interactive glazing for every day(autonomous)driving contexts.Methods Reflecting on the literature,we describe an engineering psychology practice and the design of six novel future user scenarios,which envision the application of a specific set of augmented reality(AR)support user interactions.Additionally,we conduct evaluations on specific scenarios and experiential prototypes,which reveal that these AR scenarios aid the target user groups in experiencing a new type of interaction.The overall evaluation is positive with valuable assessment results and suggestions.Conclusions This study can interest applied psychology educators who aspire to teach how AR can be operationalized in a human-centered design process to students with minimal pre-existing expertise or minimal scientific knowledge in engineering psychology.展开更多
A two-dimensional （2D） multi-channel silicon-based microelectrode array is developed for recording neural signals. Three photolithographic masks are utilized in the fabrication process. SEM images show that the micr...A two-dimensional （2D） multi-channel silicon-based microelectrode array is developed for recording neural signals. Three photolithographic masks are utilized in the fabrication process. SEM images show that the microprobe is 1.2mm long, 100μm wide,and 30μm thick,with recording sites spaced 200μm apart for good signal isolation. For the individual recording sites, the characteristics of impedance versus frequency are shown by in vitro testing. The impedance declines from 14MΩ to 1.9kΩ as the frequency changes from 0 to 10MHz. A compatible PCB （print circuit board） aids in the less troublesome implantation and stabilization of the microprobe.展开更多
This paper proposes a new approach for classification for query interfaces of Deep Web, which extracts features from the form＇s text data on the query interfaces, assisted with the synonym library, and uses radial ba...This paper proposes a new approach for classification for query interfaces of Deep Web, which extracts features from the form＇s text data on the query interfaces, assisted with the synonym library, and uses radial basic function neural network （RBFNN） algorithm to classify the query interfaces. The applied RBFNN is a kind of effective feed-forward artificial neural network, which has a simple networking structure but features with strength of excellent nonlinear approximation, fast convergence and global convergence. A TEL_8 query interfaces＇ data set from UIUC on-line database is used in our experiments, which consists of 477 query interfaces in 8 typical domains. Experimental results proved that the proposed approach can efficiently classify the query interfaces with an accuracy of 95.67%.展开更多
Aiming at the topic of electroencephalogram （EEG） pattern recognition in brain computer interface （BCI）, a classification method based on probabilistic neural network （PNN） with supervised learning is presented ...Aiming at the topic of electroencephalogram （EEG） pattern recognition in brain computer interface （BCI）, a classification method based on probabilistic neural network （PNN） with supervised learning is presented in this paper. It applies the recognition rate of training samples to the learning progress of network parameters. The learning vector quantization is employed to group training samples and the Genetic algorithm （GA） is used for training the network＇ s smoothing parameters and hidden central vector for detemlining hidden neurons. Utilizing the standard dataset I （a） of BCI Competition 2003 and comparing with other classification methods, the experiment results show that the best performance of pattern recognition Js got in this way, and the classification accuracy can reach to 93.8%, which improves over 5% compared with the best result （88.7 % ） of the competition. This technology provides an effective way to EEG classification in practical system of BCI.展开更多
Neuroscience,neuroprosthetics and neural regeneration would benefit from more adequate interfacing devices.To understand how neurons communicate,process information and control behavior,researchers need to monitor ner...Neuroscience,neuroprosthetics and neural regeneration would benefit from more adequate interfacing devices.To understand how neurons communicate,process information and control behavior,researchers need to monitor nerve cell activity with high specifity and high spatio-temporal resolution.Neural prostheses require minimally invasive-implantable devices to re- place lost function, and bypass dysfunctional pathways in the nervous system. Devices built to repair damaged nerves have to support and promote regeneration of host neurons through an injured area. Finally, as neuromodulation is being elevated from last resort to first choice treatment for an increasing number of conditions, implantable devices able to perform targeted regu- lation of neural activity are needed. Recent advances in device miniaturization, materials engineering, and nanotechnology are enabling development of an increasing number of devices that effectively interface with neural circuits. Wireless spinal cord and deep brain stimulators, retinal and cochlear implants, high density electrodes arrays for neural recording have already proven to significantly impact fundamental research in neuro- science, as well as individuals＇ quality of life.展开更多
