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Local Domain Adaptation for Cross-Domain Activity Recognition IEEE Trans. Hum. Mach. Syst. (IF 3.374) Pub Date : 2020-12-09 Jiachen Zhao; Fang Deng; Haibo He; Jie Chen
Sensor-based human activity recognition (HAR) aims to recognize a human's physical actions by using sensors attached to different body parts. As a user-specific application, HAR often suffers poor generalization from training on an individual to testing on another individual, or from one body part to another body part. To tackle this cross-domain HAR problem, this article proposes a domain adaptation
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A Comparison of Expert Ratings and Marker-Less Hand Tracking Along OSATS-Derived Motion Scales IEEE Trans. Hum. Mach. Syst. (IF 3.374) Pub Date : 2020-12-08 David P. Azari; Brady L. Miller; Brian V. Le; Jacob A. Greenberg; Reginald C. Bruskewitz; Kristin L. Long; Guanhua Chen; Robert G. Radwin
Objective: This study creates linear and generalized additive models (GAMs) of video-recorded two-dimensional hand motion (synonymously referred to as hand movements or hand kinematics) to predict expert-rated performance along a series of surgical motion scales. Background : Surgical performance assessments are costly and time consuming. Automatically quantifying hand motion may offload some burden
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Gesture-Radar: A Dual Doppler Radar Based System for Robust Recognition and Quantitative Profiling of Human Gestures IEEE Trans. Hum. Mach. Syst. (IF 3.374) Pub Date : 2020-11-20 Zhu Wang; Zhiwen Yu; Xinye Lou; Bin Guo; Liming Chen
Gesture recognition is key to enabling natural human–computer interactions. Existing approaches based on wireless sensing focus on accurate identification of arm gesture types. It remains a challenge to recognize and profile the details of arm gestures for precise interaction control. In addition, current approaches have strict positioning requirements between radars and users, making them difficult
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Hand Gesture Recognition Using Multiple Acoustic Measurements at Wrist IEEE Trans. Hum. Mach. Syst. (IF 3.374) Pub Date : 2020-12-31 Nabeel Siddiqui; Rosa H. M. Chan
This article investigates the use of acoustic signals recorded at the human wrist for hand gesture recognition. The prototype consists of 40 microphones to be worn at the wrist. The gesture recognition performance is evaluated through the identification of 36 gestures in American sign language (ASL), including 26 ASL alphabetical characters and 10 ASL numbers. The optimal area for sensor band placement
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Table of Contents IEEE Trans. Hum. Mach. Syst. (IF 3.374) Pub Date : 2020-11-19
Presents the table of contents for this issue of the publication.
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IEEE Systems, Man, and Cybernetics Society IEEE Trans. Hum. Mach. Syst. (IF 3.374) Pub Date : 2020-11-19
Presents a listing of the editorial board, board of governors, current staff, committee members, and/or society editors for this issue of the publication.
