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We will also give an example of environmental state assessment technologies for noise, pollution, or transportation usage, influencing the individual’s state and behaviors in all three above-mentioned domains. We discuss these technologies in terms of their design space and provided features, and their strengths and barriers for user adoption and scaling.
The challenge lies in the methodological aspects of the approach, where the data collected in the individual’s daily life environments must be of a particular quality to inform the clinical decisions taken. The questions are raised about where, when and what to measure, how to make sense of data, how to extract and fuse relevant features, how to use the data in individual cases (“personalized analytics”), what to consider as constituting the evidence on effectiveness of a given treatment or rehabilitation activity, and how to link that to clinical outcomes for a given patient.
Healthcare has changed more over the last 50 years than at any other time in history. The convergence of the hypothetical-deductive scientific approach, advances in disciplines (such as chemistry, biology, genetics and imaging, to name but a few) in a fast-evolving information-technology age is about to change the landscape of health beyond recognition. Not unusually, from an historical perspective, most of the influences conveying these changes do not originate from health care providers.
Access to information and technologies (e.g. to measure health parameters) is increasingly open to any citizen, who tends to be increasingly involved as their own "physician." This trend will continue and contribute to the empowerment of patients but will also totally change the approach doctors take in society.
This presentation aims to take the audience on a fabulous journey to the technological future. It will illustrate the key disruptive evolutions at the origin of the increasing role of technology in society, as well as in healthcare systems. This is not science fiction....the future is now!
“Know Thyself” is a motto leading the Quantified Self (QS) movement, which at first originated as a ‘hobby project’ driven by self-discovery, and is now being leveraged in wellness and healthcare. QS practitioners rely on the wealth of digital data originating from wearables, applications, and self-reports that enable them to assess diverse domains of their daily life. That includes their physical state (e.g., mobility, steps), psychological state (e.g., mood), social interactions (e.g., a number of Facebook “likes”) and environmental context they are in (e.g., pollution). The World Health Organization (WHO) recognizes these four QS domains as contributing to individual’s Quality of Life (QoL), with health spanning across all four domains. The collected QS data enables an individual’s state and behavioral patterns to be assessed through these different QoL domains, based on which individualized feedback can be provided, in turn enabling the improvement of the individual’s state and QoL. The evidence of causality between QS and QoL is still being established, since only data from limited cases and domains exist so far.
In this talk, I will discuss the state of this evidence via a semi-systematic review of the exemplary QS practices documented in 609 QS practitioners’ talks, and a review of the 438 latest available personal wearable technologies enabling QS. I will discuss the challenges and opportunities for QS to become an integral part of the future of healthcare and QoL-driven solutions. Some of the opportunities include using QS technologies as different types of affordances supporting the goal-oriented actions by the individual, and in turn improving their QoL.