Periodic Reporting for period 3 - SMILE (Providing digitalised prevention and prediction support for ageing people in smart living environments)
Reporting period: 2024-01-01 to 2024-09-30
The SMart Inclusive Living Environments (SMILE) project supported ageing in place for older people by combining an innovative smart living environment (SLE) ecosystem model and a set of complementary eHealth solutions co-created with older people. SMILE innovated better ways of independent living to provide timely care and assistance when needed at home.
Drawing on practical situations that older people face in daily living, SMILE created SMart Inclusive Living Environments (SLE) with novel eHealth solutions enabling ageing in place. There were 6 main objectives:
1. Identify the needs and preferences of older people while living in their home environments.
2. Undertake co-creation of easy-to-use digital solutions with older people and novel methods to involve people with dementia.
3. Develop a smart AI-based system (Digital Care Facilitator and Conversational Agent) to proactively support older people in daily living.
4. To provide acceptable digital solutions when these solutions are introduced into older people’s lives
5. Evaluate the SMILE package to assess replicability and scalability in enhancing living spaces supporting independent, active, and socially inclusive living for older people.
6. Build Europe-Canada cooperation in replicating, scaling, and extending the results of SMILE to benefit the very heterogeneous populations of older people in our societies.
These objectives were achieved by three workstreams based on trans-disciplinary research: co-creative design and evaluation; digital care facilitator (DCF) and conversational agent (CA); SMILE SLE ecosystem and digital solutions. Our targeted breakthroughs for smart living environments supporting independent and active living were: a participatory SLE ecosystem model; the ‘Digital Care Facilitator’, an AI-based system [TRL6]; a conversational agent as an everyday intermediary enhancing social participation [TRL6]; personal mHealth apps, and eHealth monitors and devices [TRL5-8]. We demonstrated that SMILE works for a very heterogeneous group with different needs and preferences: older people with severe dementia, Chronic Obstructive Pulmonary Disease (COPD) and care transitions during post-surgery recovery. With this combined package and related service improvements SMILE went beyond state of the art in ways that are sustainable, scalable, and exploitable.
Drawing on practical situations that older people face in daily living, SMILE created SMart Inclusive Living Environments (SLE) with novel eHealth solutions enabling ageing in place. There were 6 main objectives:
1. Identify the needs and preferences of older people while living in their home environments.
2. Undertake co-creation of easy-to-use digital solutions with older people and novel methods to involve people with dementia.
3. Develop a smart AI-based system (Digital Care Facilitator and Conversational Agent) to proactively support older people in daily living.
4. To provide acceptable digital solutions when these solutions are introduced into older people’s lives
5. Evaluate the SMILE package to assess replicability and scalability in enhancing living spaces supporting independent, active, and socially inclusive living for older people.
6. Build Europe-Canada cooperation in replicating, scaling, and extending the results of SMILE to benefit the very heterogeneous populations of older people in our societies.
These objectives were achieved by three workstreams based on trans-disciplinary research: co-creative design and evaluation; digital care facilitator (DCF) and conversational agent (CA); SMILE SLE ecosystem and digital solutions. Our targeted breakthroughs for smart living environments supporting independent and active living were: a participatory SLE ecosystem model; the ‘Digital Care Facilitator’, an AI-based system [TRL6]; a conversational agent as an everyday intermediary enhancing social participation [TRL6]; personal mHealth apps, and eHealth monitors and devices [TRL5-8]. We demonstrated that SMILE works for a very heterogeneous group with different needs and preferences: older people with severe dementia, Chronic Obstructive Pulmonary Disease (COPD) and care transitions during post-surgery recovery. With this combined package and related service improvements SMILE went beyond state of the art in ways that are sustainable, scalable, and exploitable.
We have through several co-creational workshops invited users of technology to describe their use of technology and express what they would like of the technology for the future. Workshops have been performed in the four living labs in the Netherlands, Denmark, Canada, and Norway, with persons with COPD, dementia, other chronic conditions, and post-surgical patients. The Living labs have been set up so that they can include participants in the SMILE project, test technology developed in the SMILE project, and evaluate the SLE ecosystem.
Based on information collected in the workshops and literature reviews, work has been done to map the users’ intent and preferences, knowledge that are used in the development of two different versions of the Conversational Agent (CA); a chatbot CA and a dashboard CA; and the Digital Care Facilitator (DCF). We have identified four features for the chatbot CA that the users, healthcare staff, and stakeholders find important: 1) Clinical condition, 2) Social support, 3) Sleep pattern/sleep quality, and 4) Physical activity. These features were incorporated in the chatbot CA that in an iterative process has been presented for the users in several co-creational workshops.