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A Review of Shared Control for Automated Vehicles: Theory and Applications IEEE Trans. Hum. Mach. Syst. (IF 3.374) Pub Date : 2020-09-22 Mauricio Marcano; Sergio Díaz; Joshué Pérez; Eloy Irigoyen
The last decade has shown an increasing interest on advanced driver assistance systems (ADAS) based on shared control, where automation is continuously supporting the driver at the control level with an adaptive authority. A first look at the literature offers two main research directions: 1) an ongoing effort to advance the theoretical comprehension of shared control, and 2) a diversity of automotive
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An AI-Based Visual Aid With Integrated Reading Assistant for the Completely Blind IEEE Trans. Hum. Mach. Syst. (IF 3.374) Pub Date : 2020-10-20 Muiz Ahmed Khan; Pias Paul; Mahmudur Rashid; Mainul Hossain; Md Atiqur Rahman Ahad
Blindness prevents a person from gaining knowledge of the surrounding environment and makes unassisted navigation, object recognition, obstacle avoidance, and reading tasks a major challenge. In this work, we propose a novel visual aid system for the completely blind. Because of its low cost, compact size, and ease-of-integration, Raspberry Pi 3 Model B+ has been used to demonstrate the functionality
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Analysis of Driving Patterns and On-Board Feedback-Based Training for Proactive Road Safety Monitoring IEEE Trans. Hum. Mach. Syst. (IF 3.374) Pub Date : 2020-10-19 Laura Pozueco; Nishu Gupta; Xabiel G. Pañeda; Roberto García; Alejandro G. Tuero; David Melendi; Abel Rionda; Víctor Corcoba
Road accidents and safe driving are one of the main concerns of transportation systems and the companies that explore different solutions to reduce the accident rate. The most interesting option to achieve this goal is through an on-board training of professional drivers to apply safe driving techniques during their work activity. The purpose of this study is to analyze a monitoring system that is
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Evaluation of a Predictor-Based Framework in High-Speed Teleoperated Military UGVs IEEE Trans. Hum. Mach. Syst. (IF 3.374) Pub Date : 2020-09-16 Yingshi Zheng; Mark J. Brudnak; Paramsothy Jayakumar; Jeffrey L. Stein; Tulga Ersal
Mobility of teleoperated unmanned ground vehicles can be significantly compromised under large communication delays, if the delays are not compensated. This article considers a recently developed delay compensation theory and presents its first empirical evaluation in improving mobility and drivability of a high-speed teleoperated vehicle under large delays. The said delay compensation theory is a
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An Empirical Approach to Modeling User-System Interaction Conflicts in Smart Homes IEEE Trans. Hum. Mach. Syst. (IF 3.374) Pub Date : 2020-09-29 Fereshteh Jadidi Miandashti; Mohammad Izadi; Ali Asghar Nazari Shirehjini; Shervin Shirmohammadi
Conflict is one of the important factors affecting user satisfaction and trust in smart environments, yet conflict modeling in mixed initiative smart environments has not been sufficiently explored. Most of the existing literature on conflict in smart homes are centered on conflicts between users. Although research has shown that about 75% of conflicts are between users and system [1] , only a few
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The HoloLens Augmented Reality System Provides Valid Measures of Gait Performance in Healthy Adults IEEE Trans. Hum. Mach. Syst. (IF 3.374) Pub Date : 2020-10-01 Mandy Miller Koop; Anson B. Rosenfeldt; Joshua D. Johnston; Matthew C. Streicher; Jingan Qu; Jay L. Alberts
Biomechanical measures are the gold standard in the assessment of gait in healthy and chronic disease populations. Augmented reality (AR) systems represent an opportunity to evaluate human movement under more realistic and interactive conditions. A barrier to integrating AR into healthcare is the unknown accuracy of systems in the quantification of human movement. This project aimed to determine the
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Two-Dimensional Fingertip Force Training With Improved Haptic Sensation via Stochastic Resonance IEEE Trans. Hum. Mach. Syst. (IF 3.374) Pub Date : 2020-10-02 Komi Chamnongthai; Takahiro Endo; Fumitoshi Matsuno; Kenta Fujimoto; Marina Kosaka
To learn motor skills using a finger in many haptic training systems, a user places his or her finger in a holder to communicate with a haptic interface. It is known that the force-detection capability at the fingertip is reduced when the user's finger is enclosed in a holder. The learning performance might therefore be impaired in training. Stochastic resonance is known to improve sensitivity at the
