Situ-Centric Reinforcement Learning for Recommendation of Tasks in Activities of Daily Living In Smart Homes

Oyeleke, Richard O.; Yu, Chen-Yeou; Chang, Carl K.

doi:10.1109/compsac.2018.10250

Cited by 23 publications

(19 citation statements)

References 17 publications

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“…In [16] the Situ framework, that was designed as a probabilistic situation analytics environment, is used for supporting the recommendation of tasks necessary for executing activities like cooking or washing in the daily life of patients in the early states of Alzheimer's disease in smart home environments. The Situ framework was constructed around the situation model introduced in [3].…”

Section: Context-and Situation-awarenessmentioning

confidence: 99%

Situation Analytics and Model-based User Interface Development: A Synergetic Approach for Building Runtime-Adaptive Business Applications

Märtin

Kampfer

Herdin

et al. 2019

CSIMQ

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Situation analytics can be used to recognize the changing behavior, emotional state, cognitive load and environmental context of a user during complex task processing. This article discusses the SitAdapt 2.0 architecture that combines a situation analytics platform with pattern-and model-based user interface construction tools in order to build runtime-adaptive interactive business applications with enhanced user experience and task-accomplishment characteristics. The article focuses on the software components and tools for observing and tracking the user, data types for modeling situations, recognizing situations, and modeling structural changes and actions for generating the dynamic adaptations. The situation recognition capabilities and adaptive functionality of the system are demonstrated for web-applications for longdistance travel booking and a beauty products web-portal.

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Section: Context-and Situation-awarenessmentioning

confidence: 99%

Situation Analytics and Model-based User Interface Development: A Synergetic Approach for Building Runtime-Adaptive Business Applications

Märtin

Kampfer

Herdin

et al. 2019

CSIMQ

View full text Add to dashboard Cite

show abstract

“…Activities of daily living refer to foundational self-care activities that form an essential routine of a person needed to navigate daily life such as cooking, bathing, toileting, dressing and grooming (Feng, Chang, & Ming, 2017;Ohnishi, Kanehira, Kanezaki, & Harada, 2016;Xie et al, 2017). (Oyeleke, Yu & Chang, 2018) define an activity as a set of tasks or events that are performed in sequence or ordered in a stepwise manner towards a goal state. For instance, a person may be hungry and need to engage in an activity of cooking in order to satisfy his hunger (i.e., reach his goal state).…”

Section: Activities Of Daily Living (Adls) and Definition Of Conceptsmentioning

confidence: 99%

“…Activity is a set of tasks or events that are performed in sequence or ordered in a stepwise manner towards a goal state. For example, a person may be hungry and may need to engage in an activity of cooking to satisfy his hunger (i.e., reach his goal state; Oyeleke, Yu & Chang, 2018).…”

Section: Activities Of Daily Living (Adls) and Definition Of Conceptsmentioning

confidence: 99%

“…Actions refer to a sequence of tasks that is required to be performed or has already been performed with respect to an activity. For example, an activity of preparing a tea may require a person to take some actions such as: "open-kitchen-door", "open-water-tap" or "turn-on-the-stove" (Oyeleke, Yu & Chang, 2018).…”

Section: Activities Of Daily Living (Adls) and Definition Of Conceptsmentioning

confidence: 99%

“…The Situ-centered intention reinforcement framework is based on the extension of our previous work (Oyeleke, Yu & Chang, 2018), which relied on two assumptions: a) a human intention or goal can be inferred, and b) the order or sequence of activities in the path of the inferred goal is known. In this paper, we improve on the previous system by addressing both assumptions with the following two new key components:…”

Section: Framework Overviewmentioning

confidence: 99%

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Situation‐centered goal reinforcement of activities of daily living in smart home environments

2019

Self Cite

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Older adults with early‐stage dementia (ED) can experience confusion or lack clarity when performing routine activities of daily living (ADLs). These circumstances predispose the older adult to safety‐critical and often risky situations. A safety‐critical risky situation is one that constitutes a hazard. To support independent living, a sensor‐laden smart environment can be employed to mitigate such hazards. In this paper, we propose a situation‐centered goal reinforcement framework that supports older adults with ED in their decision making, and guides them through their ADL in order to fulfill their goal or intention and avoid hazards. First, we employ an LSTM (Long Short‐Term Memory) model to infer the current goal of the resident, using their previously observed normal ADL patterns. Secondly, we identify potentially risky situations in their currently observed goal path. We then incorporate a situ‐learning agent (SLA) that helps an inhabitant to make the right decision, thus preventing adverse events while guiding her through the task sequence that leads to her goal state. In addition, we use a naïve agent to simulate episodes of confusion similar to those that might be experienced by older adults with ED. We validated our method against an open‐source dementia dataset (Quesada et al., 2015) by considering four types of ADLs as case studies. We achieved an accuracy of 90.1% for our goal inference model, higher than the accuracies reported by related studies. We also reported other metrics including precision, recall and f1‐score for goal inference model. Finally, SLA's action recommendations relevance was evaluated accordingly.

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Context-Aware Recommender Systems: From Foundations to Recent Developments

Adomavicius

Bauman

Tuzhilin

et al. 2021

Recommender Systems Handbook

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Situ-Centric Reinforcement Learning for Recommendation of Tasks in Activities of Daily Living In Smart Homes

Cited by 23 publications

References 17 publications

Situation Analytics and Model-based User Interface Development: A Synergetic Approach for Building Runtime-Adaptive Business Applications

Situation Analytics and Model-based User Interface Development: A Synergetic Approach for Building Runtime-Adaptive Business Applications

Situation‐centered goal reinforcement of activities of daily living in smart home environments

Context-Aware Recommender Systems: From Foundations to Recent Developments

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