Ambient Intelligence in Health Care

Riva, Giuseppe

doi:10.1089/109493103322011597

Cited by 68 publications

(27 citation statements)

References 3 publications

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“…This paper addressed one of the challenges for ambient intelligent agents (e.g., [1,2,13]), to support a human in demanding tasks, namely to be aware of which (sub)tasks the human is doing, and how much progress is made, without direct communication about this.…”

Section: Discussionmentioning

confidence: 99%

An intelligent agent model with awareness of workflow progress

Both

Hoogendoorn

Mee³

et al. 2011

Appl Intell

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To support human functioning, ambient intelligent agents require knowledge about the tasks executed by the human. This knowledge includes design-time information like: (i) the goal of a task and (ii) the alternative ways for a human to achieve that goal, as well as run-time information such as the choices made by a human during task execution. In order to provide effective support, the agent must know exactly what steps the human is following. However, if not all steps along the path can be observed, it is possible that the agent cannot uniquely derive which path the human is following. Furthermore, in order to provide timely support, the agent must observe, reason, conclude and support within a limited period of time. To deal with these problems, this paper presents a generic focused reasoning mechanism to enable a guided selection of the path which is most likely followed by the human. This mechanism is based upon knowledge about the human and the workflow to perform the task. In order to come to such an approach, a reasoning mechanism is adopted in combination with the introduction of a new workflow representation, which is utilized to focus the reasoning process in an appropriate manner. The approach is evaluated by means of an extensive case study.

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Section: Discussionmentioning

confidence: 99%

An intelligent agent model with awareness of workflow progress

Both

Hoogendoorn

Mee³

et al. 2011

Appl Intell

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“…The development of these ubiquitous domestic systems is often motivated by the desire to improve the quality of life of citizens in general, and of elderly people in particular. In this context, it is essential that this development is accompanied by the development of suitable interfaces that ensure the usability and acceptability of these systems [5], [6], [7].…”

Section: Introductionmentioning

confidence: 99%

Monitoring the State of a Ubiquitous Robotic System: A Fuzzy Logic Approach

Guarino¹,

Saffiotti

2007

2007 IEEE International Fuzzy Systems Conference

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Abstract-A trend is emerging in the fields of ambient intelligence (AmI) and autonomous robotics, which points in the direction of a merger between these two fields. The inclusion of robotic devices in AmI system, sometimes named ubiquitous robotics, makes one of the hard problems in this field even harder: how can we provide a comfortable, natural interface between the everyday user and a complex system which consists of a large multitude of highly heterogeneous devices? In this paper, we address a specific, important aspect of this problem: to monitor the state of the ubiquitous system by the user of the system. The solution that we propose is based on two mechanisms: an expression-based semantics to represent in a uniform way the status of heterogeneous devices; and a common interface point to aggregate the information from all devices into a summary status presented to the user. For both mechanisms, we propose to use the tools of fuzzy logic. We justify this choice by arguments grounded in the semantics and formal properties of fuzzy logic. We also illustrate our approach on a specific type of ubiquitous robotic system called Ecology of Physically Embedded Intelligent Systems, or PEIS-Ecology.

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“…It also identifies effectiveness (defined as attainment of the objective of the activity) and transparency (defined as an absence of breakdowns during the activity) as the main characteristics of any rehabilitative AmI system. Following this vision, the most important reason for developing AmI assistive tools lies in their potential to compensate or expand the activity of users through new forms of human-computer interaction (Morganti & Riva, 2005;Riva, 2003).…”

mentioning

confidence: 99%