Neural machine interface technology is a pioneering approach that aims to address the complex challenges of neurological dysfunctions and disabilities resulting from conditions such as congenital disorders,traumatic i...Neural machine interface technology is a pioneering approach that aims to address the complex challenges of neurological dysfunctions and disabilities resulting from conditions such as congenital disorders,traumatic injuries,and neurological diseases.Neural machine interface technology establishes direct connections with the brain or peripheral nervous system to restore impaired motor,sensory,and cognitive functions,significantly improving patients'quality of life.This review analyzes the chronological development and integration of various neural machine interface technologies,including regenerative peripheral nerve interfaces,targeted muscle and sensory reinnervation,agonist–antagonist myoneural interfaces,and brain–machine interfaces.Recent advancements in flexible electronics and bioengineering have led to the development of more biocompatible and highresolution electrodes,which enhance the performance and longevity of neural machine interface technology.However,significant challenges remain,such as signal interference,fibrous tissue encapsulation,and the need for precise anatomical localization and reconstruction.The integration of advanced signal processing algorithms,particularly those utilizing artificial intelligence and machine learning,has the potential to improve the accuracy and reliability of neural signal interpretation,which will make neural machine interface technologies more intuitive and effective.These technologies have broad,impactful clinical applications,ranging from motor restoration and sensory feedback in prosthetics to neurological disorder treatment and neurorehabilitation.This review suggests that multidisciplinary collaboration will play a critical role in advancing neural machine interface technologies by combining insights from biomedical engineering,clinical surgery,and neuroengineering to develop more sophisticated and reliable interfaces.By addressing existing limitations and exploring new technological frontiers,neural machine interface technologies have the potential to revolutionize neuroprosthetics and neurorehabilitation,promising enhanced mobility,independence,and quality of life for individuals with neurological impairments.By leveraging detailed anatomical knowledge and integrating cutting-edge neuroengineering principles,researchers and clinicians can push the boundaries of what is possible and create increasingly sophisticated and long-lasting prosthetic devices that provide sustained benefits for users.展开更多
Optogenetic has been widely applied in various pathogenesis investigations of neuropathic diseases since its accurate and targeted regulation of neuronal activity.However,due to the mismatch between the soft tissues a...Optogenetic has been widely applied in various pathogenesis investigations of neuropathic diseases since its accurate and targeted regulation of neuronal activity.However,due to the mismatch between the soft tissues and the optical waveguide,the long-term neural regulation within soft tissue(such as brain and spinal cord)by implantable optical fibers is a large challenge.Herein,we designed a modulus selfadaptive hydrogel optical fiber(MSHOF)with tunable mechanical properties(Young’modulus was tunable in the range of 0.32-10.56MPa)and low light attenuation(0.12-0.21 dB/cm,472nm laser light),which adapts to light transmission under soft tissues.These advantages of MSHOF can ensure the effectiveness of optogenetic stimulation meanwhile safeguarding the safety of the brain/materials interaction interface.In addition,this work provides more design possibilities of MSHOF for photogenetic stimuli and has significant application prospects in photomedical therapy.展开更多
Virtual reality(VR)is an emerging communication means and creates extensive opportunities in interacting scenarios such as remote collaboration and metaverse.Human-machine interfaces(HMIs)play important roles in VR as...Virtual reality(VR)is an emerging communication means and creates extensive opportunities in interacting scenarios such as remote collaboration and metaverse.Human-machine interfaces(HMIs)play important roles in VR as they provide interaction platforms between users and virtual environments.However,traditional VR HMIs based on handheld devices or keyboards cannot recognize diverse three-dimensional(3D)gestures,which results in limited freedom of VR interactions.Here,we report a noncontact VR HMI enabled by an electret-nanofiber-based triboelectric sensor(ETS),which is fabricated by the electrospun polylactic acid/thermoplastic polyurethane(PLA/TPU)electret nanofiber film.The nanofiber structure of PLA/TPU electret enhanced the charge retention ability of triboelectric sensor and thus significantly improved its signal strength and stability.Integrated with a deep learning-based multilayer perceptron neural network,the ETS realizes the recognition of 18 different types of 3D gestures with a high average accuracy of 97.3%.An intelligent noncontact VR interactive system based on the ETS is further developed,which is used to manipulate game characters for performing different actions by 3D gestures.Compared with traditional VR HMIs,the proposed VR HMI based on PLA/TPU electret nanofiber film can detect various 3D gestures and offers a superior interaction freedom.This work for the first time introduces the triboelectric 3D gesture recognition method to the VR HMIs,and could make the interaction between human and virtual environments become more efficient and fascinating.展开更多
Combination flexible and stretchable textiles with self-powered sensors bring a novel insight into wearable functional electronics and cyber security in the era of Internet of Things.This work presents a highly flexib...Combination flexible and stretchable textiles with self-powered sensors bring a novel insight into wearable functional electronics and cyber security in the era of Internet of Things.This work presents a highly flexible and self-powered fully fabric-based triboelectric nanogenerator(F-TENG)with sandwiched structure for biomechanical energy harvesting and real-time biometric authentication.The prepared F-TENG can power a digital watch by low-frequency motion and respond to the pressure change by the fall of leaves.A self-powered wearable keyboard(SPWK)is also fabricated by integrating large-area F-TENG sensor arrays,which not only can trace and record electrophysiological signals,but also can identify individuals’typing characteristics by means of the Haar wavelet.Based on these merits,the SPWK has promising applications in the realm of wearable electronics,self-powered sensors,cyber security,and artificial intelligences.展开更多
