The Humanoid Robot NAO as Trainer in a Memory Program for Elderly People with Mild Cognitive Impairment

Pino, Olimpia; Palestra, Giuseppe; Trevino, Rosalinda; Carolis, Berardina De

doi:10.1007/s12369-019-00533-y

Cited by 78 publications

(99 citation statements)

References 26 publications

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“…Schneider et al [8] reported that SARs can have positive effects on user's performance on cognitive tasks and that the task is perceived as pleasurable if the robot's feedback is appropriate to the user's task processing. Moreover, in a recent study, Pino et al [7] found that robot-based cognitive training produced an improvement of cognitive functions in individuals with mild cognitive impairment. The abovementioned studies evaluated the feasibility of a psychometric assessment administered by the robot and the performance compared to no-robot conditions.…”

Section: Related Workmentioning

confidence: 97%

“…Positive effects on performance with robot coaches have been shown, for example, in improving physical exercise [4] or promoting users' behavior changes in the role of a weight loss coach [5] and in post-stroke rehabilitation [6]. Moreover, in the case of older people, the presence of a robot can provide personalized cognitive interventions that involve guided practice of standard tasks to increase or maintain particular cognitive functions such as memory [7,8].…”

Section: Introductionmentioning

confidence: 99%

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“Don’t Get Distracted!”: The Role of Social Robots’ Interaction Style on Users’ Cognitive Performance, Acceptance, and Non-Compliant Behavior

Maggi

Dell’Aquila

Cucciniello

et al. 2020

Int J of Soc Robotics

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Social robots are developed to provide companionship and assistance in the daily life of the children, older, and disable people but also have great potential as educational technology by facilitating learning. In these application areas, a social robot can take the role of a coach by training and assisting individuals also in cognitive tasks. Since a robot’s interaction style affects users’ trust and acceptance, customizing its behavior to the proposed tasks could, potentially, have an impact on the users’ performance. To investigate these phenomena, we enrolled sixty volunteers and endowed a social robot with a friendly and an authoritarian interaction style. The aim was to explore whether and how the robot’s interaction style could enhance users’ cognitive performance during a psychometric evaluation. The results showed that the authoritarian interaction style seems to be more appropriate to improve the performance when the tasks require high cognitive demands. These differences in cognitive performance between the groups did not depend on users’ intrinsic characteristics, such as gender and personality traits. Nevertheless, in the authoritarian condition, participants’ cognitive performance was related to their trust and the acceptance of the technology. Finally, we found that users’ non-compliant behavior was not related to their personality traits. This finding indirectly supports the role of the robot’s interaction style in influencing the compliance behavior of the users.

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Section: Related Workmentioning

confidence: 97%

Section: Introductionmentioning

confidence: 99%

“Don’t Get Distracted!”: The Role of Social Robots’ Interaction Style on Users’ Cognitive Performance, Acceptance, and Non-Compliant Behavior

Maggi

Dell’Aquila

Cucciniello

et al. 2020

Int J of Soc Robotics

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“…In this work, we presented JESSIE, an end-to-end system that affords control synthesis techniques to enable novice programmers to generate high-level behaviors for a social robot. Robots have shown great potential to support people with MCI [27,72], and this system will extend the scalability, accessibility, and personalization of social robots. Additionally, this paper presents the first evaluation by possible end-users of a system whose back-end employs control synthesis layered with a tangible front-end.…”

Section: Resultsmentioning

confidence: 99%

Jessie

Kubota

Peterson

Rajendren

et al. 2020

Proceedings of the 2020 ACM/IEEE International Conference on Human-Robot Interaction

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JESSIE is a robotic system that enables novice programmers to program social robots by expressing high-level specifications. We employ control synthesis with a tangible front-end to allow users to define complex behavior for which we automatically generate control code. We demonstrate JESSIE in the context of enabling clinicians to create personalized treatments for people with mild cognitive impairment (MCI) on a Kuri robot, in little time and without error. We evaluated JESSIE with neuropsychologists who reported high usability and learnability. They gave suggestions for improvement, including increased support for personalization, multi-party programming, collaborative goal setting, and re-tasking robot role post-deployment, which each raise technical and sociotechnical issues in HRI. We exhibit JESSIE's reproducibility by replicating a clinician-created program on a TurtleBot 2. As an open-source means of accessing control synthesis, JESSIE supports reproducibility, scalability, and accessibility of personalized robots for HRI. CCS CONCEPTS • Computer systems organization → Robotic control; • Applied computing → Health informatics.

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“…It was estimated [43] that people with MCI vs. healthy older adults have triple the risk of being diagnosed with Alzheimer's dementia within 2-5 years. Delaying the appearing of dementia one year could decrease the number of the Alzheimer's patients by 9 million in 2050 [40].…”

Section: Introductionmentioning

confidence: 99%

“…positive or negative) in different tasks in order to see whether participants are positively engaged during interaction or not. Our research addresses affective expression in human-robot interactions exploiting video clips recorded during the 2-month of the previous study and analyzing facial expressions from the participants [43].…”

Section: Introductionmentioning

confidence: 99%

Detecting emotions during a memory training assisted by a social robot for individuals with Mild Cognitive Impairment (MCI)

Palestra¹,

Pino

2020

Multimed Tools Appl

Self Cite

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The attention towards robot-assisted therapies (RAT) had grown steadily in recent years particularly for patients with dementia. However, rehabilitation practice using humanoid robots for individuals with Mild Cognitive Impairment (MCI) is still a novel method for which the adherence mechanisms, indications and outcomes remain unclear. An effective computing represents a wide range of technological opportunities towards the employment of emotions to improve human-computer interaction. Therefore, the present study addresses the effectiveness of a system in automatically decode facial expression from video-recorded sessions of a robot-assisted memory training lasted two months involving twenty-one participants. We explored the robot’s potential to engage participants in the intervention and its effects on their emotional state. Our analysis revealed that the system is able to recognize facial expressions from robot-assisted group therapy sessions handling partially occluded faces. Results indicated reliable facial expressiveness recognition for the proposed software adding new evidence base to factors involved in Human-Robot Interaction (HRI). The use of a humanoid robot as a mediating tool appeared to promote the engagement of participants in the training program. Our findings showed positive emotional responses for females. Tasks affects differentially affective involvement. Further studies should investigate the training components and robot responsiveness.

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The Humanoid Robot NAO as Trainer in a Memory Program for Elderly People with Mild Cognitive Impairment

Cited by 78 publications

References 26 publications

“Don’t Get Distracted!”: The Role of Social Robots’ Interaction Style on Users’ Cognitive Performance, Acceptance, and Non-Compliant Behavior

“Don’t Get Distracted!”: The Role of Social Robots’ Interaction Style on Users’ Cognitive Performance, Acceptance, and Non-Compliant Behavior

Jessie

Detecting emotions during a memory training assisted by a social robot for individuals with Mild Cognitive Impairment (MCI)

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