Typology
operator:
and / or
Language
operator:
and / or
Date
operator:
and / or
Rights
operator:
and / or
2025
Other
Open Access
Personalised serious games with humanoid robots for older adults cognitive training
Canapa G., Catricalà B., Manca M., Paternò F., Santoro C., Zedda E.
This paper outlines the experiences in the SERENI project concerning the development and evolution of a humanoid robot-based platform for personalized cognitive training aimed at supporting older adults with cognitive decline . Using a humanoid robot and the Remind web application [1], the platform developed tailor serious games to users' personal memories. Iterative improvements introduced adaptive difficulty, diverse robot personalities, and AI-driven personalization to enhance user engagement, inclusivity, and empowerment. Findings highlight the importance of personalization and adaptability in fostering emotional connection, active participation, and a sense of empowerment for users, demonstrating the potential of humanoid robots to support cognitive health in aging populations.Project(s): SERious gamEs with humanoi robots in cogNItive training
Canapa G., Catricalà B., Manca M., Paternò F., Santoro C., Zedda E.
This paper outlines the experiences in the SERENI project concerning the development and evolution of a humanoid robot-based platform for personalized cognitive training aimed at supporting older adults with cognitive decline . Using a humanoid robot and the Remind web application [1], the platform developed tailor serious games to users' personal memories. Iterative improvements introduced adaptive difficulty, diverse robot personalities, and AI-driven personalization to enhance user engagement, inclusivity, and empowerment. Findings highlight the importance of personalization and adaptability in fostering emotional connection, active participation, and a sense of empowerment for users, demonstrating the potential of humanoid robots to support cognitive health in aging populations.Project(s): SERious gamEs with humanoi robots in cogNItive training
See at:
CNR IRIS 
| r4h-workshop.github.io | CNR IRIS 
2025
Conference article
Open Access
Pepper-based serious games for older adults: initial experiences in real-world settings (short paper)
Canapa G., Catricalà B., Manca M., Paternò F., Santoro C., Zedda E.
Social robotics for supporting cognitive stimulation of older adults has been investigated in recent years but it has not been adopted in the real world. To better understand how it can be deployed in such settings, we have carried out a trial in a healthcare residence. A set of games able to automatically personalise their interactions according to user memories has been designed and implemented in a Pepper robot. The games aim to stimulate cognitive resources such as memory and attention. In this paper, we introduce the approach proposed, how it has been proposed in a residential health care facility for older adults, and discuss the initial feedback received.Source: CEUR WORKSHOP PROCEEDINGS, vol. 3957, pp. 465-473. Cagliari, Italy, 24/03/2025
Project(s): SERious gamEs with humanoi robots in cogNItive training
Canapa G., Catricalà B., Manca M., Paternò F., Santoro C., Zedda E.
Social robotics for supporting cognitive stimulation of older adults has been investigated in recent years but it has not been adopted in the real world. To better understand how it can be deployed in such settings, we have carried out a trial in a healthcare residence. A set of games able to automatically personalise their interactions according to user memories has been designed and implemented in a Pepper robot. The games aim to stimulate cognitive resources such as memory and attention. In this paper, we introduce the approach proposed, how it has been proposed in a residential health care facility for older adults, and discuss the initial feedback received.Source: CEUR WORKSHOP PROCEEDINGS, vol. 3957, pp. 465-473. Cagliari, Italy, 24/03/2025
Project(s): SERious gamEs with humanoi robots in cogNItive training
See at:
ceur-ws.org | CNR IRIS | CNR IRIS
2025
Other
Open Access
ISTI-day 2025 Proceedings
Del Corso G., Pedrotti A., Federico G., Gennaro C., Carrara F., Amato G., Di Benedetto M., Gabrielli E., Belli D., Matrullo Z., Miori V., Tolomei G., Waheed T., Marchetti E., Calabrò A., Rossetti G., Stella M., Cazabet R., Abramski K., Cau E., Citraro S., Failla A., Mesina V., Morini V., Pansanella V., Colantonio S., Germanese D., Pascali M. A., Bianchi L., Messina N., Falchi F., Barsellotti L., Pacini G., Cassese M., Puccetti G., Esuli A., Volpi L., Moreo A., Sebastiani F., Sperduti G., Nguyen D., Broccia G., Ter Beek M. H., Ferrari A., Massink M., Belmonte G., Ciancia V., Papini O., Canapa G., Catricalà B., Manca M., Paternò F., Santoro C., Zedda E., Gallo S., Maenza S., Mattioli A., Simeoli L., Rucci D., Carlini E., Dazzi P., Kavalionak H., Mordacchini M., Rulli C., Muntean Cristina Ioana, Nardini F. M., Perego R., Rocchietti G., Lettich F., Renso C., Pugliese C., Casini G., Haldimann J., Meyer T., Assante M., Candela L., Dell'Amico A., Frosini L., Mangiacrapa F., Oliviero A., Pagano P., Panichi G., Peccerillo B., Procaccini M., Mannocci A., Manghi P., Lonetti F., Kang D., Di Giandomenico F., Jee E., Lazzini G., Conti F., Scopigno R., D'Acunto M., Moroni D., Cafiso M., Paradisi P., Callieri M., Pavoni G., Corsini M., De Falco A., Sala F., Saraceni Q., Gattiglia G.