Letter handwriting,especially stroke correction,is of great importance for recording languages and expressing and exchanging ideas for individual behavior and the public.In this study,a biodegradable and conductive ca...Letter handwriting,especially stroke correction,is of great importance for recording languages and expressing and exchanging ideas for individual behavior and the public.In this study,a biodegradable and conductive carboxymethyl chitosan-silk fibroin(CSF)film is prepared to design wearable triboelectric nanogenerator(denoted as CSF-TENG),which outputs of V_(oc)≈165 V,I_(sc)≈1.4μA,and Q_(sc)≈72 mW cm^(−2).Further,in vitro biodegradation of CSF film is performed through trypsin and lysozyme.The results show that trypsin and lysozyme have stable and favorable biodegradation properties,removing 63.1%of CSF film after degrading for 11 days.Further,the CSF-TENG-based human-machine interface(HMI)is designed to promptly track writing steps and access the accuracy of letters,resulting in a straightforward communication media of human and machine.The CSF-TENG-based HMI can automatically recognize and correct three representative letters(F,H,and K),which is benefited by HMI system for data processing and analysis.The CSF-TENG-based HMI can make decisions for the next stroke,highlighting the stroke in advance by replacing it with red,which can be a candidate for calligraphy practice and correction.Finally,various demonstrations are done in real-time to achieve virtual and real-world controls including writing,vehicle movements,and healthcare.展开更多
Limb loss and spinal cord injury are two debilitating conditions that continue to grow in prevalence. Prosthetic limbs and limb reanimation present two ways of providing affected individuals with means to interact in ...Limb loss and spinal cord injury are two debilitating conditions that continue to grow in prevalence. Prosthetic limbs and limb reanimation present two ways of providing affected individuals with means to interact in the world. These techniques are both dependent on a robust interface with the peripheral nerve. Current methods for interfacing with the peripheral nerve tend to suffer from low specificity, high latency and insufficient robustness for a chronic implant. An optical peripheral nerve interface may solve some of these problems by decreasing invasiveness and providing single axon specificity. In order to implement such an interface three elements are required:(1) a transducer capable of translating light into a neural stimulus or translating neural activity into changes in fluorescence,(2) a means for delivering said transducer and(3) a microscope for providing the stimulus light and detecting the fluorescence change. There are continued improvements in both genetically encoded calcium and voltage indicators as well as new optogenetic actuators for stimulation. Similarly, improvements in specificity of viral vectors continue to improve expression in the axons of the peripheral nerve. Our work has recently shown that it is possible to virally transduce axons of the peripheral nerve for recording from small fibers. The improvements of these components make an optical peripheral nerve interface a rapidly approaching alternative to current methods.展开更多
Quadriplegia is a neuromuscular disease that may cause varying degrees of functional loss in trunk and limbs.In such cases,head movements can be used as an alternative communication channel.In this study,a human–mach...Quadriplegia is a neuromuscular disease that may cause varying degrees of functional loss in trunk and limbs.In such cases,head movements can be used as an alternative communication channel.In this study,a human–machine interface which is controlled by human head movements is designed and implemented.The proposed system enables users to steer the desired movement direction and to control the speed of an output device by using head movements.Head movements of the users are detected using a 6 DOF IMUs measuring three-axis accelerometer and three-axis gyroscope.The head movement axes and the Euler angles have been associated with movement direction and speed,respectively.To ensure driving safety,the speed of the system is determined by considering the speed requested by the user and the obstacle distance on the route.In this context,fuzzy logic algorithm is employed for closed-loop speed control according to distance sensors and reference speed data.A car model was used as the output device on the machine interface.However,the wireless communication between human and machine interfaces provides to adapt this system to any remote device or systems.The implemented system was tested by five subjects.Performance of the system was evaluated in terms of task completion times and feedback from the subjects about their experience with the system.Results indicate that the proposed system is easy to use;and the control capability and usage speed increase with user experience.The control speed is improved with the increase in user experience.展开更多
The ratio of Fe-Al compound at the bonding interface of solid steel plate to Al-7graphite slurry was used to characterize the interracial structure of steel-Al-7graphite semi-solid bonding plate quantitatively. The re...The ratio of Fe-Al compound at the bonding interface of solid steel plate to Al-7graphite slurry was used to characterize the interracial structure of steel-Al-7graphite semi-solid bonding plate quantitatively. The relationship between the ratio of Fe-Al compound at interface and bonding parameters （such as preheat temperature of steel plate, solid fraction of Al-7graphite slurry and rolling speed） was established by artificial neural networks perfectly. The results show that when the bonding parameters are 516 ℃ for preheat temperature of steel plate, 32.5% for solid fraction of Al-7graphite slurry and 12 mm/s for rolling speed, the reasonable ratio of Fe-Al compound corresponding to the largest interfacial shear strength of bonding plate is obtained to be 70.1%. This reasonable ratio of Fe-Al compound is a quantitative criterion of interracial embrittlement, namely, when the ratio of Fe-Al compound at interface is larger than 70.1%, interfacial embrittlement will occur.展开更多
