Designing interactive glazing through an engineering psychology approach:Six augmented reality scenarios that envision future car human-machine interface

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.

Deep Learning for EMG-based Human-Machine Interaction:A Review

Electromyography(EMG)has already been broadly used in human-machine interaction(HMI)applications.Determining how to decode the information inside EMG signals robustly and accurately is a key problem for which we urgently need a solution.Recently,many EMG pattern recognition tasks have been addressed using deep learning methods.In this paper,we analyze recent papers and present a literature review describing the role that deep learning plays in EMG-based HMI.An overview of typical network structures and processing schemes will be provided.Recent progress in typical tasks such as movement classification,joint angle prediction,and force/torque estimation will be introduced.New issues,including multimodal sensing,inter-subject/inter-session,and robustness toward disturbances will be discussed.We attempt to provide a comprehensive analysis of current research by discussing the advantages,challenges,and opportunities brought by deep learning.We hope that deep learning can aid in eliminating factors that hinder the development of EMG-based HMI systems.Furthermore,possible future directions will be presented to pave the way for future research.

BLIND SPEECH SEPARATION FOR ROBOTS WITH INTELLIGENT HUMAN-MACHINE INTERACTION

Speech recognition rate will deteriorate greatly in human-machine interaction when the speaker's speech mixes with a bystander's voice. This paper proposes a time-frequency approach for Blind Source Seperation (BSS) for intelligent Human-Machine Interaction(HMI). Main idea of the algorithm is to simultaneously diagonalize the correlation matrix of the pre-whitened signals at different time delays for every frequency bins in time-frequency domain. The prososed method has two merits: (1) fast convergence speed; (2) high signal to interference ratio of the separated signals. Numerical evaluations are used to compare the performance of the proposed algorithm with two other deconvolution algorithms. An efficient algorithm to resolve permutation ambiguity is also proposed in this paper. The algorithm proposed saves more than 10% of computational time with properly selected parameters and achieves good performances for both simulated convolutive mixtures and real room recorded speeches.

A Robotic Teleoperation System for Precise Robotic Manipulation by Human-Machine Interaction

Teleoperation is of great importance in the area of robotics,especially when people are unavailable in the robot workshop.It provides a way for people to control robots remotely using human intelligence.In this paper,a robotic teleoperation system for precise robotic manipulation is established.The data glove and the 7-degrees of freedom(DOFs)force feedback controller are used for the remote control interaction.The control system and the monitor system are designed for the remote precise manipulation.The monitor system contains an image acquisition system and a human-machine interaction module,and aims to simulate and detect the robot running state.Besides,a visual object tracking algorithm is developed to estimate the states of the dynamic system from noisy observations.The established robotic teleoperation systemis applied to a series of experiments,and high-precision results are obtained,showing the effectiveness of the physical system.

Skin‑Inspired Ultra‑Tough Supramolecular Multifunctional Hydrogel Electronic Skin for Human–Machine Interaction

Multifunctional supramolecular ultra-tough bionic e-skin with unique durability for human–machine interaction in complex scenarios still remains challenging.Herein,we develop a skininspired ultra-tough e-skin with tunable mechanical properties by a physical cross-linking salting-freezing-thawing method.The gelling agent(β-Glycerophosphate sodium:Gp)induces the aggregation and binding of PVA molecular chains and thereby toughens them(stress up to 5.79 MPa,toughness up to 13.96 MJ m^(−3)).Notably,due to molecular self-assembly,hydrogels can be fully recycled and reprocessed by direct heating(100°C for a few seconds),and the tensile strength can still be maintained at about 100%after six recoveries.The hydrogel integrates transparency(>60%),super toughness(up to 13.96 MJ m^(−3),bearing 1500 times of its own tensile weight),good antibacterial properties(E.coli and S.aureus),UV protection(Filtration:80%–90%),high electrical conductivity(4.72 S m^(−1)),anti-swelling and recyclability.The hydrogel can not only monitor daily physiological activities,but also be used for complex activities underwater and message encryption/decryption.We also used it to create a complete finger joint rehabilitation system with an interactive interface that dynamically presents the user’s health status.Our multifunctional electronic skin will have a profound impact on the future of new rehabilitation medical,human–machine interaction,VR/AR and the metaverse fields.

