A Visual Editor to Support the Use of Temporal Logic for ADL Monitoring

Rugnone, Alberto; Poli, Francesco; Vicario, Enrico; Nugent, Chris; Tamburini, Elena; Paggetti, Cristiano

doi:10.1007/978-3-540-73035-4_23

Cited by 4 publications

(7 citation statements)

References 8 publications

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“…In most situations, the recognition rules are generated by following a heuristic strategy and are represented in some logical language, e.g., temporal logic or description logic. Rugnone et al [37] used temporal logic to represent recognition rules to recognize abnormal activity. Yin et al and Chen et al [38,39] represented recognition rules as an ontology, and Chen et al [40] proposed an improved ontology-based approach.…”

Section: Related Workmentioning

confidence: 99%

A Novel Approach Based on Time Cluster for Activity Recognition of Daily Living in Smart Homes

et al. 2017

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Abstract:With the trend of the increasing ageing population, more elderly people often encounter some problems in their daily lives. To enable these people to have more carefree lives, smart homes are designed to assist elderly people by recognizing their daily activities. Although different models and algorithms that use temporal and spatial features for activity recognition have been proposed, the rigid representations of these features damage the accuracy of activity recognition. In this paper, a two-stage approach is proposed to recognize the activities of a single resident. Firstly, in terms of temporal features, the approximate duration, start and end time are extracted from the activity records. Secondly, a set of activity records is clustered according to the records' temporal features. Then, the classifiers are used to recognize the daily activities in each cluster according to the spatial features. Finally, two experiments are done to validate the recognition of daily activities in order to compare the proposed approach with a one-dimensional model. The results demonstrate that the proposed approach favorably outperforms the one-dimensional model. Two public datasets are used to evaluate the proposed approach. The experiment results show that the proposed approach achieves average accuracies of 80% and 89%, respectively.

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Section: Related Workmentioning

confidence: 99%

A Novel Approach Based on Time Cluster for Activity Recognition of Daily Living in Smart Homes

et al. 2017

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“…Figure 7 depicts a possible visualization of the complete rule. The visualization can be enhanced by substituting operators with graphical symbol and also atomic prepositions with icons, as suggested by the visual editor presented (Rugnone et al 2007). …”

Section: How the Scenario Can Be Solvedmentioning

confidence: 99%

“…The recognition task in particular has been addressed with: probabilistic methods such as Bayesian networks (Albrecht et al 1998) or Markovian models (Duong et al 2005); machine-learning technologies such as pattern detection (Das et al 2002); and logical approaches such as event calculus (Chen et al 2008) or temporal logic (Rugnone et al 2007). Brdiczka et al (2008) proposed a mixed approach where an SVM is used to pre-process the data and identify basic individual postures, followed by processing with an HMM to detect more complex activities.…”

Section: Introductionmentioning

confidence: 99%

Formal Modeling Techniques for Ambient Assisted Living

Parente¹,

Nugent²,

Hong³

et al. 2010

Ageing Int

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In the development of systems of ambient assisted living (AAL), formalized models and analysis techniques can provide a ground that makes development amenable to a systematic approach. We consider the following formal modeling tools and techniques: fault trees, evidential reasoning, evidential ontology networks, temporal logic, hidden Markov models and partially observable Markov models. We review them in the perspective of their potential in the realm of AAL, recalling the general traits and potential of each of them, and highlighting how this can be concretely deployed within the AAL realm. To this end, we present a number of scenarios providing insight on how each technique can match the needs of different types of problem in the application domain.The present and forecasted evolution of population demographics demands new approaches to the delivery of health and social care (World Health Organization 2010). Technology may largely contribute both to the efficiency and effectiveness of services through solutions that range from assistive technologies such as medication management and cognitive prosthetics to wearable healthmonitoring systems (Paradiso et al. 2005). As a common trait, all these approaches pose a crucial problem pertaining to the automated extraction of high-level semantic information from low-level data acquired through technological devices. This process may take a major role in the profiling of the patient (Atallah and Yang 2009), which in turn provides a basis for supporting decisions needed for effective Ageing Int (2011) 36:192-216

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“…Recently, two studies [11], [2] have attempted to address these issues through the development of visual languages which support operators in defining the rules themselves in a non technical manner. These methods assist the operator in providing a set of rules which are both patient specific and in line with the dynamic requirements of the patient.…”

Section: B Hometlmentioning

confidence: 99%

“…Conversely, the approach presented in [2] had a strong mathematical foundation, which was based on a mature context of Formal Logic [12][13][14]. It proposed the use of a declination of a past linear temporal logic, based on state and not on action, with a formalism supported by temporal specifications.…”

Section: B Hometlmentioning

confidence: 99%

HomeTL: A visual formalism, based on temporal logic, for the design of home based care

Rugnone

Vicario

Nugent

et al. 2007

2007 IEEE International Conference on Automation Science and Engineering

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The demands of introducing a more practical means of managing and monitoring technology within the home environment to support independent living are increasing. Efforts have been made recently to address these concerns, however, they may be considered to be lacking in mathematical rigour or have not benefited from incorporating the needs and expectations of the healthcare professionals. In this paper, we present a prototype solution, referred to as HomeTL, which allows healthcare professionals to establish the conditions/rules within which technology in the home should operate. The HomeTL concept is based on previous work in the area of visual notation and linear temporal logic. A visual editor for HomeTL has been developed and is presented in this paper. Following a description of the methodology and the prototype developed, results from a usability study, conducted on three computer scientists specializing in the area of healthcare management, are presented. The initial results based on this survey are positive and show that the topic deserves further investigation.

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A Visual Editor to Support the Use of Temporal Logic for ADL Monitoring

Cited by 4 publications

References 8 publications

A Novel Approach Based on Time Cluster for Activity Recognition of Daily Living in Smart Homes

A Novel Approach Based on Time Cluster for Activity Recognition of Daily Living in Smart Homes

Formal Modeling Techniques for Ambient Assisted Living

HomeTL: A visual formalism, based on temporal logic, for the design of home based care

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