BP( Back Propagation) neural network and PSO( Particle Swarm Optimization) are two main heuristic optimization methods,and are usually used as nonlinear inversion methods in geophysics. The authors applied BP neural n...BP( Back Propagation) neural network and PSO( Particle Swarm Optimization) are two main heuristic optimization methods,and are usually used as nonlinear inversion methods in geophysics. The authors applied BP neural network and BP neural network optimized with PSO into the inversion of 3D density interface respectively,and a comparison was drawn to demonstrate the inversion results. To start with,a synthetic density interface model was created and we used the proceeding inversion methods to test their effectiveness. And then two methods were applied into the inversion of the depth of Moho interface. According to the results,it is clear to find that the application effect of PSO-BP is better than that of BP network. The BP network structures used in both synthetic and field data are consistent in order to obtain preferable inversion results. The applications in synthetic and field tests demonstrate that PSO-BP is a fast and effective method in the inversion of 3D density interface and the optimization effect is evident compared with BP neural network merely,and thus,this method has practical value.展开更多
Kinematic semantics is often an important content of a CAD model(it refers to a single part/solid model in this work)in many applications,but it is usually not the belonging of the model,especially for the one retriev...Kinematic semantics is often an important content of a CAD model(it refers to a single part/solid model in this work)in many applications,but it is usually not the belonging of the model,especially for the one retrieved from a common database.Especially,the effective and automatic method to reconstruct the above information for a CAD model is still rare.To address this issue,this paper proposes a smart approach to identify each assembly interface on every CAD model since the assembly interface is the fundamental but key element of reconstructing kinematic semantics.First,as the geometry of an assembly interface is formed by one or more adjacent faces on each model,a face-attributed adjacency graph integrated with face structure fingerprint is proposed.This can describe each CAD model as well as its assembly interfaces uniformly.After that,aided by the above descriptor,an improved graph attention network is developed based on a new dual-level anti-interference filtering mechanism,which makes it have the great potential to identify all representative kinds of assembly interface faces with high accuracy that have various geometric shapes but consistent kinematic semantics.Moreover,based on the abovementioned graph and face-adjacent relationships,each assembly interface on a model can be identified.Finally,experiments on representative CAD models are implemented to verify the effectiveness and characteristics of the proposed approach.The results show that the average assembly-interface-face-identification accuracy of the proposed approach can reach 91.75%,which is about 2%–5%higher than those of the recent-representative graph neural networks.Besides,compared with the state-of-the-art methods,our approach is more suitable to identify the assembly interfaces(with various shapes)for each individual CAD model that has typical kinematic pairs.展开更多
Sense of touch is one of the important information from environment for human to live in daily life. Haptic interface is a hot topic in virtual reality but almost all of the devices focus on fingers and hands as targe...Sense of touch is one of the important information from environment for human to live in daily life. Haptic interface is a hot topic in virtual reality but almost all of the devices focus on fingers and hands as targets. In this paper, we focus on the foot haptic device with magnetic flied sensitive elastomer （MSE）. We developed a haptic unit used as a magnetic field generator for MSE and contact point of foot haptic device. MSE samples mixed with 80 wt% carbonyl iron particles were prepared and evaluated with the developed magnet. Experimental results show that the mechanical property of the haptic unit can be modeled with the adjustable friction element. This property has a good advantage for the haptic unit.展开更多
基金sponsored by the National Natural Science Foundation of China(62121003,T2293730,T2293731,61960206012,62333020,and 62171434)the National Key Research and Development Program of China(2022YFC2402501 and 2022YFB3205602)the Major Program of Scientific and Technical Innovation 2030(2021ZD02016030)。
文摘Intracortical neural interfaces directly connect brain neurons with external devices to achieve high temporal resolution and spatially precise sampling of neural activity.When applied to freely moving animals,this technology provides in-depth insight into the underlying neural mechanisms for their movement and cognition in real-world scenarios.However,the application of implanted devices in freely moving animals is limited by restrictions on their behavioral freedom and physiologic impact.In this paper,four technological directions for ideal implantable neural interface devices are analyzed:higher spatial density,improved biocompatibility,enhanced multimodal detection of electrical/neurotransmitter signals,and more effective neural modulation.Finally,we discuss how these technological developments have been applied to freely moving animals to provide better insight into neuroscience and clinical medicine.
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 （No. 40071071）.