ISTI-Day is an annual information and networking event organized by the Institute of Information Science and Technologies "A. Faedo" (ISTI) of the Italian National Research Council (CNR). This event features an opening talk of the Director of the Dept. DIITET (Emilio F. Campana) as well as an overview of the Institute's activities presented by the ISTI Director (Roberto Scopigno). Those institutional segments are complemented by dedicated presentations and round tables featuring former staff members, as well as internal and external collaborators. To foster a network of knowledge and collaboration among newcomers, the 2025 ISTI Day edition also includes a large poster session that provides a comprehensive overview of current research activities. Each of the 13 laboratories contributes 1–3 posters, highlighting the most innovative work and offering early-career researchers a platform for discussion. Thus these proceedings include the posters selected for ISTI-Day 2025, reflecting the diverse and innovative nature of the Institute's research.
Del Corso G., Pedrotti A., Federico G., Gennaro C., Carrara F., Amato G., Di Benedetto M., Gabrielli E., Belli D., Matrullo Z., Miori V., Tolomei G., Waheed T., Marchetti E., Calabrò A., Rossetti G., Stella M., Cazabet R., Abramski K., Cau E., Citraro S., Failla A., Mesina V., Morini V., Pansanella V., Colantonio S., Germanese D., Pascali M. A., Bianchi L., Messina N., Falchi F., Barsellotti L., Pacini G., Cassese M., Puccetti G., Esuli A., Volpi L., Moreo A., Sebastiani F., Sperduti G., Nguyen D., Broccia G., Ter Beek M. H., Ferrari A., Massink M., Belmonte G., Ciancia V., Papini O., Canapa G., Catricalà B., Manca M., Paternò F., Santoro C., Zedda E., Gallo S., Maenza S., Mattioli A., Simeoli L., Rucci D., Carlini E., Dazzi P., Kavalionak H., Mordacchini M., Rulli C., Muntean Cristina Ioana, Nardini F. M., Perego R., Rocchietti G., Lettich F., Renso C., Pugliese C., Casini G., Haldimann J., Meyer T., Assante M., Candela L., Dell'Amico A., Frosini L., Mangiacrapa F., Oliviero A., Pagano P., Panichi G., Peccerillo B., Procaccini M., Mannocci A., Manghi P., Lonetti F., Kang D., Di Giandomenico F., Jee E., Lazzini G., Conti F., Scopigno R., D'Acunto M., Moroni D., Cafiso M., Paradisi P., Callieri M., Pavoni G., Corsini M., De Falco A., Sala F., Saraceni Q., Gattiglia G.
ISTI-Day is an annual information and networking event organized by the Institute of Information Science and Technologies "A. Faedo" (ISTI) of the Italian National Research Council (CNR). This event features an opening talk of the Director of the Dept. DIITET (Emilio F. Campana) as well as an overview of the Institute's activities presented by the ISTI Director (Roberto Scopigno). Those institutional segments are complemented by dedicated presentations and round tables featuring former staff members, as well as internal and external collaborators. To foster a network of knowledge and collaboration among newcomers, the 2025 ISTI Day edition also includes a large poster session that provides a comprehensive overview of current research activities. Each of the 13 laboratories contributes 1–3 posters, highlighting the most innovative work and offering early-career researchers a platform for discussion. Thus these proceedings include the posters selected for ISTI-Day 2025, reflecting the diverse and innovative nature of the Institute's research.
See at:
CNR IRIS | www.isti.cnr.it | CNR IRIS
2025
Journal article
Open Access
Adaptive humanoid robot behaviour in a serious game scenario through reinforcement learning
Zedda E., Manca M., Paternò F., Santoro C.
The study presents an adaptive technique that enables a humanoid robot to select appropriate actions to maintain the engagement level of users while they play a serious game for cognitive training. The goal is to design and develop an adaptation strategy for changing the robot's behaviour based on Reinforcement Learning (RL) to encourage the user to remain engaged. Initially, we trained the algorithm in a simulated environment before moving on to a real user experiment. Thus, we first design, develop, and validate the RL strategy in a simulated environment. Subsequently, we integrate the trained policy into the robotic system, allowing it to select the best actions based on the detected user state during real user test. The RL algorithm was designed and implemented to determine an effective adaptation strategy for the robot's actions, encompassing verbal and non-verbal interactions. The proposed solution was first trained in a simulated environment and then tested with 28 users in a mixed-method design study.Source: BEHAVIOUR & INFORMATION TECHNOLOGY, pp. 1-26
DOI: 10.1080/0144929x.2025.2456068
Project(s): SERious gamEs with humanoi robots in cogNItive training
Metrics:
Zedda E., Manca M., Paternò F., Santoro C.
