Personalized home-care support for the elderly: a field experience with a social robot at home

Napoli, Claudia Di; Ercolano, Giovanni; Rossi, Silvia

doi:10.1007/s11257-022-09333-y

Cited by 42 publications

(7 citation statements)

References 50 publications

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“…Such robots will also require the construction of personalized user models that the robot can learn and adapt over time through interaction with the OA (e.g. [ 62 , 63 ], with a focus on understanding the level and sources of the user’s ikigai and making relevant conversation, activities, and suggestions. A second function of an ikigai-supportive robot could be fostering connections for helping others.…”

Section: Discussionmentioning

confidence: 99%

Making Meaning Together: Co-designing a Social Robot for Older Adults with Ikigai Experts

Kamino

Hsu

Joshi

et al. 2023

Int J of Soc Robotics

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A sense of meaning and purpose in life–known in Japan as one’s ikigai –can lead to better health outcomes, an improved sense of well-being, and longer life as people age. The design of socially assistive robots, however, has so far focused largely on the more hedonic aims of supporting positive affect and happiness through interactions with robots. To explore how social robots might be able to support people’s ikigai, we performed (1) in-depth interviews with 12 ‘ikigai experts’ who formally support and/or study older adults (OAs)’ ikigai and (2) 5 co-design workshop sessions with 10 such experts. Our interview findings show that expert practitioners define ikigai in a holistic way in their everyday experience and practice, incorporating physical, social, and mental activities that relate not only to the individual and their behaviors, but also to their relationships with other people and to their connection with the broader community (3 levels of ikigai). Our co-design workshops showed that ikigai experts were overall positive towards the use of social robots to support OAs’ ikigai, particularly in the roles of an information-provider and social enabler that connects OAs to other people and activities in their communities. They also point out areas of potential risk, including the need to maintain OAs’ independence, relationships with others, and privacy, which should be considered in design. This research is the first to explore the co-design of social robots that can support people’s sense of ikigai–meaning and purpose–as they age.

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Section: Discussionmentioning

confidence: 99%

Making Meaning Together: Co-designing a Social Robot for Older Adults with Ikigai Experts

Kamino

Hsu

Joshi

et al. 2023

Int J of Soc Robotics

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“…During the experiments, users interact with the robot through the touchscreen. Technical details about the functioning and performance of the robotic platform used in the experimentation at home were analysed in [16].…”

Section: Methodsmentioning

confidence: 99%

Personality-Based Adaptation of Robot Behaviour: Acceptability Results on Individuals with Cognitive Impairments

Rossi,

Di Napoli,

Garramone

et al. 2023

Int J of Soc Robotics

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We performed a study to evaluate if the acceptance of a social humanoid robot used for monitoring the activities of elderly users with cognitive deficits increased after interacting with the robot. In addition, we evaluated if the robot’s acceptance is improved when the interaction with the robot occurred in different modalities modulated according to each user’s cognitive and personality profile. A group of 7 participants underwent assessment tools for cognitive and personality traits and for the level of acceptability of the robot. They interacted with the robot at their private home for a minimum of two weeks. The interaction with the robot occurred under two different modalities: standard modality where the robot performed tasks by approaching the subject at a fixed pre-defined frequency of interactions, and at fixed pre-defined times; modulated modality where the robot performed tasks by approaching the subject at different frequencies set according to some personality traits and cognitive profile of the user. The results showed no change in the acceptability level of the robot after direct interaction. Still, personality traits such as Neuroticism and Openness influenced the acceptability of the robot in the elderly only before an interaction. At the same time, these personality traits did not seem to influence the acceptability of the new technology after a direct interaction. Different is the case of cognitive profiles and demographic characteristics. Finally, the score on the pleasantness scale was higher when the interaction with the robot was set in modulated modality rather than standard modality. In conclusion, the identification of the personality traits and the cognitive status in the elderly with cognitive deficits seems to be useful to modulate the type and frequency of interaction of the robot with the user to increase the acceptability of the instrument and pleasures in every daily life.

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“…In recent years, knowledge-based systems have been utilized across diverse areas of real-world. These systems store and utilize structured information about the domain knowledge to assist humans in decision-making, learning, and other processes (Di Napoli et al, 2023;Mohamed et al, 2023). Therefore, knowledge-based systems prove beneficial in fields involving human presence and collaboration.…”

Section: Introductionmentioning

confidence: 99%

Ontology-based Activity Intention Recognition via Human-in-the-loop Framework

Heo,

Hwang,

Gong

et al. 2024

Preprint

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Human intention recognition is crucial for various human-centered settings.Existing approaches can be categorized into data-driven and knowledge-drivenmethods. While data-driven methods have shown promising performance withlarge training sets, they face challenges in data collection and limited interpretability.In contrast, knowledge-driven methods have the advantage of notrequiring training data and being interpretable, but acquiring high-qualitydomain knowledge is time-consuming and costly. To address these challenges,we propose OntoIR, a novel Ontology-based human activity Intention Recognitionsystem with a human-in-the-loop rule generation and refinement framework.OntoIR involves an ontology and human-guided logical rules to recognize humanactivities and intentions. By Leveraging rule mining model, the OntoIR extractscandidate rules enriches them with contextual information. Human experts thencurate meaningful rules and supplement insufficient context information. Thisallows us to obtain explainable human intention recognition results throughexpressive rules in situations where data is scarce. To evaluate our system,we collect an Activity/Intention recognition dataset, AICar, in a car showroomenvironment. Comprehensive experiments are conducted on the AICar,demonstrating that the collaboration of rule-mining models and domain expertsimproves the performance of activity intention recognition without lowering theinterpretability of recognition results.

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Personalized home-care support for the elderly: a field experience with a social robot at home

Cited by 42 publications

References 50 publications

Making Meaning Together: Co-designing a Social Robot for Older Adults with Ikigai Experts

Making Meaning Together: Co-designing a Social Robot for Older Adults with Ikigai Experts

Personality-Based Adaptation of Robot Behaviour: Acceptability Results on Individuals with Cognitive Impairments

Ontology-based Activity Intention Recognition via Human-in-the-loop Framework

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