文摘The fusion of VlSI （visual identity system Internet）, digital maps and Web GIS is presented. Web GIS interface interactive design with VISI needs to consider more new factors. VISI can provide the design principle, elements and contents for the Web GIS. The design of the Wuhan Bus Search System is fulfilled to confirm the validity and practicability of the fusion.
基金Supported by the‘Automotive Glazing Application in Intelligent Cockpit Human-Machine Interface’project(SKHX2021049)a collaboration between the Saint-Go Bain Research and the Beijing Normal University。
文摘Background With an increasing number of vehicles becoming autonomous,intelligent,and connected,paying attention to the future usage of car human-machine interface with these vehicles should become more relevant.Several studies have addressed car HMI but were less attentive to designing and implementing interactive glazing for every day(autonomous)driving contexts.Methods Reflecting on the literature,we describe an engineering psychology practice and the design of six novel future user scenarios,which envision the application of a specific set of augmented reality(AR)support user interactions.Additionally,we conduct evaluations on specific scenarios and experiential prototypes,which reveal that these AR scenarios aid the target user groups in experiencing a new type of interaction.The overall evaluation is positive with valuable assessment results and suggestions.Conclusions This study can interest applied psychology educators who aspire to teach how AR can be operationalized in a human-centered design process to students with minimal pre-existing expertise or minimal scientific knowledge in engineering psychology.
文摘A two-dimensional （2D） multi-channel silicon-based microelectrode array is developed for recording neural signals. Three photolithographic masks are utilized in the fabrication process. SEM images show that the microprobe is 1.2mm long, 100μm wide,and 30μm thick,with recording sites spaced 200μm apart for good signal isolation. For the individual recording sites, the characteristics of impedance versus frequency are shown by in vitro testing. The impedance declines from 14MΩ to 1.9kΩ as the frequency changes from 0 to 10MHz. A compatible PCB （print circuit board） aids in the less troublesome implantation and stabilization of the microprobe.
基金Supported by the National Natural Science Foundation of China(60473045)the Research Plan of Hebei Province(05213573)the Research Plan of Education Office of Hebei Province(2004406).
文摘This paper proposes a new approach for classification for query interfaces of Deep Web, which extracts features from the form＇s text data on the query interfaces, assisted with the synonym library, and uses radial basic function neural network （RBFNN） algorithm to classify the query interfaces. The applied RBFNN is a kind of effective feed-forward artificial neural network, which has a simple networking structure but features with strength of excellent nonlinear approximation, fast convergence and global convergence. A TEL_8 query interfaces＇ data set from UIUC on-line database is used in our experiments, which consists of 477 query interfaces in 8 typical domains. Experimental results proved that the proposed approach can efficiently classify the query interfaces with an accuracy of 95.67%.
基金Supported by the National Natural Science Foundation of China (No. 30570485)the Shanghai "Chen Guang" Project (No. 09CG69).
文摘Aiming at the topic of electroencephalogram （EEG） pattern recognition in brain computer interface （BCI）, a classification method based on probabilistic neural network （PNN） with supervised learning is presented in this paper. It applies the recognition rate of training samples to the learning progress of network parameters. The learning vector quantization is employed to group training samples and the Genetic algorithm （GA） is used for training the network＇ s smoothing parameters and hidden central vector for detemlining hidden neurons. Utilizing the standard dataset I （a） of BCI Competition 2003 and comparing with other classification methods, the experiment results show that the best performance of pattern recognition Js got in this way, and the classification accuracy can reach to 93.8%, which improves over 5% compared with the best result （88.7 % ） of the competition. This technology provides an effective way to EEG classification in practical system of BCI.
文摘Neuroscience,neuroprosthetics and neural regeneration would benefit from more adequate interfacing devices.To understand how neurons communicate,process information and control behavior,researchers need to monitor nerve cell activity with high specifity and high spatio-temporal resolution.Neural prostheses require minimally invasive-implantable devices to re- place lost function, and bypass dysfunctional pathways in the nervous system. Devices built to repair damaged nerves have to support and promote regeneration of host neurons through an injured area. Finally, as neuromodulation is being elevated from last resort to first choice treatment for an increasing number of conditions, implantable devices able to perform targeted regu- lation of neural activity are needed. Recent advances in device miniaturization, materials engineering, and nanotechnology are enabling development of an increasing number of devices that effectively interface with neural circuits. Wireless spinal cord and deep brain stimulators, retinal and cochlear implants, high density electrodes arrays for neural recording have already proven to significantly impact fundamental research in neuro- science, as well as individuals＇ quality of life.