The study presents an adaptive technique that enables a humanoid robot to select appropriate actions to maintain the engagement level of users while they play a serious game for cognitive training. The goal is to design and develop an adaptation strategy for changing the robot's behaviour based on Reinforcement Learning (RL) to encourage the user to remain engaged. Initially, we trained the algorithm in a simulated environment before moving on to a real user experiment. Thus, we first design, develop, and validate the RL strategy in a simulated environment. Subsequently, we integrate the trained policy into the robotic system, allowing it to select the best actions based on the detected user state during real user test. The RL algorithm was designed and implemented to determine an effective adaptation strategy for the robot's actions, encompassing verbal and non-verbal interactions. The proposed solution was first trained in a simulated environment and then tested with 28 users in a mixed-method design study.Source: BEHAVIOUR & INFORMATION TECHNOLOGY, pp. 1-26
DOI: 10.1080/0144929x.2025.2456068
Project(s): SERious gamEs with humanoi robots in cogNItive training
Metrics:
2025
Journal article
Open Access
Exploiting personal memories in humanoid robot serious games for mild cognitive impaired older adults
Catricalà B., Manca M., Paternò F., Sale A., Santoro C., Zedda E.
The use of humanoid robots in older adult training has recently started to be considered. We investigated a solution that offers serious games personalised to each individual, to stimulate more interest and participation in cognitive training. In particular, we have studied how to consider personal memories in customising humanoid robot games for Mild Cognitive Impaired (MCI) older adults. For this goal, a prototype platform for collecting and exploiting personal memories in associated games is presented. The memories are exploited by six games designed and implemented in a Pepper robot considering current practices. We report on a mixed-method study consisting of a two-phase trial that involved 15 MCI older adults. The participants first furnished some memories from their past, and then used two game versions regularly for twelve weeks, one personalised and one with general content. We collected both quantitative (through questionnaires and interaction log analysis) and qualitative feedback. The results provide useful information about the robot games’ impact on users and, more generally, for understanding how to introduce robot games based on personal memories in cognitive training programmes.Source: BEHAVIOUR & INFORMATION TECHNOLOGY, pp. 1-26
DOI: 10.1080/0144929x.2025.2484647
Project(s): Ageing Well in an Ageing Society, SERious gamEs with humanoi robots in cogNItive training, Tuscany Health Ecosystem
Metrics:
Catricalà B., Manca M., Paternò F., Sale A., Santoro C., Zedda E.
The use of humanoid robots in older adult training has recently started to be considered. We investigated a solution that offers serious games personalised to each individual, to stimulate more interest and participation in cognitive training. In particular, we have studied how to consider personal memories in customising humanoid robot games for Mild Cognitive Impaired (MCI) older adults. For this goal, a prototype platform for collecting and exploiting personal memories in associated games is presented. The memories are exploited by six games designed and implemented in a Pepper robot considering current practices. We report on a mixed-method study consisting of a two-phase trial that involved 15 MCI older adults. The participants first furnished some memories from their past, and then used two game versions regularly for twelve weeks, one personalised and one with general content. We collected both quantitative (through questionnaires and interaction log analysis) and qualitative feedback. The results provide useful information about the robot games’ impact on users and, more generally, for understanding how to introduce robot games based on personal memories in cognitive training programmes.Source: BEHAVIOUR & INFORMATION TECHNOLOGY, pp. 1-26
DOI: 10.1080/0144929x.2025.2484647
Project(s): Ageing Well in an Ageing Society, SERious gamEs with humanoi robots in cogNItive training, Tuscany Health Ecosystem
Metrics:
See at:
CNR IRIS | www.tandfonline.com | CNR IRIS | CNR IRIS | CNR IRIS
2025
Conference article
Open Access
Humanoid robot personalised serious games in an older adults’ care center
Canapa G., Catricalà B., Manca M., Paternò F., Santoro C., Zedda E.
Most countries are ageing rapidly, creating significant challenges in providing adequate care to elderly population. Older adults’ care centers face several difficulties in ensuring support able to address their diverse needs, due to several factors including increasing caregiver shortages, high variability in cognitive and health conditions of elderly, and challenges in delivering personalized interventions to them. Additionally, maintaining elderly engagement during cognitive training is often problematic due to the repetitive and impersonal nature of involved tasks. To address these limitations, we carried out a study investigating the use of a humanoid robot to deliver interactive, personalised serious games based on older adults' personal memories, to enhance relevance and engagement for them. The approach has been evaluated in a trial conducted in a center for older adults, involving users with varying cognitive abilities. Results indicated that such personalised games were well received by them, with a positive impact on their experience.DOI: 10.1109/ro-man63969.2025.11217838
Project(s): SERious gamEs with humanoi robots in cogNItive training
Metrics:
Canapa G., Catricalà B., Manca M., Paternò F., Santoro C., Zedda E.
Most countries are ageing rapidly, creating significant challenges in providing adequate care to elderly population. Older adults’ care centers face several difficulties in ensuring support able to address their diverse needs, due to several factors including increasing caregiver shortages, high variability in cognitive and health conditions of elderly, and challenges in delivering personalized interventions to them. Additionally, maintaining elderly engagement during cognitive training is often problematic due to the repetitive and impersonal nature of involved tasks. To address these limitations, we carried out a study investigating the use of a humanoid robot to deliver interactive, personalised serious games based on older adults' personal memories, to enhance relevance and engagement for them. The approach has been evaluated in a trial conducted in a center for older adults, involving users with varying cognitive abilities. Results indicated that such personalised games were well received by them, with a positive impact on their experience.DOI: 10.1109/ro-man63969.2025.11217838
Project(s): SERious gamEs with humanoi robots in cogNItive training
Metrics:
2024
Conference article
Open Access
Train the Brain with SERENI
Catricalà B., Manca M., Paternò F., Santoro C., Zedda E.