It became clear that the chatbot CA was not suitable for persons with dementia, and instead we designed a dashboard CA to be used by the caregivers of persons with dementia. The dashboard CA presented data collected by different technology used to monitor persons with dementia, and the dashboard CA has been presented in workshops to improve the design of it.
We have developed a DCF, as a platform to integrate data collected from different sensors and sources across country borders. The DCF demonstrated that data from different sources could be merged into the same repository, where machine learning and AI could be added to recognize patterns and information that supported independent living for older persons. This information could be given to the patient and caregivers, through the CA. One important thing that had to be in place before merging data to the DCF, was bilateral Data Processing Agreements (DPA) between the data owner and data processor. We learned that writing and signing DPA across country borders is a slow process, and it involved several parts of the organization on both sides. The Data Protection and Data Security part of the merging of data was a bigger threat to scaling up the DCF than the actual technical part.
We designed a SMILE Digital Solution Catalogue, where 32 Small and Medium Enterprises (SMEs) presented their technology and digital solutions that could be useful for our user groups. The Digital Catalogue was easily accessible for interested parties, as it was presented on the SMILE web page. On the same SMILE web page we designed a knowledge hub, where innovations, results, and experience from the SMILE project was presented. Innovations and results from the SMILE project were exploited and disseminated through papers, reports, international conferences, and collaboration with stakeholders, companies, researchers and clinicians.
We have published eight open access papers in international journals, and four more papers are submitted and under review.
Our mission at project end, is that the technology developed in the SMILE project will support independent living for elderly persons living at home.
Based on information collected in the workshops and literature reviews, work has been done to map the users’ intent and preferences, knowledge that are used in the development of two different versions of the Conversational Agent (CA); a chatbot CA and a dashboard CA; and the Digital Care Facilitator (DCF). We have identified four features for the chatbot CA that the users, healthcare staff, and stakeholders find important: 1) Clinical condition, 2) Social support, 3) Sleep pattern/sleep quality, and 4) Physical activity. These features were incorporated in the chatbot CA that in an iterative process has been presented for the users in several co-creational workshops.
It became clear that the chatbot CA was not suitable for persons with dementia, and instead we designed a dashboard CA to be used by the caregivers of persons with dementia. The dashboard CA presented data collected by different technology used to monitor persons with dementia, and the dashboard CA has been presented in workshops to improve the design of it.
We have developed a DCF, as a platform to integrate data collected from different sensors and sources across country borders. The DCF demonstrated that data from different sources could be merged into the same repository, where machine learning and AI could be added to recognize patterns and information that supported independent living for older persons. This information could be given to the patient and caregivers, through the CA. One important thing that had to be in place before merging data to the DCF, was bilateral Data Processing Agreements (DPA) between the data owner and data processor. We learned that writing and signing DPA across country borders is a slow process, and it involved several parts of the organization on both sides. The Data Protection and Data Security part of the merging of data was a bigger threat to scaling up the DCF than the actual technical part.
We designed a SMILE Digital Solution Catalogue, where 32 Small and Medium Enterprises (SMEs) presented their technology and digital solutions that could be useful for our user groups. The Digital Catalogue was easily accessible for interested parties, as it was presented on the SMILE web page. On the same SMILE web page we designed a knowledge hub, where innovations, results, and experience from the SMILE project was presented. Innovations and results from the SMILE project were exploited and disseminated through papers, reports, international conferences, and collaboration with stakeholders, companies, researchers and clinicians.
We have published eight open access papers in international journals, and four more papers are submitted and under review.
Our mission at project end, is that the technology developed in the SMILE project will support independent living for elderly persons living at home.
The SMILE project’s ambition was to develop new technology that could support aging in place. The integration of a DCF and a CA, using machine learning/AI, pushed the technological development one step further and went beyond the state of the art. The health services and infrastructure developed in the SMILE Living labs, were well suited for testing the developed SMILE technology in the very heterogeneous populations of older people in our societies.
We wrote an exploitation strategy for the project. Discussions with the pilot locations were performed, and these discussions informed the final exploitation strategy.
Information about the user-intend and the evaluation of the SLE ecosystem were disseminated in scientific journals and presented at conferences, as well as in mass- and social medias.
If the technology developed in SMILE can support aging in place and independent living at home, this will have wider implication in the society reducing the need for institutional care for the growing number of elderlies in the future.
We wrote an exploitation strategy for the project. Discussions with the pilot locations were performed, and these discussions informed the final exploitation strategy.
Information about the user-intend and the evaluation of the SLE ecosystem were disseminated in scientific journals and presented at conferences, as well as in mass- and social medias.
If the technology developed in SMILE can support aging in place and independent living at home, this will have wider implication in the society reducing the need for institutional care for the growing number of elderlies in the future.