scispace - formally typeset
Search or ask a question
JournalISSN: 2168-2291

IEEE Transactions on Human-Machine Systems 

Institute of Electrical and Electronics Engineers
About: IEEE Transactions on Human-Machine Systems is an academic journal published by Institute of Electrical and Electronics Engineers. The journal publishes majorly in the area(s): Computer science & Artificial intelligence. It has an ISSN identifier of 2168-2291. Over the lifetime, 810 publications have been published receiving 21964 citations.

Papers published on a yearly basis

Papers
More filters
Journal ArticleDOI
TL;DR: The resulting taxonomy incorporates all grasps found in the reviewed taxonomies that complied with the grasp definition and is shown that due to the nature of the classification, the 33 grasp types might be reduced to a set of 17 more generalgrasps if only the hand configuration is considered without the object shape/size.
Abstract: In this paper, we analyze and compare existing human grasp taxonomies and synthesize them into a single new taxonomy (dubbed “The GRASP Taxonomy” after the GRASP project funded by the European Commission). We consider only static and stable grasps performed by one hand. The goal is to extract the largest set of different grasps that were referenced in the literature and arrange them in a systematic way. The taxonomy provides a common terminology to define human hand configurations and is important in many domains such as human–computer interaction and tangible user interfaces where an understanding of the human is basis for a proper interface. Overall, 33 different grasp types are found and arranged into the GRASP taxonomy. Within the taxonomy, grasps are arranged according to 1) opposition type, 2) the virtual finger assignments, 3) type in terms of power, precision, or intermediate grasp, and 4) the position of the thumb. The resulting taxonomy incorporates all grasps found in the reviewed taxonomies that complied with the grasp definition. We also show that due to the nature of the classification, the 33 grasp types might be reduced to a set of 17 more general grasps if only the hand configuration is considered without the object shape/size.

636 citations

Journal ArticleDOI
TL;DR: This paper analyzes the most important requirements for an effective BSN-specific software framework, enabling efficient signal-processing applications and presents signal processing in node environment (SPINE), an open-source programming framework, designed to support rapid and flexible prototyping and management of BSN applications.
Abstract: Wireless body sensor networks (BSNs) possess enormous potential for changing people's daily lives. They can enhance many human-centered application domains such as m-Health, sport and wellness, and human-centered applications that involve physical/virtual social interactions. However, there are still challenging issues that limit their wide diffusion in real life: primarily, the programming complexity of these systems, due to the lack of high-level software abstractions, and the hardware constraints of wearable devices. In contrast with low-level programming and general-purpose middleware, domain-specific frameworks are an emerging programming paradigm designed to fulfill the lack of suitable BSN programming support with proper abstraction layers. This paper analyzes the most important requirements for an effective BSN-specific software framework, enabling efficient signal-processing applications. Specifically, we present signal processing in node environment (SPINE), an open-source programming framework, designed to support rapid and flexible prototyping and management of BSN applications. We describe how SPINE efficiently addresses the identified requirements while providing performance analysis on the most common hardware/software sensor platforms. We also report a few high-impact BSN applications that have been entirely implemented using SPINE to demonstrate practical examples of its effectiveness and flexibility. This development experience has notably led to the definition of a SPINE-based design methodology for BSN applications. Finally, lessons learned from the development of such applications and from feedback received by the SPINE community are discussed.

388 citations

Journal ArticleDOI
TL;DR: The human factors literature on intelligent systems was reviewed, and two key human performance issues related to H-A teaming for multirobot control and some promising user interface design solutions to address these issues were discussed.
Abstract: The human factors literature on intelligent systems was reviewed in relation to the following: efficient human supervision of multiple robots, appropriate human trust in the automated systems, maintenance of human operator's situation awareness, individual differences in human-agent (H-A) interaction, and retention of human decision authority. A number of approaches-from flexible automation to autonomous agents-were reviewed, and their advantages and disadvantages were discussed. In addition, two key human performance issues (trust and situation awareness) related to H-A teaming for multirobot control and some promising user interface design solutions to address these issues were discussed. Some major individual differences factors (operator spatial ability, attentional control ability, and gaming experience) were identified that may impact H-A teaming in the context of robotics control.

354 citations

Journal ArticleDOI
TL;DR: A comprehensive review of the complete systems, key techniques, and evaluation issues of brain-controlled mobile robots along with some insights into related future research and development issues is provided.
Abstract: EEG-based brain-controlled mobile robots can serve as powerful aids for severely disabled people in their daily life, especially to help them move voluntarily. In this paper, we provide a comprehensive review of the complete systems, key techniques, and evaluation issues of brain-controlled mobile robots along with some insights into related future research and development issues. We first review and classify various complete systems of brain-controlled mobile robots into two categories from the perspective of their operational modes. We then describe key techniques that are used in these brain-controlled mobile robots including the brain-computer interface techniques and shared control techniques. This description is followed by an analysis of the evaluation issues of brain-controlled mobile robots including participants, tasks and environments, and evaluation metrics. We conclude this paper with a discussion of the current challenges and future research directions.

324 citations

Journal ArticleDOI
TL;DR: This paper presents the basics of swarm robotics and introduces HSI from the perspective of a human operator by discussing the cognitive complexity of solving tasks with swarm systems and identifies the core concepts needed to design a human-swarm system.
Abstract: Recent advances in technology are delivering robots of reduced size and cost. A natural outgrowth of these advances are systems comprised of large numbers of robots that collaborate autonomously in diverse applications. Research on effective autonomous control of such systems, commonly called swarms, has increased dramatically in recent years and received attention from many domains, such as bioinspired robotics and control theory. These kinds of distributed systems present novel challenges for the effective integration of human supervisors, operators, and teammates that are only beginning to be addressed. This paper is the first survey of human–swarm interaction (HSI) and identifies the core concepts needed to design a human–swarm system. We first present the basics of swarm robotics. Then, we introduce HSI from the perspective of a human operator by discussing the cognitive complexity of solving tasks with swarm systems. Next, we introduce the interface between swarm and operator and identify challenges and solutions relating to human–swarm communication, state estimation and visualization, and human control of swarms. For the latter, we develop a taxonomy of control methods that enable operators to control swarms effectively. Finally, we synthesize the results to highlight remaining challenges, unanswered questions, and open problems for HSI, as well as how to address them in future works.

312 citations

Performance
Metrics
No. of papers from the Journal in previous years
YearPapers
2023136
2022209
202172
202058
201965
201863