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      A Human-Centered Design Methodology to Enhance the Usability, Human Factors, and User Experience of Connected Health Systems: A Three-Phase Methodology

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          Abstract

          Background

          Design processes such as human-centered design, which involve the end user throughout the product development and testing process, can be crucial in ensuring that the product meets the needs and capabilities of the user, particularly in terms of safety and user experience. The structured and iterative nature of human-centered design can often present a challenge when design teams are faced with the necessary, rapid, product development life cycles associated with the competitive connected health industry.

          Objective

          We wanted to derive a structured methodology that followed the principles of human-centered design that would allow designers and developers to ensure that the needs of the user are taken into account throughout the design process, while maintaining a rapid pace of development. In this paper, we present the methodology and its rationale before outlining how it was applied to assess and enhance the usability, human factors, and user experience of a connected health system known as the Wireless Insole for Independent and Safe Elderly Living (WIISEL) system, a system designed to continuously assess fall risk by measuring gait and balance parameters associated with fall risk.

          Methods

          We derived a three-phase methodology. In Phase 1 we emphasized the construction of a use case document. This document can be used to detail the context of use of the system by utilizing storyboarding, paper prototypes, and mock-ups in conjunction with user interviews to gather insightful user feedback on different proposed concepts. In Phase 2 we emphasized the use of expert usability inspections such as heuristic evaluations and cognitive walkthroughs with small multidisciplinary groups to review the prototypes born out of the Phase 1 feedback. Finally, in Phase 3 we emphasized classical user testing with target end users, using various metrics to measure the user experience and improve the final prototypes.

          Results

          We report a successful implementation of the methodology for the design and development of a system for detecting and predicting falls in older adults. We describe in detail what testing and evaluation activities we carried out to effectively test the system and overcome usability and human factors problems.

          Conclusions

          We feel this methodology can be applied to a wide variety of connected health devices and systems. We consider this a methodology that can be scaled to different-sized projects accordingly.

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          Most cited references67

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          A key contemporary trend emerging in big data science is the quantified self (QS)-individuals engaged in the self-tracking of any kind of biological, physical, behavioral, or environmental information as n=1 individuals or in groups. There are opportunities for big data scientists to develop new models to support QS data collection, integration, and analysis, and also to lead in defining open-access database resources and privacy standards for how personal data is used. Next-generation QS applications could include tools for rendering QS data meaningful in behavior change, establishing baselines and variability in objective metrics, applying new kinds of pattern recognition techniques, and aggregating multiple self-tracking data streams from wearable electronics, biosensors, mobile phones, genomic data, and cloud-based services. The long-term vision of QS activity is that of a systemic monitoring approach where an individual's continuous personal information climate provides real-time performance optimization suggestions. There are some potential limitations related to QS activity-barriers to widespread adoption and a critique regarding scientific soundness-but these may be overcome. One interesting aspect of QS activity is that it is fundamentally a quantitative and qualitative phenomenon since it includes both the collection of objective metrics data and the subjective experience of the impact of these data. Some of this dynamic is being explored as the quantified self is becoming the qualified self in two new ways: by applying QS methods to the tracking of qualitative phenomena such as mood, and by understanding that QS data collection is just the first step in creating qualitative feedback loops for behavior change. In the long-term future, the quantified self may become additionally transformed into the extended exoself as data quantification and self-tracking enable the development of new sense capabilities that are not possible with ordinary senses. The individual body becomes a more knowable, calculable, and administrable object through QS activity, and individuals have an increasingly intimate relationship with data as it mediates the experience of reality.
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              New directions in eHealth communication: opportunities and challenges.

              This article reviews key communication issues involved in the design of effective and humane eHealth applications to help guide strategic development and implementation of health information technologies. There is a communication revolution brewing in the delivery of health care and the promotion of health fueled by the growth of powerful new health information technologies. The development, adoption, and implementation of a broad range of new eHealth applications (such as online health information websites, interactive electronic health records, health decision support programs, tailored health education programs, health care system portals, mobile health communication programs, and advanced telehealth applications) holds tremendous promise to increase consumer and provider access to relevant health information, enhance the quality of care, reduce health care errors, increase collaboration, and encourage the adoption of healthy behaviors. With the growth of new and exciting health information technology opportunities, however, comes the daunting responsibility to design interoperable, easy to use, engaging, and accessible eHealth applications that communicate the right information needed to guide health care and health promotion for diverse audiences. Copyright 2010. Published by Elsevier Ireland Ltd.
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                Author and article information

                Contributors
                Journal
                JMIR Hum Factors
                JMIR Hum Factors
                JMIR Human Factors
                JMIR Human Factors
                JMIR Publications (Toronto, Canada )
                2292-9495
                Jan-Mar 2017
                16 March 2017
                : 4
                : 1
                : e8
                Affiliations
                [1] 1Electrical & Electronic Engineering School of Engineering & Informatics National University of Ireland Galway GalwayIreland
                [2] 2HUMAN MOVEMENT LABORATORY CÚRAM SFI Centre for Research in Medical Devices NUI Galway GalwayIreland
                [3] 3General Practice School of Medicine National University of Ireland Galway GalwayIreland
                [4] 4Georgia Institute of Technology Center for Advanced Communications Policy (CACP) Atlanta, GAUnited States
                [5] 5Irish Centre for Social Gerontology National University of Ireland Galway GalwayIreland
                [6] 6Physiology School of Medicine NUI Galway GalwayIreland
                Author notes
                Corresponding Author: Leo R Quinlan leo.quinlan@ 123456nuigalway.ie
                Author information
                http://orcid.org/0000-0002-6208-4049
                http://orcid.org/0000-0002-6153-9363
                http://orcid.org/0000-0002-9678-2654
                http://orcid.org/0000-0002-6649-3309
                http://orcid.org/0000-0003-4909-1487
                http://orcid.org/0000-0002-4011-6732
                http://orcid.org/0000-0002-1885-814X
                Article
                v4i1e8
                10.2196/humanfactors.5443
                5374275
                28302594
                50899420-d77d-4dc9-b9cc-4e010503709f
                ©Richard Harte, Liam Glynn, Alejandro Rodríguez-Molinero, Paul MA Baker, Thomas Scharf, Leo R Quinlan, Gearóid ÓLaighin. Originally published in JMIR Human Factors (http://humanfactors.jmir.org), 16.03.2017.

                This is an open-access article distributed under the terms of the Creative Commons Attribution License ( http://creativecommons.org/licenses/by/2.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in JMIR Human Factors, is properly cited. The complete bibliographic information, a link to the original publication on http://humanfactors.jmir.org, as well as this copyright and license information must be included.

                History
                : 22 December 2015
                : 23 March 2016
                : 31 October 2016
                : 12 January 2017
                Categories
                Original Paper
                Original Paper

                human-centered design,user-centered design,usability testing,user interface design,connected health,human factors,mhealth

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