scholarly journals Research of HRV as a Measure of Mental Workload in Human and Dual-Arm Robot Interaction

Electronics ◽  
2020 ◽  
Vol 9 (12) ◽  
pp. 2174
Author(s):  
Shiliang Shao ◽  
Ting Wang ◽  
Yongliang Wang ◽  
Yun Su ◽  
Chunhe Song ◽  
...  
Keyword(s):  
Classification Accuracy ◽  
Mental Workload ◽  
Well Being ◽  
Human Robot Interaction ◽  
Direct Perception ◽  
Robot Interaction ◽  
Ecg Signals ◽  
Average Classification Accuracy ◽  
Dual Arm Robot ◽  
Dual Arm

Robots instead of humans work in unstructured environments, expanding the scope of human work. The interactions between humans and robots are indirect through operating terminals. The mental workloads of human increase with the lack of direct perception to the real scenes. Thus, mental workload assessment is important, which could effectively avoid serious accidents caused by mental overloading. In this paper, the operating object is a dual-arm robot. The classification of operator’s mental workload is studied by using the heart rate variability (HRV) signal. First, two kinds of electrocardiogram (ECG) signals are collected from six subjects who performed tasks or maintained a relaxed state. Then, HRV data is obtained from ECG signals and 20 kinds of HRV features are extracted. Last, six different classifications are used for mental workload classification. Using each subject’s HRV signal to train the model, the subject’s mental workload is classified. Average classification accuracy of 98.77% is obtained using the K-Nearest Neighbor (KNN) method. By using the HRV signal of five subjects for training and that of one subject for testing with the Gentle Boost (GB) method, the highest average classification accuracy (80.56%) is obtained. This study has implications for the analysis of HRV signals characteristic of mental workload in different subjects, which could improve operators’ well-being and safety in the human-robot interaction process.

scholarly journals Comparison Analysis of Different Time-Scale Heart Rate Variability Signals for Mental Workload Assessment in Human-Robot Interaction

2021 ◽  
Vol 2021 ◽  
pp. 1-12
Author(s):  
Shiliang Shao ◽  
Ting Wang ◽  
Yawei Li ◽  
Chunhe Song ◽  
Yihan Jiang ◽  
...  
Keyword(s):  
Heart Rate ◽  
Heart Rate Variability ◽  
Time Scales ◽  
Time Scale ◽  
Mental Workload ◽  
Human Robot Interaction ◽  
Machine Learning Algorithms ◽  
Robot Interaction ◽  
Ecg Signals ◽  
Different Time Scales

Excessive mental workload affects human health and may lead to accidents. This study is motivated by the need to assess mental workload in the process of human-robot interaction, in particular, when the robot performs a dangerous task. In this study, the use of heart rate variability (HRV) signals with different time scales in mental workload assessment was analyzed. A humanoid dual-arm robot that can perform dangerous work was used as a human-robot interaction object. Electrocardiogram (ECG) signals of six subjects were collected in two states: during the task and in a relaxed state. Multiple time-scale (1, 3, and 5 min) HRV signals were extracted from ECG signals. Then, we extracted the same linear and nonlinear features from the HRV signals at different time scales. The performance of machine learning algorithms using the different time-scale HRV signals obtained during the human-robot interaction was evaluated. The results show that for the per-subject case with a 3 min HRV signal length, the K -nearest neighbor classifier achieved the best mental workload classification performance. For the cross-subject case with a 5 min time-scale signal length, the gentle boost classifier achieved the best mental workload classification accuracy. This study provides a novel research idea for using HRV signals to measure mental workload during human-robot interaction.

scholarly journals Should my robot know what's best for me? Human–robot interaction between user experience and ethical design

AI & Society ◽  
2021 ◽  
Author(s):  
Nora Fronemann ◽  
Kathrin Pollmann ◽  
Wulf Loh
Keyword(s):  
User Experience ◽  
Interaction Design ◽  
Real Life ◽  
Well Being ◽  
Design Principles ◽  
Human Robot Interaction ◽  
Ethical Challenges ◽  
Original Design ◽  
Robot Interaction ◽  
Ethical Design