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3-D Interface for the P300 Speller BCI IEEE Trans. Hum. Mach. Syst. (IF 3.374) Pub Date : 2020-09-16 Saman Noorzadeh; Bertrand Rivet; Christian Jutten
A brain–computer interface (BCI) is a common device for communication between the human brain and a computer. This article investigates the efficiency of using a 3-D interface for BCI machines. For this purpose, the P300 speller, which is a BCI device that enables the user to spell characters on a screen using brain waves, is modified. The classical virtual keyboard of the P300 speller is replaced
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Inherent Kinematic Features of Dynamic Bimanual Path Following Tasks IEEE Trans. Hum. Mach. Syst. (IF 3.374) Pub Date : 2020-09-15 Jacob R. Boehm; Nicholas P. Fey; Ann Majewicz
Bimanual coordination is critical in many robotic and haptic systems, such as surgical robots and rehabilitation robots. While these systems often incorporate two robotic manipulators for each limb, there may be a missed opportunity to leverage overarching models of human bimanual coordination to improve the way in which the robotic manipulators are controlled and respond to the dynamic human operator
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Organizing Audible Alarm Sounds in the Hospital: A Card-Sorting Study IEEE Trans. Hum. Mach. Syst. (IF 3.374) Pub Date : 2020-09-14 Melanie C. Wright; Sydney Radcliffe; Suzanne Janzen; Judy Edworthy; Thomas J. Reese; Noa Segall
In hospitals, clinicians are presented with varied and disorganized alarm sounds from disparate devices. While there has been attention to reducing inactionable alarms to address alarm overload, little effort has been focused on organizing, simplifying, or improving the informativeness of alarms. In this article, we sought to elicit nurses' tacit interpretation of alarm events to create an organizational
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Share Your Preprint Research with the World! IEEE Trans. Hum. Mach. Syst. (IF 3.374) Pub Date : 2020-11-19
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Call for Papers: Human Interaction with Artificial Intelligence Systems IEEE Trans. Hum. Mach. Syst. (IF 3.374) Pub Date : 2020-11-19
Prospective authors are requested to submit new, unpublished manuscripts for inclusion in the upcoming event described in this call for papers.
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2020 Index IEEE Transactions on Human-Machine Systems Vol. 50 IEEE Trans. Hum. Mach. Syst. (IF 3.374) Pub Date : 2020-11-19
Presents the 2020 subject/author index for this publication.
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IEEE Systems, Man, and Cybernetics Society Information IEEE Trans. Hum. Mach. Syst. (IF 3.374) Pub Date : 2020-11-19
Presents a listing of the editorial board, board of governors, current staff, committee members, and/or society editors for this issue of the publication.
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Information for Authors IEEE Trans. Hum. Mach. Syst. (IF 3.374) Pub Date : 2020-11-19
These instructions give guidelines for preparing papers for this publication. Presents information for authors publishing in this journal.
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An Adaptive General Type-2 Fuzzy Logic Approach for Psychophysiological State Modeling in Real-Time Human–Machine Interfaces IEEE Trans. Hum. Mach. Syst. (IF 3.374) Pub Date : 2020-10-20 Changjiang He; Mahdi Mahfouf; Luis A. Torres-Salomao
In this article, a new type-2 fuzzy-based modeling approach is proposed to assess human operators’ psychophysiological states for both safety and reliability of human–machine interface systems. Such a new modeling technique combines type-2 fuzzy sets with state tracking to update the rule base through a Bayesian process. These new configurations successfully lead to an adaptive, robust, and transparent
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Table of Contents IEEE Trans. Hum. Mach. Syst. (IF 3.374) Pub Date : 2020-09-15
Presents the table of contents for this issue of the publication.
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IEEE Transactions on Human-Machine Systems publication information IEEE Trans. Hum. Mach. Syst. (IF 3.374) Pub Date : 2020-09-15
Presents a listing of the editorial board, board of governors, current staff, committee members, and/or society editors for this issue of the publication.
