A situation-aware pervasive approach for assessing therapeutic goals in healthcare environment

Lopes, João Ladislau Barbará; Souza, Rodrigo Santos de; Geyer, Cláudio F. R.; Souza, Alexandre; Davet, Patricia; Pernas, Ana Marilza; Yamin, Adenauer

doi:10.1145/2851613.2851684

Cited by 3 publications

(3 citation statements)

References 7 publications

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“…The use of non-medical devices to maintain or restore health [4], [5], reinforces the importance of patient-driven health care models [6] and consumer health care models [7] that include mobile health (mHealth) applications to track lifestyle habits, wrist-band trackers, or other kind of IoT/wearable devices. There is plethora of scientific peerreview pervasive computing systems for health care [8], [9], [10]. In addition, the International Data Corporation (IDC) predicted that the wearable market will continue to grow.…”

Section: Introductionmentioning

confidence: 99%

Visions and Challenges in Managing and Preserving Data to Measure Quality of Life

Estrada-Galiñanes¹,

Wac²

2018

2018 IEEE 3rd International Workshops on Foundations and Applications of Self* Systems (FAS*W)

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Health-related data analysis plays an important role in self-knowledge, disease prevention, diagnosis, and quality of life assessment. With the advent of data-driven solutions, a myriad of apps and Internet of Things (IoT) devices (wearables, home-medical sensors, etc) facilitates data collection and provide cloud storage with a central administration. More recently, blockchain and other distributed ledgers became available as alternative storage options based on decentralised organisation systems. We bring attention to the human data bleeding problem and argue that neither centralised nor decentralised system organisations are a magic bullet for data-driven innovation if individual, community and societal values are ignored. The motivation for this position paper is to elaborate on strategies to protect privacy as well as to encourage data sharing and support open data without requiring a complex access protocol for researchers. Our main contribution is to outline the design of a self-regulated Open Health Archive (OHA) system with focus on quality of life (QoL) data.

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Section: Introductionmentioning

confidence: 99%

Visions and Challenges in Managing and Preserving Data to Measure Quality of Life

Estrada-Galiñanes¹,

Wac²

2018

2018 IEEE 3rd International Workshops on Foundations and Applications of Self* Systems (FAS*W)

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“…A health cooperative model can be self-sustainable by reinvesting earnings from data but challenges remain [81]. Pilot studies based on the cooperative model have been built in different places, Swiss 13 and Dutch 14 initiatives promote new forms of citizen-driven data collection, and cooperatives at the local level and a federation of cooperatives at a global level [82]. Healthcare professionals and many individuals may, nonetheless, restrain from participation.…”

Section: Financial and Budgetary Issuesmentioning

confidence: 99%

“…At the same time, the use of non-medical devices to maintain or restore health [7,8], reinforces the importance of patient-driven health care models [9] and consumer health care models [10] that include mobile health (mHealth) applications to track lifestyle habits, wrist-band trackers, or other kind of Internet of Things (IoT)/wearable devices. There is a plethora of scientific peer-review pervasive computing systems for health care [11][12][13][14]. vations.…”

Section: Introductionmentioning

confidence: 99%

Collecting, exploring and sharing personal data: Why, how and where

Estrada-Galiñanes

Wac

2020

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New, multi-channel personal data sources (like heart rate, sleep patterns, travel patterns, or social activities) are enabled by ever increased availability of miniaturised technologies embedded within smartphones and wearables. These data sources enable personal self-management of lifestyle choices (e.g., exercise, move to a bike-friendly area) and, on a large scale, scientific discoveries to improve health and quality of life. However, there are no simple and reliable ways for individuals to securely collect, explore and share these sources. Additionally, much data is also wasted, especially when the technology provider ceases to exist, leaving the users without any opportunity to retrieve own datasets from "dead" devices or systems. Our research reveals evidence of what we term human data bleeding and offers guidance on how to address current issues by reasoning upon five core aspects, namely technological, financial, legal, institutional and cultural factors. To this end, we present preliminary specifications of an open platform for personal data storage and quality of life research. The Open Health Archive (OHA) is a platform that would support individual, community and societal needs by facilitating collecting, exploring and sharing personal health and QoL data.

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A Situation Awareness Computational Intelligent Model for Metabolic Syndrome Management

Lofù

Pazienza²,

Ardito

et al. 2022

2022 IEEE Conference on Cognitive and Computational Aspects of Situation Management (CogSIMA)

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A situation-aware pervasive approach for assessing therapeutic goals in healthcare environment

Cited by 3 publications

References 7 publications

Visions and Challenges in Managing and Preserving Data to Measure Quality of Life

Visions and Challenges in Managing and Preserving Data to Measure Quality of Life

Collecting, exploring and sharing personal data: Why, how and where

A Situation Awareness Computational Intelligent Model for Metabolic Syndrome Management

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