基金supported in part by the National Natural Science Foundation of China,Nos.81927804(to GL),82260456(to LY),U21A20479(to LY)Science and Technology Planning Project of Shenzhen,No.JCYJ20230807140559047(to LY)+3 种基金Key-Area Research and Development Program of Guangdong Province,No.2020B0909020004(to GL)Guangdong Basic and Applied Research Foundation,No.2023A1515011478(to LY)the Science and Technology Program of Guangdong Province,No.2022A0505090007(to GL)Ministry of Science and Technology,Shenzhen,No.QN2022032013L(to LY)。
文摘Neural machine interface technology is a pioneering approach that aims to address the complex challenges of neurological dysfunctions and disabilities resulting from conditions such as congenital disorders,traumatic injuries,and neurological diseases.Neural machine interface technology establishes direct connections with the brain or peripheral nervous system to restore impaired motor,sensory,and cognitive functions,significantly improving patients'quality of life.This review analyzes the chronological development and integration of various neural machine interface technologies,including regenerative peripheral nerve interfaces,targeted muscle and sensory reinnervation,agonist–antagonist myoneural interfaces,and brain–machine interfaces.Recent advancements in flexible electronics and bioengineering have led to the development of more biocompatible and highresolution electrodes,which enhance the performance and longevity of neural machine interface technology.However,significant challenges remain,such as signal interference,fibrous tissue encapsulation,and the need for precise anatomical localization and reconstruction.The integration of advanced signal processing algorithms,particularly those utilizing artificial intelligence and machine learning,has the potential to improve the accuracy and reliability of neural signal interpretation,which will make neural machine interface technologies more intuitive and effective.These technologies have broad,impactful clinical applications,ranging from motor restoration and sensory feedback in prosthetics to neurological disorder treatment and neurorehabilitation.This review suggests that multidisciplinary collaboration will play a critical role in advancing neural machine interface technologies by combining insights from biomedical engineering,clinical surgery,and neuroengineering to develop more sophisticated and reliable interfaces.By addressing existing limitations and exploring new technological frontiers,neural machine interface technologies have the potential to revolutionize neuroprosthetics and neurorehabilitation,promising enhanced mobility,independence,and quality of life for individuals with neurological impairments.By leveraging detailed anatomical knowledge and integrating cutting-edge neuroengineering principles,researchers and clinicians can push the boundaries of what is possible and create increasingly sophisticated and long-lasting prosthetic devices that provide sustained benefits for users.
基金supported by the National Key Research and Development Program of China(Nos.2021YFA1201302 and 2021YFA1201300)the National Natural Science Foundation of China(Nos.52303033,52173029)+1 种基金Shanghai Sailing Program(No.23YF1400400)the Natural Science Foundation of Shanghai(No.21ZR1400500).
文摘Optogenetic has been widely applied in various pathogenesis investigations of neuropathic diseases since its accurate and targeted regulation of neuronal activity.However,due to the mismatch between the soft tissues and the optical waveguide,the long-term neural regulation within soft tissue(such as brain and spinal cord)by implantable optical fibers is a large challenge.Herein,we designed a modulus selfadaptive hydrogel optical fiber(MSHOF)with tunable mechanical properties(Young’modulus was tunable in the range of 0.32-10.56MPa)and low light attenuation(0.12-0.21 dB/cm,472nm laser light),which adapts to light transmission under soft tissues.These advantages of MSHOF can ensure the effectiveness of optogenetic stimulation meanwhile safeguarding the safety of the brain/materials interaction interface.In addition,this work provides more design possibilities of MSHOF for photogenetic stimuli and has significant application prospects in photomedical therapy.
基金supported by the National Natural Science Foundation of China(No.52303112)the Henan Province Science and Technology Research and Development Program Joint Fund Advantageous Discipline Cultivation Project(No.232301420033)+1 种基金the China Postdoctoral Science Foundation(Nos.2022TQ0281 and 2023M733213)the Key R&D and Promotion Special(Scientific Problem Tackling)Project of Henan Province(No.242102231014).
文摘Virtual reality(VR)is an emerging communication means and creates extensive opportunities in interacting scenarios such as remote collaboration and metaverse.Human-machine interfaces(HMIs)play important roles in VR as they provide interaction platforms between users and virtual environments.However,traditional VR HMIs based on handheld devices or keyboards cannot recognize diverse three-dimensional(3D)gestures,which results in limited freedom of VR interactions.Here,we report a noncontact VR HMI enabled by an electret-nanofiber-based triboelectric sensor(ETS),which is fabricated by the electrospun polylactic acid/thermoplastic polyurethane(PLA/TPU)electret nanofiber film.The nanofiber structure of PLA/TPU electret enhanced the charge retention ability of triboelectric sensor and thus significantly improved its signal strength and stability.Integrated with a deep learning-based multilayer perceptron neural network,the ETS realizes the recognition of 18 different types of 3D gestures with a high average accuracy of 97.3%.An intelligent noncontact VR interactive system based on the ETS is further developed,which is used to manipulate game characters for performing different actions by 3D gestures.Compared with traditional VR HMIs,the proposed VR HMI based on PLA/TPU electret nanofiber film can detect various 3D gestures and offers a superior interaction freedom.This work for the first time introduces the triboelectric 3D gesture recognition method to the VR HMIs,and could make the interaction between human and virtual environments become more efficient and fascinating.