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Hierarchical Eye-Tracking Data Analytics for Human Fatigue Detection at a Traffic Control Center IEEE Trans. Hum. Mach. Syst. (IF 3.374) Pub Date : 2020-08-28 Fan Li; Chun-Hsien Chen; Gangyan Xu; Li-Pheng Khoo
Eye-tracking-based human fatigue detection at traffic control centers suffers from an unavoidable problem of low-quality eye-tracking data caused by noisy and missing gaze points. In this article, the authors conducted pioneering work by investigating the effects of data quality on eye-tracking-based fatigue indicators and by proposing a hierarchical-based interpolation approach to extract the eye-tracking-based
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IEEE Systems, Man, and Cybernetics Society Information IEEE Trans. Hum. Mach. Syst. (IF 3.374) Pub Date : 2020-09-15
Presents a listing of the editorial board, board of governors, current staff, committee members, and/or society editors for this issue of the publication.
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IEEE Transactions on Human-Machine Systems information for authors IEEE Trans. Hum. Mach. Syst. (IF 3.374) Pub Date : 2020-09-15
These instructions give guidelines for preparing papers for this publication. Presents information for authors publishing in this journal.
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Techniques for Constructing Indoor Navigation Systems for the Visually Impaired: A Review IEEE Trans. Hum. Mach. Syst. (IF 3.374) Pub Date : 2020-09-07 Roya Norouzi Kandalan; Kamesh Namuduri
Sight is an important sensory input for humans to navigate their surrounding environment independently. Tasks that are simple for the sighted are often difficult for a visually impaired person. Throughout the years, many researchers dedicated their time and efforts to design and implement technologies and devices that can help a visually impaired person to navigate in unknown areas independently. An
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Automated Analysis of the Origin of Movement: An Approach Based on Cooperative Games on Graphs IEEE Trans. Hum. Mach. Syst. (IF 3.374) Pub Date : 2020-09-07 Ksenia Kolykhalova; Giorgio Gnecco; Marcello Sanguineti; Gualtiero Volpe; Antonio Camurri
In this work, a computational method is proposed to automatically investigate the perception of the origin of full-body human movement and its propagation. The method is based on a mathematical game built over a suitably defined graph structure representing the human body. The players of this game are the graph vertices, which form a subset of body joints. Since each vertex contributes to a shared
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Facial Expression Imitation Method for Humanoid Robot Based on Smooth-Constraint Reversed Mechanical Model (SRMM) IEEE Trans. Hum. Mach. Syst. (IF 3.374) Pub Date : 2020-09-03 Zhong Huang; Fuji Ren; Min Hu; Sugen Chen
To improve the space–time similarity and motion smoothness of facial expression imitation (FEI), a real-time FEI method for a humanoid robot is proposed based on smooth-constraint reversed mechanical model (SRMM) by combining a sequence-to-sequence deep learning model and a motion-smoothing constraint. First, on the basis of facial data from a Kinect capture device, a facial feature vector is characterized
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Characteristics of Recovery Motion Resulting From Side Contact With a Physical Assistant Robot Worn During Gait IEEE Trans. Hum. Mach. Syst. (IF 3.374) Pub Date : 2020-09-01 Yasuhiro Akiyama; Ryota Kushida; Shogo Okamoto; Yoji Yamada
Although a wearable assist robot helps to enhance the gait ability of the wearer, it can cause gait instability in an emergency. A collision with an environmental object is one source of such instability. Insufficient adaptation to change by the physical frame, and restriction of joint motion, increases the risk of collision and fall of the wearer owing to the robot. In this article, the reaction motion
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Table of Contents IEEE Trans. Hum. Mach. Syst. (IF 3.374) Pub Date : 2020-07-14
Presents the table of contents for this issue of the publication.
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IEEE Transactions on Human-Machine Systems publication information IEEE Trans. Hum. Mach. Syst. (IF 3.374) Pub Date : 2020-07-14
Presents a listing of the editorial board, board of governors, current staff, committee members, and/or society editors for this issue of the publication.