One way to address cognitive decline in ageing is the use of serious games delivered through humanoid robots, to provide engaging ways to perform exercises to train memory, attention, processing, and planning activities. We present an approach in which a humanoid robot, by using various modalities, proposes the games in a way personalised to specific individuals’ experiences using their personal memories associated with facts and events that occurred in older adults’ lives. We discuss how such an approach has been deployed in a trial and how we plan to extend it in a new trial.Source: CEUR WORKSHOP PROCEEDINGS, vol. 3794. Arenzano, Italy, 4/06/2024
Project(s): Sereni
Catricalà B., Manca M., Paternò F., Santoro C., Zedda E.
One way to address cognitive decline in ageing is the use of serious games delivered through humanoid robots, to provide engaging ways to perform exercises to train memory, attention, processing, and planning activities. We present an approach in which a humanoid robot, by using various modalities, proposes the games in a way personalised to specific individuals’ experiences using their personal memories associated with facts and events that occurred in older adults’ lives. We discuss how such an approach has been deployed in a trial and how we plan to extend it in a new trial.Source: CEUR WORKSHOP PROCEEDINGS, vol. 3794. Arenzano, Italy, 4/06/2024
Project(s): Sereni
See at:
ceur-ws.org | CNR IRIS | CNR IRIS
2024
Conference article
Open Access
Robots for Humans (RfH 2024) - Embracing human-centred robot design
Cocchella F., Eldardeer O., Manca M., Matarese M., Rezzani A., Zedda E.
The "Robots for Humans" (RfH) workshop bridges the HumanComputer Interaction (HCI) and Human-Robot Interaction (HRI) communities. The workshop encourages methodological exchange and explores theoretical, technical and design solutions in robotics. Join us to explore the intricate bond between humans and robots for thoughtful HRI advancements.DOI: 10.1145/3656650.3660535
Metrics:
Cocchella F., Eldardeer O., Manca M., Matarese M., Rezzani A., Zedda E.
The "Robots for Humans" (RfH) workshop bridges the HumanComputer Interaction (HCI) and Human-Robot Interaction (HRI) communities. The workshop encourages methodological exchange and explores theoretical, technical and design solutions in robotics. Join us to explore the intricate bond between humans and robots for thoughtful HRI advancements.DOI: 10.1145/3656650.3660535
Metrics:
See at:
IRIS Cnr | doi.org | IRIS Cnr | doi.org | CNR IRIS | CNR IRIS
2024
Contribution to book
Open Access
Preface for the 1st edition of the international Robots for Humans (RfH) workshop
Cocchella F., Eldardeer O., Manca M., Mattarese M., Rezzani A., Zedda E.
In recent years, the research field of Human-Robot Interaction has become crucial to understanding and designing the technological future. New methods and approaches in this field are urgently needed to meet the challenges of a rapidly changing landscape. In this workshop, we proposed that the intersection between Human-Computer Interaction (HCI) and HumanRobot Interaction (HRI) offers methodological opportunities while highlighting the new challenges that robot integration into society will face. In this perspective, humans bridge society, computers, and robots. Thus, the workshop proposed reflections on how embracing a human-centred design approach can help prioritise people's empowerment in society and collaborate with robots.Source: CEUR WORKSHOP PROCEEDINGS, vol. Robots for Humans Workshop 2024
Cocchella F., Eldardeer O., Manca M., Mattarese M., Rezzani A., Zedda E.
In recent years, the research field of Human-Robot Interaction has become crucial to understanding and designing the technological future. New methods and approaches in this field are urgently needed to meet the challenges of a rapidly changing landscape. In this workshop, we proposed that the intersection between Human-Computer Interaction (HCI) and HumanRobot Interaction (HRI) offers methodological opportunities while highlighting the new challenges that robot integration into society will face. In this perspective, humans bridge society, computers, and robots. Thus, the workshop proposed reflections on how embracing a human-centred design approach can help prioritise people's empowerment in society and collaborate with robots.Source: CEUR WORKSHOP PROCEEDINGS, vol. Robots for Humans Workshop 2024
See at:
ceur-ws.org | CNR IRIS | CNR IRIS
2024
Conference article
Open Access
A proposal for adapting robot behaviours using fuzzy Q-learning in cognitive serious game scenarios
Zedda E., Paternò F.
The repetitive and monotonous character of cognitive training may lead to waning interest and eventual disengagement among older adults with cognitive impairments. To address this issue, this study proposes an adaptive approach wherein a Socially Assistive Robot (SAR) autonomously selects optimal actions to sustain an emotional state in older adults while participating in serious cognitive training games. The aim is to propose an adaptation strategy that leverages fuzzy Q-learning to prompt users to maintain a positive state.Source: CEUR WORKSHOP PROCEEDINGS, vol. 3794. Arenzano, Italy, 3/06/2024
Zedda E., Paternò F.
