Ambient assisted living (AAL) makes it possible to build assistance for older adults according to the person’s context. Understanding the person’s context sometimes involves transforming one’s home into a smart home. Typically, this is carried out using nonintrusively distributed sensors and calm technologies. Older adults often have difficulty performing activities of daily living, such as taking medication, drinking coffee, watching television, using certain electronic devices, and dressing. This difficulty is even greater when these older adults suffer from cognitive impairments. Defining an assistance solution requires a multidisciplinary and iterative collaborative approach. It is necessary, therefore, to reason about the imperatives and solutions of this multidisciplinary collaboration (e.g., clinical), as well as the adaptation of technical constraints (e.g., technologies). A common approach to reasoning is to represent knowledge using logic-based formalisms, such as ontologies. However, there is not yet an established ontology that defines concepts such as multidisciplinary collaboration in successive stages of the assistance process. This article presents OntoDomus, an ontology that describes, at several levels, the semantic interactions between ambient assisted living, context awareness, smart home, and Internet of Things, based on multidisciplinarity. It revolves around two main notions: multidisciplinarity, based on specific sub-ontologies and the ambient feedback loop. OntoDomus combines SPARQL queries and OWL 2 models to improve the reusability of domain terminology, allowing stakeholders to represent their knowledge in different collaborative and adaptive situations. The ontological model is validated, first by its reuse in more specific works—specific to an aspect of ambient assistance. Second, it is validated by the structuring of ambient knowledge and inferences of the formalization in a case study that includes instances for a particular activity of daily living. It places the ambient feedback loop at the center of the ontology by focusing on highly expressive domain ontology formalisms with a low level of expressiveness between them.

The Assistive living technologies provide good results for the support of specific activities transforming a home into a smart home. In this paper, we present a personalized ambient support system for elderly suffering from Alzheimer's dementia and nighttime wandering. Our goal is to help the person stay at home as long as possible and regain a regular circadian cycle while providing more comfort to the caregiver. The intervention proceeds in two phases. During the monitoring phase, the system determines the resident profile based on nighttime routines. Data is gathered from sensors dispatched in the smart home, coupled with physiological data obtained from worn sensors. Data is then classified to determine engine rules that will provide assistance to the resident to satisfy his needs. In the second phase, assistance is provided to the person by triggering rules depending on the activities occurring during night. It offers a calm environment with music and visual icons to soothe the person then encourage it to return to bed. The system is installed at the Alzheimer's home using wireless technologies. Multiple heterogeneous technologies are put in common to achieve it. Reliabilities and robustness tests were carried out in a 4 1/2 room apartment for 3 months with over 3.78 million collected data tuples. These tests have established three clusters of activities necessary for the recognition of nighttime wandering activities. This helped start an ongoing experiment in homes.

Ambient Assisted Living (AAL) environments encompass technical systems and the Internet of Things (IoT) tools to support seniors in their daily routines. They aim to enable seniors to live independently and safely for as long as possible when faced declining physical or cognitive capacities. This work presents the design, development and deployment of an AAL system in the context of smart cities. The proposed architecture is based on microservices and software components. We examined the requirements and specifications of AAL systems in smart homes, in efforts to describe and evaluate how they would be transposable in the case of smart cities. The system has been tested and evaluated in the laboratory; it has been deployed in real life settings within city and is still in use by five elderly people.

Objectives: This work presents an ambient-assisted living application that encourages seniors during nocturnal wandering episodes to return to bed in calm and comfort reassurance. Methods: Structuring knowledge by designing a software architecture capable of delivering high-level analysis and processing. A senior’s home has been upgraded into a smart home enabling the gathering of habits for two weeks and set up for personalized assistance over four weeks. Home automation devices associated with Actigraph monitors and self-reported sleep were used for more accuracy. Results: The architectural model can be used in ambient-assisted living applications for which data collection is permanent and continuous. Its layered organization facilitates the management of specific and general activities of daily life. The results of the home experience show that the system gave a notification whenever the need arose. On the other hand, it allowed the caregiver to get more information about the lifestyle of the senior. Conclusions: Future work should focus on providing more services to contextualize assistance. Ontology is used to structure all the ambient knowledge of the smart home. We also plan to do more home experiments.

Background: Telemonitoring of activities of daily living (ADLs) offers significant potential for gaining a deeper insight into the home care needs of older adults experiencing cognitive decline, particularly those living alone. In 2016, our team and a health care institution in Montreal, Quebec, Canada, sought to test this technology to enhance the support provided by home care clinical teams for older adults residing alone and facing cognitive deficits. The Support for Seniors’ Autonomy program (SAPA [Soutien à l’autonomie des personnes âgées]) project was initiated within this context, embracing an innovative research approach that combines action research and design science. Objective: This paper presents the research protocol for the SAPA project, with the aim of facilitating the replication of similar initiatives in the future. The primary objectives of the SAPA project were to (1) codevelop an ADL telemonitoring system aligned with the requirements of key stakeholders, (2) deploy the system in a real clinical environment to identify specific use cases, and (3) identify factors conducive to its sustained use in a real-world setting. Given the context of the SAPA project, the adoption of an action design research (ADR) approach was deemed crucial. ADR is a framework for crafting practical solutions to intricate problems encountered in a specific organizational context. Methods: This project consisted of 2 cycles of development (alpha and beta) that involved cyclical repetitions of stages 2 and 3 to develop a telemonitoring system for ADLs. Stakeholders, such as health care managers, clinicians, older adults, and their families, were included in each codevelopment cycle. Qualitative and quantitative data were collected throughout this project. Results: The first iterative cycle, the alpha cycle, took place from early 2016 to mid 2018. The first prototype of an ADL telemonitoring system was deployed in the homes of 4 individuals receiving home care services through a public health institution. The prototype was used to collect data about care recipients’ ADL routines. Clinicians used the data to support their home care intervention plan, and the results are presented here. The prototype was successfully deployed and perceived as useful, although obstacles were encountered. Similarly, a second codevelopment cycle (beta cycle) took place in 3 public health institutions from late 2018 to late 2022. The telemonitoring system was installed in 31 care recipients’ homes, and detailed results will be presented in future papers. Conclusions: To our knowledge, this is the first reported ADR project in ADL telemonitoring research that includes 2 iterative cycles of codevelopment and deployment embedded in the real-world clinical settings of a public health system. We discuss the artifacts, generalization of learning, and dissemination generated by this protocol in the hope of providing a concrete and replicable example of research partnerships in the field of digital health in cognitive aging. International Registered Report Identifier (IRRID): RR1-10.2196/52284