AbstractTo integrate social robots in real-life contexts, it is crucial that they are accepted by the users. Acceptance is not only related to the functionality of the robot but also strongly depends on how the user experiences the interaction. Established design principles from usability and user experience research can be applied to the realm of human–robot interaction, to design robot behavior for the comfort and well-being of the user. Focusing the design on these aspects alone, however, comes with certain ethical challenges, especially regarding the user’s privacy and autonomy. Based on an example scenario of human–robot interaction in elder care, this paper discusses how established design principles can be used in social robotic design. It then juxtaposes these with ethical considerations such as privacy and user autonomy. Combining user experience and ethical perspectives, we propose adjustments to the original design principles and canvass our own design recommendations for a positive and ethically acceptable social human–robot interaction design. In doing so, we show that positive user experience and ethical design may be sometimes at odds, but can be reconciled in many cases, if designers are willing to adjust and amend time-tested design principles.

scholarly journals Reports of the AAAI 2016 Spring Symposium Series

AI Magazine ◽  
2017 ◽  
Vol 37 (4) ◽  
pp. 83-88
Author(s):  
Christopher Amato ◽  
Ofra Amir ◽  
Joanna Bryson ◽  
Barbara Grosz ◽  
Bipin Indurkhya ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Intelligent Systems ◽  
Observational Studies ◽  
Human Error ◽  
Well Being ◽  
Human Robot Interaction ◽  
Robot Interaction ◽  
Symposium Series ◽  
Research Platform ◽  
Challenges And Opportunities

The Association for the Advancement of Artificial Intelligence, in cooperation with Stanford University's Department of Computer Science, presented the 2016 Spring Symposium Series on Monday through Wednesday, March 21-23, 2016 at Stanford University. The titles of the seven symposia were (1) AI and the Mitigation of Human Error: Anomalies, Team Metrics and Thermodynamics; (2) Challenges and Opportunities in Multiagent Learning for the Real World (3) Enabling Computing Research in Socially Intelligent Human-Robot Interaction: A Community-Driven Modular Research Platform; (4) Ethical and Moral Considerations in Non-Human Agents; (5) Intelligent Systems for Supporting Distributed Human Teamwork; (6) Observational Studies through Social Media and Other Human-Generated Content, and (7) Well-Being Computing: AI Meets Health and Happiness Science.

scholarly journals Assistive technology design and development for acceptable robotics companions for ageing years

2013 ◽  
Vol 4 (2) ◽  
Author(s):  
Farshid Amirabdollahian ◽  
Rieks op den Akker ◽  
Sandra Bedaf ◽  
Richard Bormann ◽  
Heather Draper ◽  
...  
Keyword(s):  
Home Environment ◽  
Technology Development ◽  
Sensor Arrays ◽  
Well Being ◽  
Human Robot Interaction ◽  
Robot Interaction ◽  
Technology Design ◽  
Novel Approach ◽  
Smart Home Environment ◽  
Technological Integration

AbstractA new stream of research and development responds to changes in life expectancy across the world. It includes technologies which enhance well-being of individuals, specifically for older people. The ACCOMPANY project focuses on home companion technologies and issues surrounding technology development for assistive purposes. The project responds to some overlooked aspects of technology design, divided into multiple areas such as empathic and social human-robot interaction, robot learning and memory visualisation, and monitoring persons’ activities at home. To bring these aspects together, a dedicated task is identified to ensure technological integration of these multiple approaches on an existing robotic platform, Care-O-Bot®3 in the context of a smart-home environment utilising a multitude of sensor arrays. Formative and summative evaluation cycles are then used to assess the emerging prototype towards identifying acceptable behaviours and roles for the robot, for example role as a butler or a trainer, while also comparing user requirements to achieved progress. In a novel approach, the project considers ethical concerns and by highlighting principles such as autonomy, independence, enablement, safety and privacy, it embarks on providing a discussion medium where user views on these principles and the existing tension between some of these principles, for example tension between privacy and autonomy over safety, can be captured and considered in design cycles and throughout project developments.