The repetitive and monotonous character of cognitive training may lead to waning interest and eventual disengagement among older adults with cognitive impairments. To address this issue, this study proposes an adaptive approach wherein a Socially Assistive Robot (SAR) autonomously selects optimal actions to sustain an emotional state in older adults while participating in serious cognitive training games. The aim is to propose an adaptation strategy that leverages fuzzy Q-learning to prompt users to maintain a positive state.Source: CEUR WORKSHOP PROCEEDINGS, vol. 3794. Arenzano, Italy, 3/06/2024
See at:
ceur-ws.org | CNR IRIS | CNR IRIS
2024
Book
Restricted
Proceedings of the 1st Workshop on Robots for Humans (RfH 2024), co-located with 17th edition of the Conference on Advanced Visual Interfaces (AVI 2024)
Cocchella F., Eldardeer O., Manca M., Mattarese M., Rezzani A., Zedda E.
In recent years, the research field of Human-Robot Interaction has become crucial to understanding and designing the technological future. New methods and approaches in this field are urgently needed to meet the challenges of a rapidly changing landscape. In this workshop, we proposed that the intersection between Human-Computer Interaction (HCI) and HumanRobot Interaction (HRI) offers methodological opportunities while highlighting the new challenges that robot integration into society will face. In this perspective, humans bridge society, computers, and robots. Thus, the workshop proposed reflections on how embracing a human-centred design approach can help prioritise people's empowerment in society and collaborate with robots. This CEUR-WS volume contains the proceedings of the first edition of the Robots for Humans (RfH) Workshop. The workshop was held on Jun 3rd, 2024, in Arenzano (Italy) during the 17th edition of the Conference on Advanced Visual Interfaces (AVI 2024 https://avi2024.dibris.unige.it/home). It receives contributions from authors from countries such as Italy, Germany and Israel.Source: CEUR WORKSHOP PROCEEDINGS, vol. 3794
Cocchella F., Eldardeer O., Manca M., Mattarese M., Rezzani A., Zedda E.
In recent years, the research field of Human-Robot Interaction has become crucial to understanding and designing the technological future. New methods and approaches in this field are urgently needed to meet the challenges of a rapidly changing landscape. In this workshop, we proposed that the intersection between Human-Computer Interaction (HCI) and HumanRobot Interaction (HRI) offers methodological opportunities while highlighting the new challenges that robot integration into society will face. In this perspective, humans bridge society, computers, and robots. Thus, the workshop proposed reflections on how embracing a human-centred design approach can help prioritise people's empowerment in society and collaborate with robots. This CEUR-WS volume contains the proceedings of the first edition of the Robots for Humans (RfH) Workshop. The workshop was held on Jun 3rd, 2024, in Arenzano (Italy) during the 17th edition of the Conference on Advanced Visual Interfaces (AVI 2024 https://avi2024.dibris.unige.it/home). It receives contributions from authors from countries such as Italy, Germany and Israel.Source: CEUR WORKSHOP PROCEEDINGS, vol. 3794
See at:
ceur-ws.org | CNR IRIS | CNR IRIS
2023
Conference article
Open Access
Towards adaptation of humanoid robot behaviour in serious game scenarios using reinforcement learning
Zedda E, Manca M, Paternò F
Repetitive cognitive training can be seen as tedious by older adults and cause participants to drop out. Humanoid robots can be exploited to reduce boredom and the cognitive burden in playing serious games as part of cognitive training. In this paper, an adaptive technique to select the best actions for a robot is proposed to maintain the attention level of elderly users during a serious game. The goal is to create a strategy to adapt the robot's behaviour to stimulate the user to remain attentive through reinforcement learning. Specifically, a learning algorithm (QL) has been applied to obtain the best adaptation strategy for the selection of the robot's actions. The robot's actions consist of a combination of verbal and nonverbal interaction aspects. We have applied this approach to the behaviour of a Pepper robot for which two possible personalities have been defined. Each personality is exhibited by performing specific actions in the various modalities supported. Simulation results indicate learning convergence and seem promising to validate the effectiveness of the obtained strategy. Preliminary test results with three participants suggest that the adaption in the robot is perceived.Source: CEUR WORKSHOP PROCEEDINGS, pp. 93-99. Florence, Italy, 16/12/2022
Zedda E, Manca M, Paternò F
Repetitive cognitive training can be seen as tedious by older adults and cause participants to drop out. Humanoid robots can be exploited to reduce boredom and the cognitive burden in playing serious games as part of cognitive training. In this paper, an adaptive technique to select the best actions for a robot is proposed to maintain the attention level of elderly users during a serious game. The goal is to create a strategy to adapt the robot's behaviour to stimulate the user to remain attentive through reinforcement learning. Specifically, a learning algorithm (QL) has been applied to obtain the best adaptation strategy for the selection of the robot's actions. The robot's actions consist of a combination of verbal and nonverbal interaction aspects. We have applied this approach to the behaviour of a Pepper robot for which two possible personalities have been defined. Each personality is exhibited by performing specific actions in the various modalities supported. Simulation results indicate learning convergence and seem promising to validate the effectiveness of the obtained strategy. Preliminary test results with three participants suggest that the adaption in the robot is perceived.Source: CEUR WORKSHOP PROCEEDINGS, pp. 93-99. Florence, Italy, 16/12/2022
See at:
ceur-ws.org | CNR IRIS | ISTI Repository | CNR IRIS
2023
Conference article
Open Access
An environment to collect personal memories of older adults and use them to personalise serious games with humanoid robots
Catricalà B., Ledda M., Manca M., Paternò F., Santoro C., Zedda E.
