A Possibilistic Approach for Activity Recognition in Smart Homes for Cognitive Assistance to Alzheimer’s Patients

Roy, Patrice; Giroux, Sylvain; Bouchard, Bruno; Bouzouane, Abdenour; Phua, Clifton; Tolstikov, Andrei; Biswas, Jit

doi:10.2991/978-94-91216-05-3_2

Cited by 39 publications

(30 citation statements)

References 30 publications

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“…One common paradigm features libraries of plans which are explicitly provided by human experts. For example, Roy et al [7] relies on manually created ontology-based plan libraries. These plans represent partially ordered sequences of actions that must be carried out in order to achieve a goal.…”

Section: Related Workmentioning

confidence: 99%

“…To address these problems, knowledge-based approaches rely on domain knowledge in the form of symbolic models and rules to reason about observed behaviours [11,7]. These approaches are advantageous since they are able to reason beyond sensor data and provide information about the patient's situation and potential medical reasons for their behaviour [14].…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Recognition of unscripted kitchen activities and eating behaviour for health monitoring

Whitehouse

Yordanova

Paiement

et al. 2016

2nd IET International Conference on Technologies for Active and Assisted Living (TechAAL 2016)

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Section: Related Workmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Recognition of unscripted kitchen activities and eating behaviour for health monitoring

Whitehouse

Yordanova

Paiement

et al. 2016

2nd IET International Conference on Technologies for Active and Assisted Living (TechAAL 2016)

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“…One other interesting research is proposed in [12], in which the smart home sensors are applied as the machine states of a Hidden Markov Model and a probabilistic approach that recognizes activities based on the sensors' behavior is proposed. In [4], activities are considered as concepts in description logic and in order to recognize the concepts, a possibilistic approach is proposed; moreover, in [5], an approach to calculate the probable contexts that activities may occur in them is proposed. Finally, in [2], it is proposed to model the activities as the series of fuzzy events that occur in the ambient environment.…”

Section: B State Of the Artmentioning

confidence: 99%

Data driven conceptual structures for simultaneous activities

Amirjavid

Bouzouane

Bouchard

2013

2013 IEEE/ACIS 12th International Conference on Computer and Information Science (ICIS)

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An activity is a chain of fuzzy events that occur in an environment caused by an intelligent system in order to achieve a goal. A goal may be achieved by effort of more than one individual. Regardless from the physical entity (modality and location) of the intelligence source and the quantity of individuals who perform the activities; per each possible goal or activity, we consider a source of intelligence who directs the order of fuzzy events that occur in the world. By frequently observation of the world, the plan behind world actuations is modeled applying extensions of the fuzzy logic. The main key point that we deal with is the analysis of the observations in order to make inferences about possible simultaneous activities that may be planned and realized by one or more individuals. A fuzzy conceptual structure for each individual and simultaneous activity is formalized; however, the model tolerates partial deviations from the activity structure.

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“…, 3, 2). So, the time of day features take on values in range [0][1][2][3][4][5][6][7][8][9][10][11][12] and are of length 24.…”

Section: A Low-level Featuresmentioning

confidence: 99%

“…Smart environments that are capable of activity recognition [2]- [6] and assistive technologies for the disabled [7], [8] has been designed. In the scope of ATTEND (AdapTive scenario recogniTion for Emergency and Need Detection) project, we are working on a system that is capable of activity recognition using a network of sensors installed in the living environment.…”

Section: Introductionmentioning

confidence: 99%

Activity recognition using a hierarchical model

Tırkaz

Bruckner

Yin

et al. 2012

IECON 2012 - 38th Annual Conference on IEEE Industrial Electronics Society

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Abstract-In this paper, we propose a human daily activity recognition method that is used for Ambient Assisted Living. The proposed system is able to learn a user's activities using the data from motion and door sensors. We extract low level features from the sensor data and feed the features to a model that combines support vector machines (SVMs) and conditional random fields (CRFs) to give accurate recognition results. We propose to combine SVM and CRF classifiers in a hierarchical model which results in better accuracies and can also make use of high level features. We conducted experiments and presented the effectiveness and accuracies of the proposed method.

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A Possibilistic Approach for Activity Recognition in Smart Homes for Cognitive Assistance to Alzheimer’s Patients

Cited by 39 publications

References 30 publications

Recognition of unscripted kitchen activities and eating behaviour for health monitoring

Recognition of unscripted kitchen activities and eating behaviour for health monitoring

Data driven conceptual structures for simultaneous activities

Activity recognition using a hierarchical model

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