Flexible and multifunctional triboelectric nanogenerator based on liquid metal/polyvinyl alcohol hydrogel for energy harvesting and self-powered wearable human-machine interaction

Hydrogel-based triboelectric nanoge nerator(TENG)has a promising applied prospect in wearable electronic devices.However,its low performance,poor stability,insufficient recyclability and inferior self-healing seriously hinder its development.Herein,we report a robust route to a liquid metal(LM)/polyvinyl alcohol(PVA)hydrogel-based TENG(LP-TENG).Owing to the intrinsically liquid feature of conductive LM within the flexible PVA hydrogel,the as-prepared LP-TENG exhibited comprehensiye advantages of adaptability,biocompatibility,outstanding electrical performance,superior stability,recyclability and diverse applications,which were unattainable by traditional systems.Concretely,the LP-TENG delivered appealing open circuit voltage of 250 V,short circuit current of 4μA and transferred charge of 120 nC with high stability,outperforming most advanced TENG systems.The LP-TENG was successfully employed for versatile applications with multifunctionality,including human motion detection,handwriting recognition,energy collection,message transmission and human-machine interaction.This work presents significant prospects for crafting advanced materials and devices in the fields of wearable electronics,flexible skin and smart robots.

Web GIS Human-Machine Interactive Interface Design with VISI

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.

Magnetic Array Assisted Triboelectric Nanogenerator Sensor for Real‑Time Gesture Interaction

In human-machine interaction,robotic hands are useful in many scenarios.To operate robotic hands via gestures instead of handles will greatly improve the convenience and intuition of human-machine interaction.Here,we present a magnetic array assisted sliding triboelectric sensor for achieving a real-time gesture interaction between a human hand and robotic hand.With a finger’s traction movement of flexion or extension,the sensor can induce positive/negative pulse signals.Through counting the pulses in unit time,the degree,speed,and direction of finger motion can be judged in realtime.The magnetic array plays an important role in generating the quantifiable pulses.The designed two parts of magnetic array can transform sliding motion into contact-separation and constrain the sliding pathway,respectively,thus improve the durability,low speed signal amplitude,and stability of the system.This direct quantization approach and optimization of wearable gesture sensor provide a new strategy for achieving a natural,intuitive,and real-time human-robotic interaction.

Human Interaction Dynamics for Its Use in Mobile Robotics:Impedance Control for Leader-follower Formation

A complete characterization of the behavior in human-robot interactions(HRI) includes both: the behavioral dynamics and the control laws that characterize how the behavior is regulated with the perception data. In this way, this work proposes a leader-follower coordinate control based on an impedance control that allows to establish a dynamic relation between social forces and motion error. For this, a scheme is presented to identify the impedance based on fictitious social forces, which are described by distance-based potential fields.As part of the validation procedure, we present an experimental comparison to select the better of two different fictitious force structures. The criteria are determined by two qualities: least impedance errors during the validation procedure and least parameter variance during the recursive estimation procedure.Finally, with the best fictitious force and its identified impedance,an impedance control is designed for a mobile robot Pioneer 3AT,which is programmed to follow a human in a structured scenario.According to results, and under the hypothesis that moving like humans will be acceptable by humans, it is believed that the proposed control improves the social acceptance of the robot for this kind of interaction.

Interaction and the Genesis of Experience: A Phenomenological Contribution for Meaningful Embodied Artificial Intelligence

In this article I will address the issue of the meaning of Embodied Artificial Intelligence(EAI)as it is configured today.My starting point is the refined interactive perspective on the semantics of EAI,as was recently suggested by Froese and colleagues.This perspective rests on the assumption that the concept of human bodily subjectivity must be extended to include meaning-making processes,which are enabled by advanced AI systems that may be incorporated in the human biological body.After having clarified the technical background,I will introduce the genetic component of the phenomenological method as a suitable tool to face the aforementioned issue.Towards this end,I will place the genetic method in the context of the so-called New Human-Machine Interaction(New HMI).I will further outline a genetic phenomenology of visual embodiment,suggesting a futuristic application based on the thesis of the“technological supplementation of phenomenological methodology”through the synthetic method.The case at stake is that of patients with a severe clinical picture characterised by the loss of corneal function,who in the near future could be treated with synthetic corneal prosthetic implants produced by a 3D bio-printing process by using an advanced EAI technique.I will conclude this article with a brief review of the main problems that still remain open.

褐飞虱和白背飞虱混合饲养中的共生细菌转移

【目的】探究褐飞虱Nilaparvata lugens和白背飞虱Sogatella furcifera的种间互作是否会导致其共生细菌的变化。【方法】分别对褐飞虱和白背飞虱进行单独饲养或混合饲养,并基于16S rRNA基因测序,分析不同饲养褐飞虱和白背飞虱种群共生细菌的多样性。【结果】混合饲养的与单独饲养的相比,褐飞虱和白背飞虱的共生菌群落结构均发生明显变化且具有趋同现象;混合饲养的褐飞虱共生细菌多样性比单独饲养的显著增加;褐飞虱中的133个扩增子序列变异(amplicon sequence variants,ASVs)和白背飞虱中的143个ASVs被定义为潜在的水平转移物种。【结论】褐飞虱和白背飞虱的种间互作改变了其共生细菌群落,研究结果为深入研究基于共生细菌的稻飞虱种间互作提供了新视角。

