Semantic representation and processing of hypoglycemic events derived from wearable sensor data

Calbimonte, Jean-Paul; Ranvier, Jean-Eudes; Dubosson, Fabien; Aberer, Karl

doi:10.3233/ais-160420

Cited by 9 publications

(3 citation statements)

References 28 publications

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“…Several studies review wearable sensors in stress and pain detection [ 80 , 81 , 82 ], electrical brain activity [ 83 ], skin hardness [ 84 ], hypoglycemic events [ 85 , 86 , 87 , 88 ], and inflammation [ 89 ]. The useful physiological signs described in the mentioned studies are heart activity (i.e., ECG—Electrocardiogram) and blood volume pulse (BVP), brain activity (i.e., EEG—Electroencephalogram), muscle and neural activity (i.e., EMG—Electromyography), electrodermal activity (EDA), body temperature, and respiratory activity, which are organized in Table 2 with the attributed commercialized and divulgated wearable sensors.…”

Section: Wearable Sensors In Health Monitoringmentioning

confidence: 99%

“Listen to Your Immune System When It’s Calling for You”: Monitoring Autoimmune Diseases Using the iShU App

Ortet

Costa

2022

Sensors

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The immune system plays a key role in protecting living beings against bacteria, viruses, and fungi, among other pathogens, which may be harmful and represent a threat to our own health. However, for reasons that are not fully understood, in some people this protective mechanism accidentally attacks the organs and tissues, thus causing inflammation and leads to the development of autoimmune diseases. Remote monitoring of human health involves the use of sensor network technology as a means of capturing patient data, and wearable devices, such as smartwatches, have lately been considered good collectors of biofeedback data, owing to their easy connectivity with a mHealth system. Moreover, the use of gamification may encourage the frequent usage of such devices and behavior changes to improve self-care for autoimmune diseases. This study reports on the use of wearable sensors for inflammation surveillance and autoimmune disease management based on a literature search and evaluation of an app prototype with fifteen stakeholders, in which eight participants were diagnosed with autoimmune or inflammatory diseases and four were healthcare professionals. Of these, six were experts in human–computer interaction to assess critical aspects of user experience. The developed prototype allows the monitoring of autoimmune diseases in pre-, during-, and post-inflammatory crises, meeting the personal needs of people with this health condition. The findings suggest that the proposed prototype—iShU—achieves its purpose and the overall experience may serve as a foundation for designing inflammation surveillance and autoimmune disease management monitoring solutions.

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Section: Wearable Sensors In Health Monitoringmentioning

confidence: 99%

“Listen to Your Immune System When It’s Calling for You”: Monitoring Autoimmune Diseases Using the iShU App

Ortet

Costa

2022

Sensors

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“…This ontology is expressed using Ontology Web Language OWL and includes modular component vocabularies to represent intelligent agents with associated beliefs, desires, time, space, events, user profiles, actions, and policies for privacy. The authors of [33] present a framework for inferring semantically annotated glycemic events on the patient, which leverages data from mobile wearable sensors. The authors use a standard machine-readable data model to represent events and they include observations like temporal and location information.…”

Section: Related Workmentioning

confidence: 99%

Ontology-Based Context Event Representation, Reasoning, and Enhancing in Academic Environments

2021

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An Ambient Intelligence responds to user requests based on several contexts. A relevant context is related to what has happened in the ambient; therefore, it focuses a primordial interest on events. These involve information about time, space, or people, which is significant for modeling the context. In this paper, we propose an event-driven approach for context representation based on an ontological model. This approach is extendable and adaptable for academic domains. Moreover, the ontological model to be proposed is used in reasoning and enrichment processes with the context event information. Our event-driven approach considers five contexts as a modular perspective in the model: Person, temporal (time), physical space (location), network (resources to acquire data from the ambient), and academic events. We carried out an evaluation process for the approach based on an ontological model focused on (a) the extensibility and adaptability of use case scenarios for events in an academic environment, (b) the level of reasoning by using competence questions related to events, (c) and the consistency and coherence in the proposed model. The evaluation process shows promising results for our event-driven approach for context representation based on the ontological model.

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“…Otro trabajo relacionado a la especificación de detección de eventos y representación mediante ontologías es el de Jean-Paul Calbimonte, Jean-Eudes Ranviera, Fabien Dubosson, Karl Aberer [4] que presentan un framework para inferir eventos semánticamente de glucosa obtenidos de pacientes, mediante datos de sensores móviles desplegados en un cinturón deportivo. Este trabajo es parte del proyecto D1namo para monitoreo de la diabetes, se centra en la representación y el procesamiento de consultas de datos producidos por los sensores portátiles, utilizando tecnologías semánticas.…”

Section: Trabajos Relacionadosunclassified

Detección y representación de eventos ambientales basada en agentes

Padilla-Cuevas

Reyes‐Ortiz

Bravo

et al. 2019

JTEN

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An Intelligent environment can respond to the necessities of the users according to the context, this is so that the individuals can have the ideal climatic conditions in order to go about their activities, these conditions are related through a series of special norms. The events that we describe in this paper are in relation to the events of the environment (temperature, humidity, brightness, and presence), also involved are different variables like time, space, or person, such are important in order to be able to model what is occurring in a determined place. In this project, we propose a personalized ontological design for the academic dominion. The ontological model is utilized for the identification of environmental events according to the data acquired from the environment through the simulation of intellectual agents. Also, our ontological model is used to rationalize with the information obtained from the identified events. The model of ontologies based on events considers four contextual questions like a perspective modular: person, seasonality (weather), spatiality (location), network (resources in order to acquire environmental data) and event (academic events). And the detector is based on rules obtained from the standards of optimum climatic conditions of a physical space.

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Semantic representation and processing of hypoglycemic events derived from wearable sensor data

Cited by 9 publications

References 28 publications

“Listen to Your Immune System When It’s Calling for You”: Monitoring Autoimmune Diseases Using the iShU App

“Listen to Your Immune System When It’s Calling for You”: Monitoring Autoimmune Diseases Using the iShU App

Ontology-Based Context Event Representation, Reasoning, and Enhancing in Academic Environments

Detección y representación de eventos ambientales basada en agentes

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