About This Project
Panic attacks are intense episodes of discomfort, fear, and feelings of helplessness experienced by millions of people every year. Fortunately, panic attacks can be effectively treated with biofeedback therapy, which combines the minute-by-minute tracking of respiratory rate, heart rate, and subjective anxiety levels. Unfortunately, there are currently no widely accessible, accurate means for delivering this therapy. We aim to create an app to disseminate this intervention to anyone in need.
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What is the context of this research?
In panic attacks, intense emotions lead to hyperventilation, which increases blood pH and leads to a cascade of uncomfortable symptoms such as dizziness, heart palpitations, and nausea (Teachman, 2010). Symptoms develop abruptly and peak within 10 minutes (Meuret, 2001).
During biofeedback therapy, patients track their respiratory and heart rates during panic attacks using electronic instruments. This therapy has been shown to make improvements in 81% of patients, who continued to remain panic-free at 2 years follow-up (Craske, 1991). Biofeedback therapy is said to help individuals “feel more in control of their bodily reactions and react less fearfully to them," thus ending the cycle of panic (Bouton, 2001).
What is the significance of this project?
Roughly 2 million young adults have had a panic attack in the last 12 months. If untreated, panic attacks can lead to mental illnesses including phobias, depression, and substance use disorders. Currently, biofeedback therapy is only accessible to research study participants using cumbersome hand-held respiratory rate monitors to track their symptoms. Current standard of care includes significant costs and wait times for clinic services, which often do not have equipment to collect physiological data for biofeedback therapy. Home-based therapies are as effective as treatment with a clinician (Wright, 2000), thus we aim to develop an app to 1) accurately track physiological signals, and 2) provide panic attack sufferers access to biofeedback therapy wherever and whenever it's needed.
What are the goals of the project?
The goal of this project is to develop and validate algorithms for extracting heart and respiratory rate from the high-definition (HD) video and/or inertial sensor data sampled by a mobile phone. These algorithms will ultimately form the heart of our app for providing biofeedback therapy to panic attack sufferers as they enable visualization of how these physiological signals are changing during each panic attack episode. Once funded, we will create these algorithms and recruit subjects for our validation study. We will conduct our study by collecting data from 20 participants and establish the accuracy of our algorithms relative to the techniques currently used in clinical practice. Ultimately, we will describe this study and the results in a technical publication.
Paramount to the success of this project are methods for estimating respiratory rate and heart rate that are accurate and enable a seamless user experience. This funding will enable development of these methods, and therefore success of the research project.
Specifically, funds are allocated for the research and development of the heart rate and respiratory rate signal processing algorithms. Once we develop these algorithms, we will recruit subjects (N=20) and design a research study to establish their accuracy relative to techniques used in the clinic today. We will then execute this study, and compensate subjects $10 for their time. Following completion of the study, we will perform the data analysis necessary to establish the accuracy of our algorithms and publish the results.
Meet the Team
Dr. Ryan McGinnis, a PhD in mechanical engineering, and Ellen McGinnis, a PhD student in clinical psychology, share a love of research...and for each other. They got married in 2012 after 10 years of friendship and dating. Over dinner one night, they decided to join their seemingly separate research programs to better study the biomechanics and physiology of mental health. This project concept was created while riding the T together to the Boston Museum of Science.
I began my PhD in Clinical Science at the University of Michigan in 2011 and have been focused on improving assessment and intervention of anxiety and depressive disorders in both therapeutic and research contexts.
I completed my PhD and Postdoctoral Training in kinesiology and mechanical engineering at the University of Michigan in 2013. My research is focused on developing and validating methods for characterizing human biomechanics and physiology that leverage recent advances in wearable technology. I have recently been working to incorporate some of these findings into products that can help improve people’s lives.
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