Sleep plays an important role in brain recovery and functioning making it a key marker to measure in the prognostication of mild traumatic brain injury (mTBI). Sleep disruption following injury can be multi-faceted, with different sleep profiles reflecting different injury types and recovery trajectories. In this work stream, we will capture different aspects of sleep using a variety of established and scalable techniques that can be captured remotely, non-invasively and cost-effectively.
Objective sleep data will be captured using wrist-worn actigraphy and simultaneous sleep diary entries via an app. This non-invasive wearable technology detects movement allowing for an estimation of sleep-wake patterns over extended periods of time (several weeks). Through the application of established algorithms to actigraphy data, we will obtain important quantifiable information about the sleep-wake cycle across the course of recovery following mTBI.
Subjective sleep data will be captured using an array of established self-report measures. The subjective perception of sleep can be particularly useful in clinical assessments, including the long-term prognosis of mTBI. Our sleep questionnaire platform will include the PSQI (sleep quality), ISI (insomnia severity), ESS (daytime sleepiness), and FSS (Fatigue severity) alongside other questionnaires. Together with our objective monitoring approaches, these questionnaires will form a complete picture of sleep health, including sleep duration, timing or regularity, sleep quality, as well as highlighting any risk of common sleep disorders.
In this workstream we aim to identify the most important sleep biomarkers for the prognostication of mTBI and determine whether we can improve mTBI prognosis overall through merging sleep biomarkers with other cutting-edge techniques captured in the program. Together, this will improve the future management of mTBI to ensure better outcomes for patients.
Lead researchers