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A Usability Study of Low-Cost Wireless Brain-Computer Interface for Cursor Control Using Online Linear Model IEEE Trans. Hum. Mach. Syst. (IF 3.374) Pub Date : 2020-05-14 Reza Abiri; Soheil Borhani; Justin Kilmarx; Connor Esterwood; Yang Jiang; Xiaopeng Zhao
Computer cursor control using electroencephalogram (EEG) signals is a common and well-studied brain-computer interface (BCI). The emphasis of the literature has been primarily on evaluation of the objective measures of assistive BCIs such as accuracy of the neural decoder whereas the subjective measures such as user's satisfaction play an essential role for the overall success of a BCI. As far as we
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Cross-Modality Matching for Evaluating User Experience of Emerging Mobile EEG Technology IEEE Trans. Hum. Mach. Syst. (IF 3.374) Pub Date : 2020-06-01 Thea Radüntz; Beate Meffert
Emerging technology for brain-state monitoring offers the possibility to conduct measurements outside the laboratory. However, user-experience research is lacking. In this article, we present and test an approach for determining the development of user experience in the course of time using the so-called cross-modality matching (CMM). We conducted experiments with 24 subjects and evaluated seven mobile
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A Comparative Evaluation of a Virtual Reality Table and a HoloLens-Based Augmented Reality System for Anatomy Training IEEE Trans. Hum. Mach. Syst. (IF 3.374) Pub Date : 2020-06-02 Ramiro Serrano Vergel; Pedro Morillo Tena; Sergio Casas Yrurzum; Carolina Cruz-Neira
Anatomy training with real cadavers poses many practical problems for which new training and educational solutions have been developed making use of technologies based on real-time 3-D graphics. Although virtual reality (VR) and augmented reality (AR) have been previously used in the medical field, it is not easy to select the right 3-D technology or setup for each particular problem. For this reason
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Connect. Support. Inspire. IEEE Trans. Hum. Mach. Syst. (IF 3.374) Pub Date : 2020-07-14
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IEEE Foundation Realize the Full Potential of IEEE IEEE Trans. Hum. Mach. Syst. (IF 3.374) Pub Date : 2020-07-14
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Present a world of opportunity IEEE Trans. Hum. Mach. Syst. (IF 3.374) Pub Date : 2020-07-14
Advertisement.
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IEEE Systems, Man, and Cybernetics Society Information IEEE Trans. Hum. Mach. Syst. (IF 3.374) Pub Date : 2020-07-14
Presents a listing of the editorial board, board of governors, current staff, committee members, and/or society editors for this issue of the publication.
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IEEE Transactions on Human-Machine Systems information for authors IEEE Trans. Hum. Mach. Syst. (IF 3.374) Pub Date : 2020-07-14
These instructions give guidelines for preparing papers for this publication. Presents information for authors publishing in this journal.
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Estimating an LPV Model of Driver Neuromuscular Admittance Using Grip Force as Scheduling Variable IEEE Trans. Hum. Mach. Syst. (IF 3.374) Pub Date : 2020-06-17 Anne J. Pronker; David A. Abbink; Marinus M. van Paassen; Max Mulder
Humans can rapidly change their low-frequency arm dynamics to resist forces or give way to them. Quantifying driver time-varying arm dynamics is important to develop steer-by-wire and haptic support systems. Conventional linear time-invariant (LTI) identification, and even time-varying techniques such as wavelets, fail to capture fast changing dynamics. Moreover, such techniques require perturbation
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Physiological Synchrony Revealed by Delayed Coincidence Count: Application to a Cooperative Complex Environment IEEE Trans. Hum. Mach. Syst. (IF 3.374) Pub Date : 2020-06-15 Kevin J. Verdière; Mélisande Albert; Frédéric Dehais; Raphaëlle N. Roy
Synchrony at the physiological level is an objective measure that can be used to investigate cooperation between human agents. This physiological synchrony has been experimentally observed in different dyadic contexts through measures of the autonomous system such as cardiac measures. Various metrics are used to characterize synchrony between participants such as cross-correlation, weighted coherence