Recent advances in stretchable triboelectric nanogenerators for use in wearable bioelectronic devices

Wearable bioelectronic devices have the capacity for real-time human health monitoring,the provision of tailored services,and natural interaction with smart devices.However,these wearable bioelectronic devices rely on conventional rigid batteries that are frequently charged or replaced and are incompatible with the skin,leading to a discontinuity in complex therapeutic tasks related to human health monitoring and human-machine interaction.Stretchable triboelectric nanogenerator(TENG)is a high-efficiency energy harvesting technology that converts mechanical into electrical energy,effectively powering wearable bioelectronic devices.This study comprehensively overviews recent advances in stretchable TENG for use in wearable bioelectronic devices.The working mechanism of stretchable TENG is initially explained.A comprehensive discussion presents the approaches for fabricating stretchable TENG,including the design of stretchable structures and the selection of stretchable materials.Furthermore,applications of wearable bioelectronic devices based on stretchable TENG in human health monitoring(body movements,pulse,and respiration)and human-machine interaction(touch panels,machine control,and virtual reality)are introduced.Ultimately,the challenges and developmental trends regarding wearable bioelectronic devices based on stretchable TENG are elaborated.

“双碳”战略与新质生产力的耦合机制、要素解构与共生路径

新质生产力本身就是绿色生产力,因此作为加速推进国家能源绿色转型的关键部署,“双碳”战略与新质生产力具有显著的耦合共生关系。新质生产力发展为“双碳”战略进行核心技术绿色创新探寻新空间,“双碳”战略实施为新质生产力系统构建绿色经济政策体系铸就新基底。通过解构共生单元、共生模式、共生界面、共生环境等要素,本文从四个维度提出“双碳”战略与新质生产力的共生路径:聚合共生单元,激发多元主体的深度参与动力;创设共生模式,推动“双碳”战略与新质生产力的互惠共进;强化共生界面,打通绿色低碳发展与新质生产力的传输协同渠道;营造共生环境,构建绿色经济政策体系的制度优势,以此实现稳妥推进碳达峰碳中和、促进生产力系统性跃升的齐路并进。

A wave-shaped electrode flexible sensor capable of sensitively responding to wrinkle excitation for a multifunctional human-computer interaction system

Human-machine interactions(HMIs)have advanced rapidly in recent decades in the fields of healthcare,work,and life.However,people with disabilities and other mobility problems do not have corresponding high-tech aids for them to enjoy the convenience of HMIs.In this paper,we propose a sensor with a wave-shaped(corrugated)electrode embedded in a friction layer,which exhibits high sensitivity to skin fold excitation and enormous potential in HMIs.Attributing to the wave-shaped electrode design,it has no built-in cavities,and its small size allows it to flexibly cope with folds at different angles.By specifying the carbon nanotube hybrid silicone film as the electrode layer material and silicone film as the friction layer,good electrical output performance,tensile properties,and biocompatibility can be achieved.Then,the sensor is tested on various joints and skin folds of the human body,the output signals of which can be distinguished between normal physiological behavior and test behavior.Based on this sensor,we designed a medical alarm system,a robotic arm assistive system,and a cell phone application control system for the disabled to help them in the fields of healthcare,work,and life.In conclusion,our research presents a feasible technology to enhance HMIs and makes a valuable contribution to the development of high-tech aids for the disabled.

Machine learning and human‐machine trust in healthcare:A systematic survey

As human‐machine interaction(HMI)in healthcare continues to evolve,the issue of trust in HMI in healthcare has been raised and explored.It is critical for the development and safety of healthcare that humans have proper trust in medical machines.Intelligent machines that have applied machine learning(ML)technologies continue to penetrate deeper into the medical environment,which also places higher demands on intelligent healthcare.In order to make machines play a role in HMI in healthcare more effectively and make human‐machine cooperation more harmonious,the authors need to build good humanmachine trust(HMT)in healthcare.This article provides a systematic overview of the prominent research on ML and HMT in healthcare.In addition,this study explores and analyses ML and three important factors that influence HMT in healthcare,and then proposes a HMT model in healthcare.Finally,general trends are summarised and issues to consider addressing in future research on HMT in healthcare are identified.