One of the goals of Ambient Assisted Living (AAL) solutions is to be able to stimulate the cognitive resources of older adults. An innovative way to address such stimulation is the use of serious games delivered through humanoid robots, as they can provide an engaging way to perform exercises useful for training human memory, attention, processing, and planning activities. This paper presents an approach to supporting cognitive stimulation based on personal memories. The humanoid robot can exhibit different behaviours using various modalities, and propose the games in a way personalised to specific individuals' requirements, preferences, abilities, and motivations, which can vary among older adults, and even dynamically evolve over time for the same person depending on changing user needs and health conditions. Using personal memories associated with facts and events thatoccurred in older adults life in the serious games can increase their engagement, and thus potentially reduce the cognitive training drop-out.Source: CEUR WORKSHOP PROCEEDINGS, pp. 44-54. Florence, Italy, 16/12/2022
Catricalà B., Ledda M., Manca M., Paternò F., Santoro C., Zedda E.
One of the goals of Ambient Assisted Living (AAL) solutions is to be able to stimulate the cognitive resources of older adults. An innovative way to address such stimulation is the use of serious games delivered through humanoid robots, as they can provide an engaging way to perform exercises useful for training human memory, attention, processing, and planning activities. This paper presents an approach to supporting cognitive stimulation based on personal memories. The humanoid robot can exhibit different behaviours using various modalities, and propose the games in a way personalised to specific individuals' requirements, preferences, abilities, and motivations, which can vary among older adults, and even dynamically evolve over time for the same person depending on changing user needs and health conditions. Using personal memories associated with facts and events thatoccurred in older adults life in the serious games can increase their engagement, and thus potentially reduce the cognitive training drop-out.Source: CEUR WORKSHOP PROCEEDINGS, pp. 44-54. Florence, Italy, 16/12/2022
See at:
ceur-ws.org | CNR IRIS | ISTI Repository | CNR IRIS
2023
Conference article
Open Access
An adaptive behaviour-based strategy for SARs interacting with older adults with MCI during a serious game scenario
Zedda E., Manca M., Paternò F., Santoro C.
The monotonous nature of repetitive cognitive training may cause losing interest in it and dropping out by older adults. This study introduces an adaptive technique that enables a Socially Assistive Robot (SAR) to select the most appropriate actions to maintain the engagement level of older adults while they play the serious game in cognitive training. The goal is to develop an adaptation strategy for changing the robot's behaviour that uses reinforcement learning to encourage the user to remain engaged. A reinforcement learning algorithm was implemented to determine the most effective adaptation strategy for the robot's actions, encompassing verbal and nonverbal interactions. The simulation results demonstrate that the learning algorithm achieved convergence and offers promising evidence to validate the strategy's effectiveness.DOI: 10.48550/arxiv.2305.01492
Metrics:
Zedda E., Manca M., Paternò F., Santoro C.
The monotonous nature of repetitive cognitive training may cause losing interest in it and dropping out by older adults. This study introduces an adaptive technique that enables a Socially Assistive Robot (SAR) to select the most appropriate actions to maintain the engagement level of older adults while they play the serious game in cognitive training. The goal is to develop an adaptation strategy for changing the robot's behaviour that uses reinforcement learning to encourage the user to remain engaged. A reinforcement learning algorithm was implemented to determine the most effective adaptation strategy for the robot's actions, encompassing verbal and nonverbal interactions. The simulation results demonstrate that the learning algorithm achieved convergence and offers promising evidence to validate the strategy's effectiveness.DOI: 10.48550/arxiv.2305.01492
Metrics:
See at:
arxiv.org | CNR IRIS | ISTI Repository | CNR IRIS
2023
Conference article
Open Access
Biography-based robot games for older adults
Catricalà B., Ledda M., Manca M., Paternò F., Santoro C., Zedda E.
One issue in aging is how to stimulate the cognitive skills of older adults. One way to address it is the use of serious games delivered through humanoid robots, to provide engaging ways to perform exercises to train memory, attention, processing, and planning activities. We present an approach in which a humanoid robot, by using various modalities, propose the games in a way personalised to specific individuals' experiences using their personal memories associated with facts and events that occurred in older adults' life. This personalization can increase their interest and engagement, and thus potentially reduce the cognitive training drop-out.DOI: 10.48550/arxiv.2305.19849
Metrics:
Catricalà B., Ledda M., Manca M., Paternò F., Santoro C., Zedda E.
One issue in aging is how to stimulate the cognitive skills of older adults. One way to address it is the use of serious games delivered through humanoid robots, to provide engaging ways to perform exercises to train memory, attention, processing, and planning activities. We present an approach in which a humanoid robot, by using various modalities, propose the games in a way personalised to specific individuals' experiences using their personal memories associated with facts and events that occurred in older adults' life. This personalization can increase their interest and engagement, and thus potentially reduce the cognitive training drop-out.DOI: 10.48550/arxiv.2305.19849
Metrics:
See at:
CNR IRIS | ISTI Repository | CNR IRIS
2023
Journal article
Open Access
Personalisation of humanoid robots: serious games for older adults based on biographical memories
Catricalà B., Manca M., Paternò F., Santoro C., Zedda E.
