How smartphones are changing the face of mobile and participatory healthcare: an overview, with example from eCAALYX

By Maged N. Kamel Boulos, Steve Wheeler, Carlos Tavares, Ray B. Jones. BioMedical Engineering OnLine, 2011

1,132 citations recorded by the source corpus.

The latest generation of smartphones are increasingly viewed as handheld computers rather than as phones, due to their powerful on-board computing capability, capacious memories, large screens and open operating systems that encourage application development. This paper provides a brief state-of-the-art overview of health and healthcare smartphone apps (applications) on the market today, including emerging trends and market uptake. Platforms available today include Android, Apple iOS, RIM BlackBerry, Symbian, and Windows (Windows Mobile 6.x and the emerging Windows Phone 7 platform). The paper covers apps targeting both laypersons/patients and healthcare professionals in various scenarios, e.g., health, fitness and lifestyle education and management apps; ambient assisted living apps; continuing professional education tools; and apps for public health surveillance. Among the surveyed apps are those assisting in chronic disease management, whether as standalone apps or part of a BAN (Body Area Network) and remote server configuration. We describe in detail the development of a smartphone app within eCAALYX (Enhanced Complete Ambient Assisted Living Experiment, 2009-2012), an EU-funded project for older people with multiple chronic conditions. The eCAALYX Android smartphone app receives input from a BAN (a patient-wearable smart garment with wireless health sensors) and the GPS (Global Positioning System) location sensor in the smartphone, and communicates over the Internet with a remote server accessible by healthcare professionals who are in charge of the remote monitoring and management of the older patient with multiple chronic conditions. Finally, we briefly discuss barriers to adoption of health and healthcare smartphone apps (e.g., cost, network bandwidth and battery power efficiency, usability, privacy issues, etc.), as well as some workarounds to mitigate those barriers.

Subfields: Computer Vision and Pattern Recognition, Demography, General Health Professions

View Paper: https://www.semanticscholar.org/paper/88599a1e56a446eec7f3caec382c94d78a11f846

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Computer Vision and Pattern Recognition

In Demography

In General Health Professions

Citations in the corpus

Health 2050: The Realization of Personalized Medicine through Crowdsourcing, the Quantified Self, and the Participatory Biocitizen (2012, background): “Application downloads grew explosively from 300 million in 2009 to five billion in 2010, and over 7,000 apps are health-related [39].”
Mobile medical and health apps: state of the art, concerns, regulatory control and certification (2014, background): “, the CAALYX/eCAALYX system described in [2,54].”
Mapping mHealth Research: A Decade of Evolution (2013, background): “Therefore, iPhones and similar devices are potentially very interesting for application in health care—they already integrate most of the features that researchers previously had to add to traditional mobile phones in order to use them for health-related purposes and monitoring [15,16].”
Putting the ‘app’ in Happiness: A Randomised Controlled Trial of a Smartphone-Based Mindfulness Intervention to Enhance Wellbeing (2016, background): “’’ Discernable links between smartphone technology and positive health outcomes have already been recognized in many fields, with preventative health and clinical interventions leading the way (Stevens and Bryan 2012; Ozdalga et al. 2012; Hebden et al. 2012; Boulos et al. 2011; Luxton et al. 2011; B”
The role of Information and Communication Technologies in healthcare: taxonomies, perspectives, and challenges (2018, background): “Systems—even on a micrometer or nanometer scale—are included in the area of robotics if they perform all three essential functions defining a robot: (i) acting on environmental stimuli in combination with (ii) sensing and (iii) logical reasoning [37].”
Physiological Parameter Monitoring from Optical Recordings with a Mobile Phone (2011, neutral): “These factors make smart phones an ideal option as a “takeanywhere” physiological monitor without the need for additional hardware, and their potential has been explored for many medical telemonitoring applications [1, 2].”
The Role of Healthcare Robots for Older People at Home: A Review (2014, background): “It is able to inform the individual’s healthcare provider over the Internet about the condition of their patient [47].”
Smartphone App Use Among Medical Providers in ACGME Training Programs (2012, background): “Smartphone apps, such as those available in the Apple and Android app stores, are quickly becoming integrated into clinical practice by physicians [1].”
mHealth 2.0: Experiences, Possibilities, and Perspectives (2014, background): “In addition, studies show a high attrition rate for Internet interventions and mobile applications [9,10], which may be a reflection of an early interest in the novelty of the application, with a decline in eagerness as the novelty of the intervention wears off.”
Ambient Assisted Living Healthcare Frameworks, Platforms, Standards, and Quality Attributes (2014, neutral): “[72,73].”
Systematic review of smartphone-based passive sensing for health and wellbeing (2017, background): “Patients ’ disease management and preventive health behaviors bene ﬁ t from the collection and tracking of health-related data, from daily weights to calorie counts to pain scores [1,2].”
A Systematic Review of Healthcare Applications for Smartphones (2012, background): “Users can see current medical reports on their smartphones based on sensor data, perform new measurements, and communicate with caregivers through the application [83].”
A Real-Time Health Monitoring System for Remote Cardiac Patients Using Smartphone and Wearable Sensors (2015, background): “It should be noted that over 94% of the world population, that is, 6.8 billion people, are the subscribers of cell phone and about 2 International Journal of Telemedicine and Applications 2.7 billion subscribers are using Internet [12].”
The Smartphone in Medicine: A Review of Current and Potential Use Among Physicians and Students (2012, background): “Recognizing the challenges of a growing elderly population, one group worked on the European Union-funded project Enhanced Complete Ambient Assisted Living Experiment [14].”
Can Mobile Phones Improve Gender Equality and Nutrition? Panel Data Evidence from Farm Households in Uganda (2017, background): “…in various sectors, including agriculture, health, education, financial services, and many more (Fozdar and Kumar, 2007; Jensen, 2007; Duncombe and Boateng, 2009; Aker and Mbiti, 2010; Aker, 2011; Boulos et al., 2011; Aker and Ksoll, 2016; Blauw and Franses, 2016, Nakasone and Torero, 2016).”
Enabling Effective Programming and Flexible Management of Efficient Body Sensor Network Applications (2013, background): “Furthermore, through their Internet connectivity capabilities, they can transmit sensed and/or processed data to remote servers and cloud services for offline and long-term analysis [30].”