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Reciprocity and Its Neurological Correlates in Human-Agent Cooperation IEEE Trans. Hum. Mach. Syst. (IF 3.374) Pub Date : 2020-06-09 Jiahao Li; Shen Dong; Erin K. Chiou; Jie Xu
Reciprocal cooperation is prevalent in human society. Understanding human reciprocal cooperation in human-agent interaction can help design human-agent systems that promote cooperation and joint performance. Studies have found that people reciprocate cooperative behavior when interacting with computer agents in social dilemma games. However, few studies have investigated human reciprocal cooperation
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Agreement Study Using Gesture Description Analysis IEEE Trans. Hum. Mach. Syst. (IF 3.374) Pub Date : 2020-06-01 Naveen Madapana; Glebys Gonzalez; Lingsong Zhang; Richard Rodgers; Juan Wachs
Choosing adequate gestures for touchless interfaces is a challenging task that has a direct impact on human–computer interaction. Such gestures are commonly determined by the designer, ad-hoc, rule-based, or agreement-based methods. Previous approaches to assess agreement grouped the gestures into equivalence classes and ignored the integral properties that are shared between them. In this article
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Human Threshold Model for Perceiving Changes in System Dynamics IEEE Trans. Hum. Mach. Syst. (IF 3.374) Pub Date : 2020-05-25 Wei Fu; M. M. van Paassen; Max Mulder
Limitations of a haptic device can cause distortions of the force feedback it presents. Just-noticeable difference (JND) in system dynamics is important for creating transparent haptic interaction. Based on the previous work, this article presents a unified model that extends the existing JND rule. Our approach projects the JNDs in the mechanical properties of a second-order mass-spring-damper system
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Demand-Driven Transparency for Monitoring Intelligent Agents IEEE Trans. Hum. Mach. Syst. (IF 3.374) Pub Date : 2020-05-20 Mor Vered; Piers Howe; Tim Miller; Liz Sonenberg; Eduardo Velloso
In autonomous multiagent or multirobotic systems, the ability to quickly and accurately respond to threats and uncertainties is important for both mission outcomes and survivability. Such systems are never truly autonomous, often operating as part of a human-agent team. Artificial intelligent agents (IAs) have been proposed as tools to help manage such teams; e.g., proposing potential courses of action
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Musculoskeletal Model for Path Generation and Modification of an Ankle Rehabilitation Robot IEEE Trans. Hum. Mach. Syst. (IF 3.374) Pub Date : 2020-05-12 Prashant K. Jamwal; Shahid Hussain; Yun H. Tsoi; Sheng Q. Xie
While newer designs and control approaches are being proposed for rehabilitation robots, vital information from the human musculoskeletal system should also be considered. Incorporating knowledge about joint biomechanics during the development of robot controllers can enhance the safety and performance of robot-aided treatments. In this article, the optimal path or trajectories of a parallel ankle
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Finding a Secure Place: A Map-Based Crowdsourcing System for People With Autism IEEE Trans. Hum. Mach. Syst. (IF 3.374) Pub Date : 2020-04-30 Amon Rapp; Federica Cena; Claudio Schifanella; Guido Boella
People with autism have idiosyncratic sensory experiences, which may impact on how they live the “spaces” of their everyday life. Starting from an investigation of their conception and experience of “secure places,” we defined a series of user requirements for designing technology that supports their everyday movements in the urban environment. On the basis of such requirements, we developed an interactive
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Statistical Modeling of Visual Attention of Junior and Senior Anesthesiologists During the Induction of General Anesthesia in Real and Simulated Cases IEEE Trans. Hum. Mach. Syst. (IF 3.374) Pub Date : 2020-04-30 Tobias Grundgeiger; Thomas Wurmb; Oliver Happel
In visually rich working environments, it is important for operators to distribute their visual attention in an optimal fashion in order to operate safely. Computational models can provide a systematic method of investigating the attention distribution of humans. In this article, we reanalyze eye tracking data from anesthesiologists when inducing general anesthesia to test whether the so-called expectancy
