RADAR-Base: Open Source Mobile Health Platform for Collecting, Monitoring, and Analyzing Data Using Sensors, Wearables, and Mobile Devices

Ranjan, Yatharth; Rashid, Zulqarnain; Stewart, Callum; Conde, Pauline; Begale, Mark; Verbeeck, Denny; Boettcher, Sebastian; Hyve,; Dobson, Richard; Folarin, Amos

doi:10.2196/11734

Cited by 190 publications

(141 citation statements)

References 9 publications

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“…Recently, open source platforms have been developed to make the collection of passive data from smartphone sensors easier for researchers, facilitating the use of passive data in research even further. A few examples are the AWARE framework (Ferreira et al 2015), RADAR-base (Ranjan et al 2019) and the Insight app (Montag et al 2019).…”

Section: Objective Datamentioning

confidence: 99%

Smartphone-Based Ecological Momentary Assessment of Well-Being: A Systematic Review and Recommendations for Future Studies

2020

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Feelings of well-being and happiness fluctuate over time and contexts. Ecological Momentary Assessment (EMA) studies can capture fluctuations in momentary behavior, and experiences by assessing these multiple times per day. Traditionally, EMA was performed using pen and paper. Recently, due to technological advances EMA studies can be conducted more easily with smartphones, a device ubiquitous in our society. The goal of this review was to evaluate the literature on smartphone-based EMA in well-being research in healthy subjects. The systematic review was conducted according to the Preferred Reporting Items for Systematic Review and Meta-Analysis (PRISMA) guidelines. Searching PubMed and Web of Science, we identified 53 studies using smartphone-based EMA of well-being. Studies were heterogeneous in designs, context, and measures. The average study duration was 12.8 days, with well-being assessed 2–12 times per day. Half of the studies included objective data (e.g. location). Only 47.2% reported compliance, indicating a mean of 71.6%. Well-being fluctuated daily and weekly, with higher well-being in evenings and weekends. These fluctuations disappeared when location and activity were accounted for. On average, being in nature and physical activity relates to higher well-being. Working relates to lower well-being, but workplace and company do influence well-being. The important advantages of using smartphones instead of other devices to collect EMAs are the easier data collection and flexible designs. Smartphone-based EMA reach far larger maximum sample sizes and more easily add objective data to their designs than palm-top/PDA studies. Smartphone-based EMA research is feasible to gain insight in well-being fluctuations and its determinants and offers the opportunity for parallel objective data collection. Most studies currently focus on group comparisons, while studies on individual differences in well-being patterns and fluctuations are lacking. We provide recommendations for future smartphone-based EMA research regarding measures, objective data and analyses.

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Section: Objective Datamentioning

confidence: 99%

Smartphone-Based Ecological Momentary Assessment of Well-Being: A Systematic Review and Recommendations for Future Studies

2020

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“…The results are based on the combination of the surveys. All data was managed by the open-source RADAR-based platform (www.radar-base.org) [2].…”

Section: Study Participantsmentioning

confidence: 99%

“…Remote Assessment of Disease and Relapse in Central Nervous System Disorders (RADAR-CNS) is an Innovative Medicine Initiative-funded project aimed at monitoring major depressive disorders, epilepsy, and multiple sclerosis (MS) using wearable devices and smartphone technology [2].…”

Section: Introductionmentioning

confidence: 99%

Real-time assessment of COVID-19 prevalence among multiple sclerosis patients: a multicenter European study

et al. 2020

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We assessed the prevalence and impact of COVID-19 among multiple sclerosis (MS) patients across Europe by leveraging participant data collected as part of the ongoing EU IMI2 RADAR-CNS major programme aimed at finding new ways of monitoring neurological disorders using wearable devices and smartphone technology. In the present study, 399 patients of RADAR-MS have been included (mean age 43.9 years, 60.7% females) with 87/399 patients (21.8%) reporting major symptoms suggestive of COVID-19. A trend for an increased risk of COVID-19 symptoms under alemtuzumab and cladribine treatments in comparison to injectables was observed. Remote monitoring technologies may support health authorities in monitoring and containing the ongoing pandemic.

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“…This concept has already been developed among people with Major Depressive Disorder (MDD) to explore if longitudinal tracking using RMT can capture information predictive of depressive relapse and other key clinical outcomes (73). RMTs also offer a unique capability to provide continuous objective data, through passive data streaming methods (72). Sleep quality and quantity variables (e.g., duration of sleep and time spent in REM cycles) can be monitored remotely through actigraphy and consumer-wearable activity trackers (74,75).…”

Section: Mood Measurement For Remote Memory Clinicsmentioning

confidence: 99%

Implementing Remote Memory Clinics to Enhance Clinical Care During and After COVID-19

et al. 2020

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Social isolation is likely to be recommended for older adults due to COVID-19, with ongoing reduced clinical contact suggested for this population. This has increased the need for remote memory clinics, we therefore review the literature, current practices and guidelines on organizing such remote memory clinics, focusing on assessment of cognition, function and other relevant measurements, proposing a novel pathway based on three levels of complexity: simple telephone or video-based interviews and testing using available tests (Level 1), digitized and validated methods based on standard pen-and-paper tests and scales (Level 2), and finally fully digitized cognitive batteries and remote measurement technologies (RMTs, Level 3). Pros and cons of these strategies are discussed. Remotely collected data negates the need for frail patients or carers to commute to clinic and offers valuable insights into progression over time, as well as treatment responses to therapeutic interventions, providing a more realistic and contextualized environment for data-collection. Notwithstanding several challenges related to internet access, computer skills, limited evidence base and regulatory and data protection issues, digital biomarkers collected remotely have significant potential for diagnosis and symptom management in older adults and we propose a framework and pathway for how technologies can be implemented to support remote memory clinics. These platforms are also well-placed for administration of digital cognitive training and other interventions. The individual, societal and public/private costs of COVID-19 are high and will continue to rise for some time but the challenges the pandemic has placed on memory services also provides an opportunity to embrace novel approaches. Remote memory clinics' financial, logistical, clinical and practical benefits have been highlighted by COVID-19, supporting their use to not only be maintained when social distancing legislation is lifted but to be devoted extra resources and attention to fully potentiate this valuable arm of clinical assessment and care.

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RADAR-Base: Open Source Mobile Health Platform for Collecting, Monitoring, and Analyzing Data Using Sensors, Wearables, and Mobile Devices

Cited by 190 publications

References 9 publications

Smartphone-Based Ecological Momentary Assessment of Well-Being: A Systematic Review and Recommendations for Future Studies

Smartphone-Based Ecological Momentary Assessment of Well-Being: A Systematic Review and Recommendations for Future Studies

Real-time assessment of COVID-19 prevalence among multiple sclerosis patients: a multicenter European study

Implementing Remote Memory Clinics to Enhance Clinical Care During and After COVID-19

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