Brain Activation in Response to Personalized Behavioral and Physiological Feedback From Self-Monitoring Technology: Pilot Study (original) (raw)

The ENGAGE study: Integrating neuroimaging, virtual reality and smartphone sensing to understand self-regulation for managing depression and obesity in a precision medicine model

Behaviour research and therapy, 2017

Precision medicine models for personalizing achieving sustained behavior change are largely outside of current clinical practice. Yet, changing self-regulatory behaviors is fundamental to the self-management of complex lifestyle-related chronic conditions such as depression and obesity - two top contributors to the global burden of disease and disability. To optimize treatments and address these burdens, behavior change and self-regulation must be better understood in relation to their neurobiological underpinnings. Here, we present the conceptual framework and protocol for a novel study, "Engaging self-regulation targets to understand the mechanisms of behavior change and improve mood and weight outcomes (ENGAGE)". The ENGAGE study integrates neuroscience with behavioral science to better understand the self-regulation related mechanisms of behavior change for improving mood and weight outcomes among adults with comorbid depression and obesity. We collect assays of three ...

Detecting Smartwatch-Based Behavior Change in Response to a Multi-Domain Brain Health Intervention

ACM Transactions on Computing for Healthcare

In this study, we introduce and validate a computational method to detect lifestyle change that occurs in response to a multi-domain healthy brain aging intervention. To detect behavior change, digital behavior markers are extracted from smartwatch sensor data and a permutation-based change detection algorithm quantifies the change in marker-based behavior from a pre-intervention, 1-week baseline. To validate the method, we verify that changes are successfully detected from synthetic data with known pattern differences. Next, we employ this method to detect overall behavior change for n = 28 brain health intervention subjects and n = 17 age-matched control subjects. For these individuals, we observe a monotonic increase in behavior change from the baseline week with a slope of 0.7460 for the intervention group and a slope of 0.0230 for the control group. Finally, we utilize a random forest algorithm to perform leave-one-subject-out prediction of intervention versus control subjects ...

Self-monitoring technologies to promote healthy behavior in the long term

2020

Nowadays, the world is facing two major issues: Non-Communicable Diseases and ageing population. Although committing in healthy behaviors has been shown to be highly beneficial for individual’s health and well-being, the challenge remains in motivating the adoption and the long-term engagement in such behaviors. This thesis focuses on the efficiency of self-monitoring technologies to promote positive change in the long-term on modifiable behaviors, mainly regarding physical activity and nutrition. It sheds light on the opportunities and the limitations of self-monitoring, gamified, social and conversational applications and intends to provide guidelines for designing these technologies for specific population, namely: chronically ill and elderly patients. Overall, the work conducted within this dissertation offers new perspectives on the design of self-monitoring technologies for elderly and chronically-ill patients. It makes several research contributions that are of interest to th...

A Social Neuroscience Perspective on Physical Activity

Journal of Sport and Exercise Psychology, 2008

The objective of this investigation was to examine the cognitive characteristics of individuals who demonstrate successful and unsuccessful self-regulation of physical activity behavior. In Study 1, participants articulated 1-week intentions for physical activity and wore a triaxial accelerometer over the subsequent 7 days. Among those who were motivated to increase their physical activity, those who were most and least successful were administered an IQ test. In Study 2, a second sample of participants completed the same protocol and a smaller subset of matched participants attended a functional imaging (fMRI) session. In Study 1, successful self-regulators (SSRs) scored significantly higher than unsuccessful self-regulators (USRs) on a test of general cognitive ability, and this difference could not be accounted for by favorability of attitudes toward physical activity or conscientiousness. In Study 2, the IQ effect was replicated, with SSRs showing a full standard deviation advan...

Sedentary Behavior and the Use of Wearable Technology: An Editorial

International Journal of Environmental Research and Public Health, 2020

Globally, we continue to face a mounting issue of obesity combined with inactivity; sedentary behaviour is independently associated with poor health outcomes including disease and mortality. As such, exploring ways to try to reduce sedentary behaviour and decrease the risk of diseases is an important area of consideration. The role of wearable technology, such as fitness trackers, to encourage and subsequently increase physical activity is relatively well documented. These devices have been successful at encouraging populations to increase daily activity levels. While time being sedentary is often correlated with physical activity participation, this is not always the case. Therefore, it may be just as important to consider the activity an individual is not doing when evaluating health and well-being. This Editorial will summarize the importance of distinguishing between physical activity and sedentary behaviour. It will also discuss how wearable technology, in the form of fitness t...