scholarly journals Impact of human-robot interaction on user satisfaction with humanoid-based healthcare

2018 ◽  
Vol 7 (2.12) ◽  
pp. 68
Author(s):  
Ohbyung Kwon ◽  
Jeonghun Kim ◽  
Yoonsun Jin ◽  
Namyeon Lee
Keyword(s):  
User Satisfaction ◽  
Healthcare Service ◽  
Empirical Test ◽  
Health Assessment ◽  
Well Being ◽  
Human Robot Interaction ◽  
Robot Interaction ◽  
The Difference ◽  
Self Service ◽  
Self Service Technology

Background/Objectives: The advent of self-service technology (SST) (e.g.,kiosks and Automatic Response System), has made it possible for service providersto make use of non-face-to-face channels to meet users’needs and decrease users’costs and time. On the other hand, however, more complex technology and/or services inhibit users’ satisfaction and,consequently,the intention to adopt SST, because such SST can instill fear in users. Nevertheless, at present, patients and other people who are interested in their own health and well-being are paying great attention to healthcare robots (as a form of SST)and,consequently, it has become crucial to investigate how these healthcare robots can positively influence users’ satisfaction with them. Hence, this study aims to empirically investigate the factors that affect users’ satisfaction with healthcare robots, especially in regard to human-robot interaction (HRI).Methods/Statistical analysis: We focused on the theory of heterophily and applied a series of factors identified in previous robot-adoption studies.Uniquely, this study focuses on users’ heterophily with healthcare robots, examining heterophily through three fundamental elements, empathy, professionalism, and personality, which we considered to be suitable fordetermining user satisfaction with HRI-based communication.To prove the validity of our hypotheses, we conducted an empirical testthat involved participants receiving a short health assessment from a robot.Findings: The findings of our empirical test supported our hypothesis that the lower the difference in empathy between a user and robot, the higher the level of user satisfaction with the humanoid-style healthcare service. Further, our results also suggest that heterogeneity between a user and healthcare robot is positively associated with user satisfaction.Improvements/Applications: First, to increase user satisfaction,robots must be provided with the ability to somehow recognizea user’s personality and adjust their own accordingly before beginning the robot-based healthcare service. Secondly, users’ behavior patterns should be analyzed by the healthcare robot. Overall, our study empirically shows the importance of ensuring thatprofessionalism is present in healthcare-domain-related HRI.  

scholarly journals Human-Robot Interaction with Drones and Drone Swarms in Law Enforcement Clearing Operations

2019 ◽  
Vol 63 (1) ◽  
pp. 1213-1217
Author(s):  
Richard T. Stone ◽  
Thomas M. Schnieders ◽  
Kevin A. Push ◽  
Stephen Terry ◽  
Mary Truong ◽  
...  
Keyword(s):  
Law Enforcement ◽  
Police Officers ◽  
Situational Awareness ◽  
Mental Workload ◽  
High Stress ◽  
Human Robot Interaction ◽  
Moderate Level ◽  
Robot Interaction ◽  
Mental Demand

Police officers often must work alone in clearing operations, a procedure that involves surveying a building for threats and appropriately responding. A partnership between drone swarms and officers has potential to increase the safety of officers and civilians during these high-stress operations and reduce the risk of harm from hostile persons. This two part study examines aspects of trust, situational awareness, mental demand, performance, and human-robot interaction during law enforcement building clearing operations using either a single drone or a drone swarm. Results indicate that single drone use can increase time for operation, but accuracy and safety of clearing is enhanced. Single drone use saw increased situational awareness, a decrease in number of targets missed, and a moderate level of trust. For drone swarms, results indicate significant differences in mental workload from swarm data feeds compared to single drone feeds but no substantial difference in accuracy of finding targets.

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