关中地区传统村落的聚落发展与文化传承共生协调评价及交互作用研究

传统村落具有乡村聚落和活态遗产的特殊属性。以关中地区14座典型传统村落为研究对象,从共生视角出发,构建传统村落的聚落发展与文化传承共生协调评价指标体系并进行测度,采用K-modes聚类分析对传统村落进行类型划分,运用偏最小二乘回归分析聚落发展和文化传承之间的交互作用。结果表明:(1)案例村落的聚落发展与文化传承总体共生水平为“初级”,其中聚落发展与文化传承均处于较低水平,但文化传承的非均衡性更高。(2)人口活力不足、经济发展滞后是阻碍传统村落聚落发展的关键因素,物质空间保存度低、传统文化活化利用不足严重阻滞传统村落的文化传承。(3)案例村落一半以上是均衡共生型,其次是内化提升型,文旅主导型较少。(4)传统村落的聚落发展与文化传承对彼此有正向激励作用和反向抑制作用,其中正向激励作用更大。研究结果为传统村落的聚落发展与文化传承共生协调发展提供了理论基础和科技支撑。

当机器人也有体验时——人机共生体验的研究脉络、理论视角和未来研究

语音助理等智能机器的应用和普及,预示着人类已处于万物互联、实时交互的人机共生的数字生态系统中,这给所有参与者及其组合带来全新的体验,即人机共生体验(Human-machine Symbiosis Experience,简称HSX),是指在万物互联的人和机器共生的状态中,所有参与其中的各类主体即人、机器以及人和/或机器构成的各种组合实时交互后给这些主体带来的体验,这类体验具有实时性、涌现性、交互性和迭代性等特征。本文基于客户体验、人机共生的相关研究脉络、理论视角与机制研究的梳理,得出现有客户体验的理论视角包含消费者文化理论、价值共创理论和心流理论,已不足以涵盖HSX,且对HSX的形成机理和作用效能仍知之甚少,严重制约其作用的发挥。为此,本文基于人机共生相关客户体验理论即组合理论、涌现理论、螺旋理论,提出了人机共生体验的三个未来研究:①人机共生体验内涵及结构;②人机共生体验形成过程;③人机共生体验的作用机制。从而为人机共生体验理论在营销领域的发展提供未来研究方向。HSX蕴含的福利和经济价值随着“机器在与人以及彼此交互中拥有自己独特的能力和体验”而得到强化,在营造乐趣、启迪智慧、传播美感和转移关注基础上带来多元繁荣,为赋能经济发展、丰富人民生活作出贡献。

Human-machine interactive streaming anomaly detection by online self-adaptive forest

At nomaly detectors are used to distinguish differences between normal and abnormal data,which are usually implemented by evaluating and ranking the anomaly scores of each instance.A static unsupervised streaming anomaly detector is difficult to dynamically adjust anomaly score calculation.In real scenarios,anomaly detection often needs to be regulated by human feedback,which benefits adjusting anomaly detectors.In this paper,we propose a human-machine interactive streaming anomaly detection method,named ISPForest,which can be adaptively updated online under the guidance of human feedback.In particular,the feedback will be used to adjust the anomaly score calculation and structure of the detector,ideally attaining more accurate anomaly scores in the future.Our main contribution is to improve the tree-based streaming anomaly detection model that can be updated online from perspectives of anomaly score calculation and model structure.Our approach is instantiated for the powerful class of tree-based streaming anomaly detectors,and we conduct experiments on a range of benchmark datasets.The results demonstrate that the utility of incorporating feedback can improve the performance of anomaly detectors with a few human efforts.

Human-machine interaction force control: using a model-referenced adaptive impedance device to control an index finger exoskeleton

Exoskeleton robots and their control methods have been extensively developed to aid post-stroke rehabilitation. Most of the existing methods using linear controllers are designed for position control and are not suitable for human-machine interaction(HMI) force control, as the interaction system between the human body and exoskeleton is uncertain and nonlinear. We present an approach for HMI force control via model reference adaptive impedance control(MRAIC) to solve this problem in case of index finger exoskeleton control. First, a dynamic HMI model, which is based on a position control inner loop, is formulated. Second, the theoretical MRAC framework is implemented in the control system. Then, the adaptive controllers are designed according to the Lyapunov stability theory. To verify the performance of the proposed method, we compare it with a proportional-integral-derivative(PID) method in the time domain with real experiments and in the frequency domain with simulations. The results illustrate the effectiveness and robustness of the proposed method in solving the nonlinear HMI force control problem in hand exoskeleton.

Research of Natural Gesture Recognition and Interactive Technology Compatible with YCb Crand HSV Color Space

In view of the current gesture recognition algorithm based on skin color segmentation is not flexible and has weak resistance to the environment, this paper puts forward a new method of skin color modeling to improve the adaptability of gesture segmentation when it face to different states. The modeling built by double color space instead of only one is compatible both in YCbCr and HSV color space to training the Gaussian model which can update the threshold value for binarization. Finally, this paper designed a natural gesture recognition and interactive systems based on the double color space model. It has shown that the system has a good interactive experience in different environments.