基金the National Key R&D Project from Minister of Science and Technology(Grant No.2016YFA0202704)the Beijing Municipal Natural Science Foundation(Grant No.2212052)+1 种基金the Shanghai Sailing Program(Grant No.19S28101)the Fundamental Research Funds for the Central Universities(Grant No.19D128102).
文摘Combination flexible and stretchable textiles with self-powered sensors bring a novel insight into wearable functional electronics and cyber security in the era of Internet of Things.This work presents a highly flexible and self-powered fully fabric-based triboelectric nanogenerator(F-TENG)with sandwiched structure for biomechanical energy harvesting and real-time biometric authentication.The prepared F-TENG can power a digital watch by low-frequency motion and respond to the pressure change by the fall of leaves.A self-powered wearable keyboard(SPWK)is also fabricated by integrating large-area F-TENG sensor arrays,which not only can trace and record electrophysiological signals,but also can identify individuals’typing characteristics by means of the Haar wavelet.Based on these merits,the SPWK has promising applications in the realm of wearable electronics,self-powered sensors,cyber security,and artificial intelligences.
基金This study was financially supported by National Natural Science Foundation of China(NO.31470509)China Postdoctoral Science Foundation(No.2019T120390)+1 种基金China Scholarship Council(NO.202006790091)the Opening Project of China National Textile and Apparel Council Key Laboratory of Natural Dyes,Soochow University(No.SDHY2122)。
文摘Letter handwriting,especially stroke correction,is of great importance for recording languages and expressing and exchanging ideas for individual behavior and the public.In this study,a biodegradable and conductive carboxymethyl chitosan-silk fibroin(CSF)film is prepared to design wearable triboelectric nanogenerator(denoted as CSF-TENG),which outputs of V_(oc)≈165 V,I_(sc)≈1.4μA,and Q_(sc)≈72 mW cm^(−2).Further,in vitro biodegradation of CSF film is performed through trypsin and lysozyme.The results show that trypsin and lysozyme have stable and favorable biodegradation properties,removing 63.1%of CSF film after degrading for 11 days.Further,the CSF-TENG-based human-machine interface(HMI)is designed to promptly track writing steps and access the accuracy of letters,resulting in a straightforward communication media of human and machine.The CSF-TENG-based HMI can automatically recognize and correct three representative letters(F,H,and K),which is benefited by HMI system for data processing and analysis.The CSF-TENG-based HMI can make decisions for the next stroke,highlighting the stroke in advance by replacing it with red,which can be a candidate for calligraphy practice and correction.Finally,various demonstrations are done in real-time to achieve virtual and real-world controls including writing,vehicle movements,and healthcare.
基金funded in part by the University of Colorado Medical Scientist Training Program and funds from the NIH SPARC initiative administered through the Office of the Director:1OT2OD023852-01
文摘Limb loss and spinal cord injury are two debilitating conditions that continue to grow in prevalence. Prosthetic limbs and limb reanimation present two ways of providing affected individuals with means to interact in the world. These techniques are both dependent on a robust interface with the peripheral nerve. Current methods for interfacing with the peripheral nerve tend to suffer from low specificity, high latency and insufficient robustness for a chronic implant. An optical peripheral nerve interface may solve some of these problems by decreasing invasiveness and providing single axon specificity. In order to implement such an interface three elements are required:(1) a transducer capable of translating light into a neural stimulus or translating neural activity into changes in fluorescence,(2) a means for delivering said transducer and(3) a microscope for providing the stimulus light and detecting the fluorescence change. There are continued improvements in both genetically encoded calcium and voltage indicators as well as new optogenetic actuators for stimulation. Similarly, improvements in specificity of viral vectors continue to improve expression in the axons of the peripheral nerve. Our work has recently shown that it is possible to virally transduce axons of the peripheral nerve for recording from small fibers. The improvements of these components make an optical peripheral nerve interface a rapidly approaching alternative to current methods.
基金the Scientific and Technological Research Council of Turkey(TUBITAK).
文摘Quadriplegia is a neuromuscular disease that may cause varying degrees of functional loss in trunk and limbs.In such cases,head movements can be used as an alternative communication channel.In this study,a human–machine interface which is controlled by human head movements is designed and implemented.The proposed system enables users to steer the desired movement direction and to control the speed of an output device by using head movements.Head movements of the users are detected using a 6 DOF IMUs measuring three-axis accelerometer and three-axis gyroscope.The head movement axes and the Euler angles have been associated with movement direction and speed,respectively.To ensure driving safety,the speed of the system is determined by considering the speed requested by the user and the obstacle distance on the route.In this context,fuzzy logic algorithm is employed for closed-loop speed control according to distance sensors and reference speed data.A car model was used as the output device on the machine interface.However,the wireless communication between human and machine interfaces provides to adapt this system to any remote device or systems.The implemented system was tested by five subjects.Performance of the system was evaluated in terms of task completion times and feedback from the subjects about their experience with the system.Results indicate that the proposed system is easy to use;and the control capability and usage speed increase with user experience.The control speed is improved with the increase in user experience.
