Despite advancements in the field of concussion care, the individualized nature and nuances of concussion make it a difficult condition to manage. It has been shown that both complete rest or too much activity can prolong recovery from concussion, indicating there is an ideal zone of activity that can aid in concussion recovery. Heart-rate guided sub-symptom aerobic physical activity has been shown to speed concussion recovery and provide an objective measure for patients with concussion to inform their rehabilitative physical activities. However, no such equal exists for guiding cognitive pacing.~This study will utilize a wearable EEG headband linked to a mobile application to monitor cognitive activity post-concussion, and alert a patient when it is time to take a mental break. Personalized cloud-based machine learning algorithms will analyze EEG data in real-time for neural features of mental workload and mental fatigue, and will notify a patient when it is time to rest based on these measures. These algorithms have been developed and validated on healthy participants, and refined in concussion patients in an ongoing observational investigation yet to be published. The proposed investigation is a randomized, prospective pilot study to test the early efficacy of this technology in concussion recovery compared to standard of care alone. The results of this pilot investigation will be used to inform a future large-scale clinical trial to confirm the efficacy of this technology on concussion recovery.
This investigation will assess the utility of a novel wearable electroencephalography (EEG) headband linked to a mobile application to monitor cognitive activity post-concussion, and alert a patient when it is time to take a mental break. Personalized cloud-based machine learning algorithms will analyze EEG data in real-time for neural features indicative of mental workload and mental fatigue, and will notify a patient when it is time to rest based on these measures. It is hypothesized that this technology may provide a much needed data-driven management tool to better inform the cognitive pacing process for both patients with concussion, as well as their clinicians.