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The Effect of Room Complexity on Physical Object Selection Performance in 3-D Mobile User Interfaces IEEE Trans. Hum. Mach. Syst. (IF 3.374) Pub Date : 2020-04-30 Maryam Rezaie; Morteza Malekmakan; Ali Asghar Nazari Shirehjini; Shervin Shirmohammadi
An important challenge in smart environments is how to manipulate the smart objects. Although mobile applications are typically used for controlling a smart environment, no previous study has evaluated the users performance in manipulating smart objects under different environmental complexities. This article presents an experimental comparison between three different selection techniques 3-D, 2-D
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A Smartphone-Based Adaptive Recognition and Real-Time Monitoring System for Human Activities IEEE Trans. Hum. Mach. Syst. (IF 3.374) Pub Date : 2020-04-24 Wen Qi; Hang Su; Andrea Aliverti
Human activity recognition (HAR) using smartphones provides significant healthcare guidance for telemedicine and long-term treatment. Machine learning and deep learning (DL) techniques are widely utilized for the scientific study of the statistical models of human behaviors. However, the performance of existing HAR platforms is limited by complex physical activity. In this article, we proposed an adaptive
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Performance of a Steady-State Visual Evoked Potential and Eye Gaze Hybrid Brain-Computer Interface on Participants With and Without a Brain Injury IEEE Trans. Hum. Mach. Syst. (IF 3.374) Pub Date : 2020-04-24 Chris Brennan; Paul McCullagh; Gaye Lightbody; Leo Galway; Sally McClean; Piotr Stawicki; Felix Gembler; Ivan Volosyak; Elaine Armstrong; Eileen Thompson
The brain–computer interface (BCI) and the tracking of eye gaze provide modalities for human–machine communication and control. In this article, we provide the evaluation of a collaborative BCI and eye gaze approach, known as a hybrid BCI. The combined inputs interact with a virtual environment to provide actuation according to a four-way menu system. The following two approaches are evaluated: first
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Table of Contents IEEE Trans. Hum. Mach. Syst. (IF 3.374) Pub Date : 2020-03-13
Presents the table of contents for this issue of the publication.
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IEEE Transactions on Human-Machine Systems publication information IEEE Trans. Hum. Mach. Syst. (IF 3.374) Pub Date : 2020-03-13
Presents a listing of the editorial board, board of governors, current staff, committee members, and/or society editors for this issue of the publication.
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Brain–Computer Interface Software: A Review and Discussion IEEE Trans. Hum. Mach. Syst. (IF 3.374) Pub Date : 2020-02-12 Pierce Stegman; Chris S. Crawford; Marvin Andujar; Anton Nijholt; Juan E. Gilbert
Software is a critical component of brain–computer interfaces (BCIs). While BCI hardware enables the retrieval of brain signals, BCI software is required to analyze these signals, produce output, and provide feedback. Users from multiple research areas have adopted BCI software platforms to investigate various concepts. Recently, interest in web-based BCI software has also emerged. The system design
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State of the Art in Bionic Hands IEEE Trans. Hum. Mach. Syst. (IF 3.374) Pub Date : 2020-02-20 Hirakjyoti Basumatary; Shyamanta M. Hazarika
Prosthetic hands have made a significant influence on the quality of life of people with upper arm amputation. Research on prosthetic hands today is focused on replicating the functionalities of the biological hands. The present article provides a bibliometric survey on bionic hands, done through a compilation of a scientific publications database on the field of prosthetic hands spanning the last
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Review of Human–Machine Interfaces for Small Unmanned Systems With Robotic Manipulators IEEE Trans. Hum. Mach. Syst. (IF 3.374) Pub Date : 2020-02-24 Sierra N. Young; Joshua M. Peschel
This article reviews the human–machine interaction (HMI) technologies used for telemanipulation by small unmanned systems (SUS) with remote manipulators. SUS, including land, air, and sea vehicles, can perform a wide range of reconnaissance and manipulation tasks with varying levels of autonomy. SUS operations involving physical interactions with the environment require some level of operator involvement