Automated Monitoring and Clinical Notifications of Patient State for Neuropsychiatric Neuromodulation Studies

The proliferation of wearable technologies and the internet of things has revolutionized clinical research by opening the door to continuous at-home monitoring. These systems give clinicians better insight into patient well-being throughout daily life. Concurrently, new deep brain stimulation (DBS) devices have opened avenues for continuous neural recordings in the background of everyday activities. Behavioral data passively collected from wearables could lead to new insights into the neural mechanism underlying the pathophysiology of neurological or psychiatric disorders. Additionally, reliable multi-device monitoring systems could be used to detect or predict symptoms of a disorder or side effects of an intervention. This is particularly important in investigational neuromodulation trials in which stimulation parameters can be adjusted in the clinic to manage symptoms and side effects but the chronic response of the patient's symptoms to stimulation out of the clinic is still under investigation. Here we demonstrate a prototype continuous monitoring and email-based warning notification system, designed to incorporate data from multiple wearable devices and detect changes in clinical status for patients with neuropsychiatric disorders enrolled in DBS studies. The system is built with custom Python packages that collect data from multiple third-party APIs and synchronize different data modalities to a common second-resolution database. This backend enables automated analysis and visualization, supporting both real-time monitoring and retrospective review of patients undergoing deep brain stimulation treatment., It has been tested and deployed to the real world with several patients who wore Oura rings while undergoing deep brain stimulation treatment for obsessive-compulsive disorder. The system has been able to reliably detect changes in measurable changes in the individual's behavior and has operated successfully for over 8 months.Clinical RelevanceThis is a prototype of a continuous monitoring and email-notification system that will allow clinicians to automatically monitor patient states and receive notifications of behavioral changes, thereby improving patient outcomes and increasing the safety of clinical trials, especially those where stimulation may have an unknown effect on the patient while outside of the clinic.