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Indoor location identification of patients for directing virtual care: An AI approach using machine learning and knowledge-based methods
شناسایی موقعیت داخلی بیماران برای هدایت مراقبت های مجازی: رویکرد هوش مصنوعی با استفاده از یادگیری ماشین و روش های دانش بنیان-2020 In a digitally enabled healthcare setting, we posit that an individual’s current location is pivotal for supporting
many virtual care services—such as tailoring educational content towards an individual’s current location, and,
hence, current stage in an acute care process; improving activity recognition for supporting self-management in a
home-based setting; and guiding individuals with cognitive decline through daily activities in their home.
However, unobtrusively estimating an individual’s indoor location in real-world care settings is still a challenging
problem. Moreover, the needs of location-specific care interventions go beyond absolute coordinates and
require the individual’s discrete semantic location; i.e., it is the concrete type of an individual’s location (e.g., exam
vs. waiting room; bathroom vs. kitchen) that will drive the tailoring of educational content or recognition of
activities. We utilized Machine Learning methods to accurately identify an individual’s discrete location, together
with knowledge-based models and tools to supply the associated semantics of identified locations. We
considered clustering solutions to improve localization accuracy at the expense of granularity; and investigate
sensor fusion-based heuristics to rule out false location estimates. We present an AI-driven indoor localization
approach that integrates both data-driven and knowledge-based processes and artifacts. We illustrate the application
of our approach in two compelling healthcare use cases, and empirically validated our localization
approach at the emergency unit of a large Canadian pediatric hospital. Keywords: Virtual care | Ambient sensors | Indoor localization | Machine learning | Semantic web | eHealth platform | Data fusion | Self-management | Ambient assisted living | Activities of daily living |
مقاله انگلیسی |
2 |
Robot Assistant in Management of Diabetes in Children Based on the Internet of Things
دستیار ربات در مدیریت دیابت در کودکان مبتنی بر اینترنت اشیاء -2017 This paper presents a new eHealth platform
incorporating humanoid robots to support an emerging
multidimensional care approach for the treatment of diabetes.
The architecture of the platform extends the Internet of Things
to a Web-centric paradigm through utilizing existing Web standards to access and control objects of the physical layer. This
incorporates capillary networks, each of which encompasses a set
of medical sensors linked wirelessly to a humanoid robot linked
(via the Internet) to a Web-centric disease management hub.
This provides a set of services for both patients and their caregivers that support the full continuum of the multidimensional
care approach of diabetes. The platform’s software architecture
pattern enables the development of various applications without knowing low-level details of the platform. This is achieved
through unifying the access interface and mechanism of handling service requests through a layered approach based on
object virtualization and automatic service delivery. A fully functional prototype is developed, and its end-to-end functionality and
acceptability are tested successfully through a clinician-led pilot
study, providing evidence that both patients and caregivers are
receptive to the introduction of the proposed platform.
Index Terms: Diabetes | eHealth | Internet of Things (IoT) | multidimensional care | object virtualization | robot-assisted therapy |
مقاله انگلیسی |