User-driven design of a context-aware application: an ambient-intelligent nurse call system

Abstract

Abstract-The envisioned ambient-intelligent patient room contains numerous devices to sense and adjust the environment, monitor patients and support caregivers. Context-aware techniques are often used to combine and exploit the heterogeneous data offered by these devices to improve the provision of continuous care. However, the adoption of context-aware applications is lagging behind what could be expected, because they are not adapted to the daily work practices of the users, a lack of personalization of the services and not tackling problems such as the need of the users for control. To mediate this, an interdisciplinary methodology was investigated and designed in this research to involve the users in each step of the development cycle of the context-aware application. The methodology was used to develop an ambient-intelligent nurse call system, which uses gathered context data to find the most appropriate caregivers to handle a call of a patient and generate new calls based on sensor data. Moreover, a smartphone application was developed for the caregivers to receive and assess calls. The lessons learned during the user-driven development of this system are highlighted.

Design of a Smart Learning System

“…The authors of [9] proposed the user-driven development method for context-aware applications. Using the method, they implemented an ambient-intelligent nurse call system that determines user's context with sensor data and finds the most appropriate caregivers based on the patient's context.…”

The Innovation Binder Approach: A Guide Towards a Social-Technical Balanced Pervasive Health System

“…This steered the decision to pick those scenes in the future scenario where the added value of this technology could be shown both from a user and technical perspective, illustrating a balanced use of computer reasoning and human intervention in the process (Ongenae, 2012). In the Care4Balance project, one of the main drivers is having a demonstrator that is able to show the reciprocity between caregiver and care receiver, as well as using a new interface.…”

“…A detailed description and comparison of the workshop types can be retrieved in Ongenae et al (2011Ongenae et al ( & 2012. For example, the first one was a role playing workshop during which we let different stakeholders from the care field play scenes from the future scenario, offering information on both current practices, used concepts for the ontology and the envisioned future use of sensors in a ward environment.…”

“…For instance, the team can organize a role-play workshop revolving around the proof of concept, supplied with mock-ups of those features that have not yet been implemented. As such, it is possible to create an improved second proof of concept that is based on significant user tests (Ongenae, 2012).…”

“…In our examples, we will refer to experiences from several projects. These include the finished project ACCIO (2010ACCIO ( -2012, developing a contextual nurse call system making use of ontologies and sensor data, Ongenae et al 2012) and TransEcare (2007TransEcare ( -2009, creating transparant ICT platforms for eCare); and to current experiences in the O'CareCloudS project (2012)(2013)(2014), developing a contextual information sharing system between caregivers), Fallrisk (2013-2014, on contextual fall risk prevention and detection using sensor information) and the AAL project Care4Balance (2013-2015, on dashboard applications for elderly to coordinate care provisioning).…”