We present an approach to novel digital cognitive training through serious games able to adapt to personally relevant material from the older adult's life. The games are based on memories associated with the older adult's biography, thus making interactions personalised, relevant, and more engaging. The serious games are accessed through humanoid robots, which can make the training exercise more engaging because of their human-like behaviour.Source: ERCIM NEWS, vol. 132, pp. 28-29
Catricalà B., Manca M., Paternò F., Santoro C., Zedda E.
We present an approach to novel digital cognitive training through serious games able to adapt to personally relevant material from the older adult's life. The games are based on memories associated with the older adult's biography, thus making interactions personalised, relevant, and more engaging. The serious games are accessed through humanoid robots, which can make the training exercise more engaging because of their human-like behaviour.Source: ERCIM NEWS, vol. 132, pp. 28-29
See at:
ercim-news.ercim.eu | CNR IRIS | ISTI Repository | CNR IRIS
2023
Conference article
Open Access
MCI older adults' user experience with introverted and extraverted humanoid robot personalities
Zedda E., Manca M., Paternò F., Santoro C.
This study aimed to investigate the impact of different personalities in humanoid robots for cognitive training scenarios with olderadults with mild cognitive impairment (MCI). In particular, we have designed an application with two opposite personalities based onthe Extraversion dimension of the Big Five Factors model. A user test with 16 Italian-speaking participants diagnosed with MCI aged68+ was performed. The analysis of the data collected suggests that the robot's personality can have an effect on the engagementof such users and also found that participants can discriminate between the two personalities. Overall, the study highlights theimportance of designing human-robot interactions considering personality-related aspects when considering MCI older adults.DOI: 10.1145/3605390.3605405
Metrics:
Zedda E., Manca M., Paternò F., Santoro C.
This study aimed to investigate the impact of different personalities in humanoid robots for cognitive training scenarios with olderadults with mild cognitive impairment (MCI). In particular, we have designed an application with two opposite personalities based onthe Extraversion dimension of the Big Five Factors model. A user test with 16 Italian-speaking participants diagnosed with MCI aged68+ was performed. The analysis of the data collected suggests that the robot's personality can have an effect on the engagementof such users and also found that participants can discriminate between the two personalities. Overall, the study highlights theimportance of designing human-robot interactions considering personality-related aspects when considering MCI older adults.DOI: 10.1145/3605390.3605405
Metrics:
See at:
dl.acm.org | CNR IRIS | ISTI Repository | CNR IRIS | CNR IRIS
2023
Journal article
Open Access
Older adults' user experience with introvert and extravert humanoid robot personalities
Zedda E., Manca M., Paternò F., Santoro C.
Humanoid robots can be an effective tool for the cognitive training of older adults. For this purpose, it is important that their interaction be engaging. In this study, we investigate whether proposing robots exhibiting extraverted or introverted personalities can improve user experience. In particular, we have designed and implemented a set of multi-modal cues for such personality traits, which have been exploited in an application proposing typical exercises for cognitive training through a Pepper robot. We report on a user test with 24 older adults (65 +), which provided interesting and positive feedback regarding how the robot personalities have been exhibited and their impact on the experience of such users.Source: UNIVERSAL ACCESS IN THE INFORMATION SOCIETY (INTERNET)
DOI: 10.1007/s10209-023-01054-2
Metrics:
Zedda E., Manca M., Paternò F., Santoro C.
Humanoid robots can be an effective tool for the cognitive training of older adults. For this purpose, it is important that their interaction be engaging. In this study, we investigate whether proposing robots exhibiting extraverted or introverted personalities can improve user experience. In particular, we have designed and implemented a set of multi-modal cues for such personality traits, which have been exploited in an application proposing typical exercises for cognitive training through a Pepper robot. We report on a user test with 24 older adults (65 +), which provided interesting and positive feedback regarding how the robot personalities have been exhibited and their impact on the experience of such users.Source: UNIVERSAL ACCESS IN THE INFORMATION SOCIETY (INTERNET)
DOI: 10.1007/s10209-023-01054-2
Metrics:
See at:
CNR IRIS | link.springer.com | ISTI Repository | CNR IRIS
2023
Software
Metadata Only Access
Robot personalities module
Zedda E
Description: An application designed to enhance cognitive stimulation among older adults by manipulating robot behaviours into a cooking game. The application incorporates a personality module that generates two robot personalities (extravert and introvert) designed and implemented to improve the Human-Robot Interaction (HRI) of older adults with cognitive impairments. Technologies used: Java, QiSDK, SQL Version: 5.0 CNR Link: https://giteas2i2s.isti.cnr.it/Human_in_Information_Systems_HIIS/Personality
Zedda E
Description: An application designed to enhance cognitive stimulation among older adults by manipulating robot behaviours into a cooking game. The application incorporates a personality module that generates two robot personalities (extravert and introvert) designed and implemented to improve the Human-Robot Interaction (HRI) of older adults with cognitive impairments. Technologies used: Java, QiSDK, SQL Version: 5.0 CNR Link: https://giteas2i2s.isti.cnr.it/Human_in_Information_Systems_HIIS/Personality
See at:
CNR IRIS
2023
Other
Metadata Only Access
Personalities in humanoid robots for cognitive training of older adults
Zedda E
