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.

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.

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.

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.

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.

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.

Organizational Justice and Gender Equity:The Contingent Effect of Islamic Work Ethics

Organizations are facing challenges to cope with gender equity in the presence of a diverse workforce.The present study investigates the moderating impact of Islamic work ethics on the organizational justicegender equity relationship.Self-administered questionnaires were sent to employees working in a large private university in a State of Qatar.This study collected data from 250 employees with 66.12%response rate.The present study employed structural equation modelling to analyse data in SmartPLS 3.0 and SPSS version 24.Empirical findings revealed the significant relationship of distributive justice and interactional justice with gender equity.Procedural justice did not relate to gender equity.Furthermore,Islamic work ethics also moderated the relationship of interactional justice with gender equity.Limitations and implications have been added at the end of paper.This study is first in its nature revealing the conditional factor of Islamic work ethics on the organizational justicegender equity relationship.

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.

A Rapid Adaptation Approach for Dynamic Air‑Writing Recognition Using Wearable Wristbands with Self‑Supervised Contrastive Learning

Wearable wristband systems leverage deep learning to revolutionize hand gesture recognition in daily activities.Unlike existing approaches that often focus on static gestures and require extensive labeled data,the proposed wearable wristband with selfsupervised contrastive learning excels at dynamic motion tracking and adapts rapidly across multiple scenarios.It features a four-channel sensing array composed of an ionic hydrogel with hierarchical microcone structures and ultrathin flexible electrodes,resulting in high-sensitivity capacitance output.Through wireless transmission from a Wi-Fi module,the proposed algorithm learns latent features from the unlabeled signals of random wrist movements.Remarkably,only few-shot labeled data are sufficient for fine-tuning the model,enabling rapid adaptation to various tasks.The system achieves a high accuracy of 94.9%in different scenarios,including the prediction of eight-direction commands,and air-writing of all numbers and letters.The proposed method facilitates smooth transitions between multiple tasks without the need for modifying the structure or undergoing extensive task-specific training.Its utility has been further extended to enhance human–machine interaction over digital platforms,such as game controls,calculators,and three-language login systems,offering users a natural and intuitive way of communication.

Artificial Intelligence in Healthcare and Medicine:Promises,Ethical Challenges and Governance

Artificial intelligence (AI) is rapidly being applied to a wide range of fields,including medicine,and has been considered as an approach that may augment or substitute human professionals in primary healthcare.However,AI also raises several challenges and ethical concerns.In this article,the author investigates and discusses three aspects of AI in medicine and healthcare:the application and promises of AI,special ethical concerns pertaining to AI in some frontier fields,and suggestive ethical governance systems.Despite great potentials of frontier AI research and development in the field of medical care,the ethical challenges induced by its applications has put forward new requirements for governance.To ensure “trustworthy” AI applications in healthcare and medicine,the creation of an ethical global governance framework and system as well as special guidelines for frontier AI applications in medicine are suggested.The most important aspects include the roles of governments in ethical auditing and the responsibilities of stakeholders in the ethical governance system.

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.

High-performance optical noncontact controlling system based on broadband PtTex/Si heterojunction photodetectors for human-machine interaction

Noncontact interaction systems have attracted considerable research attention in recent years because of convenient operation,sterility,and injury prevention.However,the insufficient sensing distance and weak robustness of noncontact interaction systems for complex environments limit their practical applications.Here,we designed an integrated optical noncontact controlling system(ONCS)based on PtTe_(x)/Si optoelectronic heterojunction array.Broadband sensitive photoresponse is realized at zero bias voltage,with excellent detectivity and responsivity,boosting the noncontact sensing distance to at least 150 mm.Consequently,the system can perform noncontact detection,encoding,and control by recognizing shadow-induced spatiotemporal sequence changes in heterojunction array photocurrents.As a proof of concept,different interactive functions have been demonstrated with good accuracy and robustness by encoding finger movement above the ONCS.This study provides a new perspective for constructing high-performance noncontact interaction systems.

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.

生成式人工智能驱动教育变革的路径探索

生成式人工智能正在深刻改变教育领域,通过其强大的数据处理和模型学习能力,推动个性化教学和教育资源的普及。生成式人工智能能够生成多种形式的新内容,展现出卓越的创造性和适应性,有望解决教育资源分配不均和个性化教学难题。然而,其在应用过程中也面临教育公平性和隐私保护的挑战。可汗学院和清华大学的案例展示了生成式人工智能在实现因材施教、提升教学效率和改善学习体验方面的实际应用。为实现教育变革,需推进课程的跨学科融合、建立AI通识课程、创新评估方式,并推广个性化学习系统,以引领未来教育的发展。

理解学生:符号伦理意蕴及其实现路径

教育是一种特殊的交往实践。理解学生既是教育交往得以展开的前提,也是教育交往中师生对话的关键所在。以符号伦理学的角度审视,理解学生的符号伦理意蕴在于:理解学生是对教育交往中学生交往符号的意义阐释,是对学生精神世界的关怀,是面向学生(他者)的责任担当。实践中,教师在理解学生方面存在诸多不当,集中表现在忽视符号之于学生个体的“感官意义”差异,漠视学生作为符号表达者的“意愿意义”,轻视符号活动中“道德意义”显现的复杂性,等等。从有利于促进和实现教育交往出发,教师要真正做到理解学生,必须充分关注教育交往中理解学生的符号伦理意蕴,通过关怀式倾听、负责任回应、允许性沉默等促进自身对学生的理解,从而担负起教师作为伦理主体的责任。

小学教师课堂互动决策的伦理考量探析——基于眼动追踪的数据

教学是极具伦理意义的专业实践,特别是在小学教育中,教师教学过程中的伦理性体现尤为重要。目前对教学过程中的伦理研究大多数仍停留在“应然”的层次,本研究以教师在真实课堂佩戴眼动仪所获得的眼动数据为基础,整合视频分析、教师课后访谈及教师评定学生表现的量表数据,对小学教师课堂视觉关注及互动决策的伦理性进行了探析。研究发现,教师在整个课堂教学中的视觉关注具有公平性,教师的互动决策与学生表现特征具有一定的相关性,而这种相关性与教师的伦理考量关系密切。本研究从伦理理论之结果论的视角出发,发展出“教师利益—学生利益”与“集体利益—个体利益”的二维分析框架,并以此对教师课堂互动决策过程中的伦理考量进行了分析。

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.