The Impact of Human–Robot Interface Design on the Use of a Learning Robot System

Doisy, Guillaume; Meyer, Joachim; Edan, Yael

doi:10.1109/thms.2014.2331618

Cited by 19 publications

(10 citation statements)

References 21 publications

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“…However, continuous feedback could lead to presentation of too much information [41]. This can result in information overload and decrease the performance of the user [41].…”

Section: Introductionmentioning

confidence: 99%

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Robotic System for Physical Training of Older Adults

Avioz-Sarig

Olatunji

Sarne-Fleischmann

et al. 2020

Int J of Soc Robotics

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Physical exercise has many physical, psychological and social health benefits leading to improved life quality. This paper presents a robotic system developed as a personal coach for older adults aiming to motivate older adults to participate in physical activities. The robot instructs the participants, demonstrates the exercises and provides real-time corrective and positive feedback according to the participant’s performance as monitored by an RGB-D camera. Two robotic systems based on two different humanoid robots (Nao, toy-like and Poppy, mechanical-like) were developed and implemented using the Python programming language. Experimental studies with 32 older adults were conducted, to determine the preferable mode and timing of the feedback provided to the user to accommodate user preferences, motivate the users and improve their interaction with the system. Additionally, user preferences with regards to the two different humanoid robots used were explored. The results revealed that the system motivated the older adults to engage more in physical exercises. The type and timing of feedback influenced this engagement. Most of these older adults also perceived the system as very useful, easy to use, had a positive attitude towards the system and noted their intention to use it. Most users preferred the more mechanical looking robot (Poppy) over the toy-like robot (Nao).

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“…However, continuous feedback could lead to presentation of too much information [41]. This can result in information overload and decrease the performance of the user [41].…”

Section: Introductionmentioning

confidence: 99%

“…Continuous feedback proved to improve the trust of the user in the robot [ 39 , 40 ] and decrease the users’ workload [ 39 ]. However, continuous feedback could lead to presentation of too much information [ 41 ]. This can result in information overload and decrease the performance of the user [ 41 ].…”

Section: Introductionmentioning

confidence: 99%

Robotic System for Physical Training of Older Adults

Avioz-Sarig

Olatunji

Sarne-Fleischmann

et al. 2020

Int J of Soc Robotics

Self Cite

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“…The information presented must conform with perceptual and cognitive peculiarities of the users [10], [21], [22] and relate to the environment, task, and robot [20]. Too little information may not be sufficient to ensure reliable interaction with the robot [8], whereas too much may cause confusion and error [20].…”

Section: Related Workmentioning

confidence: 99%

“…several challenges remain [7]. A significant challenge is the lack of fit between user expectations of the robot and its capabilities and behavior [8], leading to an interaction gap. Overexpectations can cause older adults to overrely on the robot, misuse or abuse it [9].…”

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confidence: 99%

Levels of Automation and Transparency: Interaction Design Considerations in Assistive Robots for Older Adults

Olatunji

Oron-Gilad

Markfeld

et al. 2021

IEEE Trans. Human-Mach. Syst.

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It is important to encourage older adults to remain active when interacting with assistive robots. This study proposes a schematic model for integrating levels of automation (LOAs) and transparency (LoTs) in assistive robots to match the preferences and expectations of older adults. Metrics to evaluate LOA and LoT design combinations are defined. We develop two distinctive test cases to examine interaction design considerations for robots working for this population in everyday tasks: a person-following task with a mobile robot and a table-setting task with a robot manipulator. Evaluations in user studies with older adults reveal that LOA and LoT combinations influence interaction elements. Low LOA and high LoT encouraged activity engagement while receiving adequate information regarding the robot's behavior. The variety of objective and subjective metrics is essential to provide a holistic framework for evaluating the interaction. Index Terms-Assistive robots (ARs), human-robot interaction, interaction design, level of automation (LOA), level of transparency (LoT), older adults, socially ARs. I. BACKGROUNDT HE GLOBAL population of older adults (aged 65+) is increasing rapidly without commensurate growth in people that can support them [1]. This shortage is creating an eldercare gap in which the scarcity of caregivers, social support, and healthcare professionals has left many in this group facing many barriers in aging [2]. Assistive robots (ARs) can help reduce these barriers, facilitate independence, and promote more successful aging (e.g., [3]-[5]). While there has been progress in AR design and development for many daily applications [6],

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“…Previous researches have validated the effectivity of the use of the MYO Armband in obtaining sEMG signals from a user's forearm, which may be very useful in field such as rehabilitation and health. Another implementation is the Human-Robot Interaction (HRI); HRIs are robots that socially interact with humans and aid in day to day tasks, offer companionship, and offer assistance in health care and therapy [4]. An HRI robot called Pepper developed by SoftBank Robotics which falls under the category of Socially Assistive Robots (SAR) was evaluated in the study conducted by Barakeh et al (2019) [5]; and it was found that the implementation of an HRI robot, particularly Pepper, in airports, and hospitals were found to be more socially acceptable as compared to malls, and banks by people through a survey.…”

Section: Introductionmentioning

confidence: 99%

A Wearable MYO Gesture Armband Controlling Sphero BB-8 Robot

Chu

Chua

Secco

2020

HighTech. Innov. J.

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In this paper we present the development and preliminary validation of a wearable system which is combined with an algorithm interfacing the MYO gesture armband with a Sphero BB-8 robotic device. The MYO armband is a wearable device which measures real-time EMG signals of the end user’s forearm muscles as the user is executing a set of upper limb gestures. These gestures are interpreted and transmitted to a computing hardware via a Bluetooth Low Energy IEEE 802.15.1 wireless protocol. The algorithm analyzes and sorts the data and sends a set of commands to the Sphero robotic device while performing navigation movements. After designing and integrating the software and hardware architecture, we have validated the system with two sets of trials involving a series of commands performed in multiple iterations. The consequent reactions of the robots, due to these commands, were recorded and the performance of the system was analyzed in a confusion matrix to obtain an average accuracy of the system outcome vs. the expected and desired actions. Results show that our integrated system can satisfactorily interface with the system in an intuitive way with an accuracy rating of 85.7 % and 92.9 % for the two tests, respectively. Doi: 10.28991/HIJ-2020-01-04-05 Full Text: PDF

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The Impact of Human–Robot Interface Design on the Use of a Learning Robot System

Cited by 19 publications

References 21 publications

Robotic System for Physical Training of Older Adults

Robotic System for Physical Training of Older Adults

Levels of Automation and Transparency: Interaction Design Considerations in Assistive Robots for Older Adults

A Wearable MYO Gesture Armband Controlling Sphero BB-8 Robot

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