基金Project(50054) supported by the Program for New Century Excellent Talents in Universityproject(20060004020) supported by the Research Fund for the Doctoral Program of Higher Education+1 种基金project(3062017) supported by the Natural Science Foundation of Beijing, Chinaproject(2004SZ007) supported by the Foundation of Beijing Jiaotong University
文摘The ratio of Fe-Al compound at the bonding interface of solid steel plate to Al-7graphite slurry was used to characterize the interracial structure of steel-Al-7graphite semi-solid bonding plate quantitatively. The relationship between the ratio of Fe-Al compound at interface and bonding parameters （such as preheat temperature of steel plate, solid fraction of Al-7graphite slurry and rolling speed） was established by artificial neural networks perfectly. The results show that when the bonding parameters are 516 ℃ for preheat temperature of steel plate, 32.5% for solid fraction of Al-7graphite slurry and 12 mm/s for rolling speed, the reasonable ratio of Fe-Al compound corresponding to the largest interfacial shear strength of bonding plate is obtained to be 70.1%. This reasonable ratio of Fe-Al compound is a quantitative criterion of interracial embrittlement, namely, when the ratio of Fe-Al compound at interface is larger than 70.1%, interfacial embrittlement will occur.
基金Supported by National High-tech Research&Development Program of China(863 Project)(No.2014AA06A613)
文摘BP( Back Propagation) neural network and PSO( Particle Swarm Optimization) are two main heuristic optimization methods,and are usually used as nonlinear inversion methods in geophysics. The authors applied BP neural network and BP neural network optimized with PSO into the inversion of 3D density interface respectively,and a comparison was drawn to demonstrate the inversion results. To start with,a synthetic density interface model was created and we used the proceeding inversion methods to test their effectiveness. And then two methods were applied into the inversion of the depth of Moho interface. According to the results,it is clear to find that the application effect of PSO-BP is better than that of BP network. The BP network structures used in both synthetic and field data are consistent in order to obtain preferable inversion results. The applications in synthetic and field tests demonstrate that PSO-BP is a fast and effective method in the inversion of 3D density interface and the optimization effect is evident compared with BP neural network merely,and thus,this method has practical value.
基金supported by the National Natural Science Foundation of China[61702147]the Zhejiang Provincial Science and Technology Program in China[2021C03137].
文摘Kinematic semantics is often an important content of a CAD model(it refers to a single part/solid model in this work)in many applications,but it is usually not the belonging of the model,especially for the one retrieved from a common database.Especially,the effective and automatic method to reconstruct the above information for a CAD model is still rare.To address this issue,this paper proposes a smart approach to identify each assembly interface on every CAD model since the assembly interface is the fundamental but key element of reconstructing kinematic semantics.First,as the geometry of an assembly interface is formed by one or more adjacent faces on each model,a face-attributed adjacency graph integrated with face structure fingerprint is proposed.This can describe each CAD model as well as its assembly interfaces uniformly.After that,aided by the above descriptor,an improved graph attention network is developed based on a new dual-level anti-interference filtering mechanism,which makes it have the great potential to identify all representative kinds of assembly interface faces with high accuracy that have various geometric shapes but consistent kinematic semantics.Moreover,based on the abovementioned graph and face-adjacent relationships,each assembly interface on a model can be identified.Finally,experiments on representative CAD models are implemented to verify the effectiveness and characteristics of the proposed approach.The results show that the average assembly-interface-face-identification accuracy of the proposed approach can reach 91.75%,which is about 2%–5%higher than those of the recent-representative graph neural networks.Besides,compared with the state-of-the-art methods,our approach is more suitable to identify the assembly interfaces(with various shapes)for each individual CAD model that has typical kinematic pairs.
文摘Sense of touch is one of the important information from environment for human to live in daily life. Haptic interface is a hot topic in virtual reality but almost all of the devices focus on fingers and hands as targets. In this paper, we focus on the foot haptic device with magnetic flied sensitive elastomer （MSE）. We developed a haptic unit used as a magnetic field generator for MSE and contact point of foot haptic device. MSE samples mixed with 80 wt% carbonyl iron particles were prepared and evaluated with the developed magnet. Experimental results show that the mechanical property of the haptic unit can be modeled with the adjustable friction element. This property has a good advantage for the haptic unit.
