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Lukasz Piwek, David A Ellis
Smartphones continue to provide huge potential for psychological science and the advent of novel research frameworks brings new opportunities for researchers who have previously struggled to develop smartphone applications. However, despite this renewed promise, smartphones have failed to become a standard item within psychological research. Here we consider the key issues that continue to limit smartphone adoption within psychological science and how these barriers might be diminishing in light of ResearchKit and other recent methodological developments...
2016: Frontiers in Psychology
E Ray Dorsey, Yu-Feng Yvonne Chan, Michael V McConnell, Stanley Y Shaw, Andrew D Trister, Stephen H Friend
Because of their growing popularity and functionality, smartphones are increasingly valuable potential tools for health and medical research. Using ResearchKit, Apple's open-source platform to build applications ("apps") for smartphone research, collaborators have developed apps for researching asthma, breast cancer, cardiovascular disease, type 2 diabetes, and Parkinson disease. These research apps enhance widespread participation by removing geographical barriers to participation, provide novel ways to motivate healthy behaviors, facilitate high-frequency assessments, and enable more objective data collection...
April 26, 2016: Academic Medicine: Journal of the Association of American Medical Colleges
Pascal B Pfiffner, Isaac Pinyol, Marc D Natter, Kenneth D Mandl
A renewed interest by consumer information technology giants in the healthcare domain is focused on transforming smartphones into personal health data storage devices. With the introduction of the open source ResearchKit, Apple provides a framework for researchers to inform and consent research subjects, and to readily collect personal health data and patient reported outcomes (PRO) from distributed populations. However, being research backend agnostic, ResearchKit does not provide data transmission facilities, leaving research apps disconnected from the health system...
2016: PloS One
Brian M Bot, Christine Suver, Elias Chaibub Neto, Michael Kellen, Arno Klein, Christopher Bare, Megan Doerr, Abhishek Pratap, John Wilbanks, E Ray Dorsey, Stephen H Friend, Andrew D Trister
Current measures of health and disease are often insensitive, episodic, and subjective. Further, these measures generally are not designed to provide meaningful feedback to individuals. The impact of high-resolution activity data collected from mobile phones is only beginning to be explored. Here we present data from mPower, a clinical observational study about Parkinson disease conducted purely through an iPhone app interface. The study interrogated aspects of this movement disorder through surveys and frequent sensor-based recordings from participants with and without Parkinson disease...
2016: Scientific Data
Elias Chaibub Neto, Brian M Bot, Thanneer Perumal, Larsson Omberg, Justin Guinney, Mike Kellen, Arno Klein, Stephen H Friend, Andrew D Trister
We propose hypothesis tests for detecting dopaminergic medication response in Parkinson disease patients, using longitudinal sensor data collected by smartphones. The processed data is composed of multiple features extracted from active tapping tasks performed by the participant on a daily basis, before and after medication, over several months. Each extracted feature corresponds to a time series of measurements annotated according to whether the measurement was taken before or after the patient has taken his/her medication...
2016: Pacific Symposium on Biocomputing
Michael Eisenstein
No abstract text is available yet for this article.
October 2015: Nature Biotechnology
Jennifer Jardine, Jonathan Fisher, Benjamin Carrick
No abstract text is available yet for this article.
August 2015: Journal of the Royal Society of Medicine
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