In the last decade, the ageing of the population is occurring worldwide, and ageing increases the degeneration in the cognitive and physical domains of older adults. For this reason, technologies to support older adults in trying to slow down the progression of cognitive impairment are becoming more and more important. In particular, humanoid robots with social skills are increasingly common in the real world. Although life expectancy is increasing, the quality of life is not necessarily doing so. Thus, we may find ourselves and our loved ones dependent and in need of another person to perform the most basic tasks, which has a strong negative psychological impact. As a result, social robots may be the definitive tool to improve the quality of life by empowering people dependent on others and extending their independent living. In this context, humanoid robots can be an effective tool for the cognitive training of older adults, and to achieve this, their interaction with humans must be engaging. In this Thesis, we seek to understand if proposing robots with extraverted or introverted personalities could improve the user experience during a serious game scenario. Specifically, we design, implement, refine, and test a set of verbal and nonverbal parameters for such personality traits, which are general and potentially have different fields of application. The two personalities are implemented in an application that proposes typical cognitive training exercises using a Pepper robot. Additionally, we identify the requirements for designing and implementing a serious game to be a useful tool to be included in cognitive training. After evaluating the robot personalities with different tests and interviews with 52 users, including experts, healthy older adults and users with mild cognitive impairment, we address the problem of how to improve engagement and adaptation for older adults during repetitive cognitive training. The monotonous nature of repetitive cognitive training may cause older adults to lose interest and drop out. Social robots are used to reduce boredom and cognitive load when playing serious games as part of cognitive training, indeed. In this Thesis, a behaviour-adaptation technique is proposed to select the best actions, which consist of a combination of verbal and non-verbal interaction aspects, for the robot to maintain the attention level of older adult users during a serious game. The behaviour-adaptation technique proposed allows the robot to autonomously select the most appropriate actions to maintain the level of engagement of older adults during the full interaction session. After a session with 28 users, where both the adaptive and non-adaptive robot is used, a test to evaluate the adaptive behaviour of the robot is performed. The findings demonstrate users' ability to differentiate between the behaviours exhibited by the adaptive and non-adaptive robot. The users perceived the adaptive robot as displaying greater adaptability and engagement than the non-adaptive robot. This adaptability contributed to a more engaging and motivating user interaction with the robot. In summary, we provide a system and the guidelines to design a robotic behaviour of the future. The robot is able to autonomously adapt its personality to increase user engagement and experience, stimulating the users to continue the cognitive training.
Zedda E
In the last decade, the ageing of the population is occurring worldwide, and ageing increases the degeneration in the cognitive and physical domains of older adults. For this reason, technologies to support older adults in trying to slow down the progression of cognitive impairment are becoming more and more important. In particular, humanoid robots with social skills are increasingly common in the real world. Although life expectancy is increasing, the quality of life is not necessarily doing so. Thus, we may find ourselves and our loved ones dependent and in need of another person to perform the most basic tasks, which has a strong negative psychological impact. As a result, social robots may be the definitive tool to improve the quality of life by empowering people dependent on others and extending their independent living. In this context, humanoid robots can be an effective tool for the cognitive training of older adults, and to achieve this, their interaction with humans must be engaging. In this Thesis, we seek to understand if proposing robots with extraverted or introverted personalities could improve the user experience during a serious game scenario. Specifically, we design, implement, refine, and test a set of verbal and nonverbal parameters for such personality traits, which are general and potentially have different fields of application. The two personalities are implemented in an application that proposes typical cognitive training exercises using a Pepper robot. Additionally, we identify the requirements for designing and implementing a serious game to be a useful tool to be included in cognitive training. After evaluating the robot personalities with different tests and interviews with 52 users, including experts, healthy older adults and users with mild cognitive impairment, we address the problem of how to improve engagement and adaptation for older adults during repetitive cognitive training. The monotonous nature of repetitive cognitive training may cause older adults to lose interest and drop out. Social robots are used to reduce boredom and cognitive load when playing serious games as part of cognitive training, indeed. In this Thesis, a behaviour-adaptation technique is proposed to select the best actions, which consist of a combination of verbal and non-verbal interaction aspects, for the robot to maintain the attention level of older adult users during a serious game. The behaviour-adaptation technique proposed allows the robot to autonomously select the most appropriate actions to maintain the level of engagement of older adults during the full interaction session. After a session with 28 users, where both the adaptive and non-adaptive robot is used, a test to evaluate the adaptive behaviour of the robot is performed. The findings demonstrate users' ability to differentiate between the behaviours exhibited by the adaptive and non-adaptive robot. The users perceived the adaptive robot as displaying greater adaptability and engagement than the non-adaptive robot. This adaptability contributed to a more engaging and motivating user interaction with the robot. In summary, we provide a system and the guidelines to design a robotic behaviour of the future. The robot is able to autonomously adapt its personality to increase user engagement and experience, stimulating the users to continue the cognitive training.
See at:
etd.adm.unipi.it | CNR IRIS