Smartphones take part in any aspect of human behavior and as such, they offer a great promise as a probe of human behavior. We developed a technology for passive sensing of human behavior using smartphones. Our platform uses the multiple sensors and logs that are continuously recorded in smartphones to create a model of the behavior of a user. The features and the algorithms that characterize this behavior, allow detection of anomalies in this behavior. We demonstrated a unique capability in providing early detection of mental health relapses, using this platform.
Mild Cognitive Impairment (MCI) is a neurological disorder, occurring mainly in the aging population, and that affects multiple tasks related to memory and cognition. Recent clinical studies demonstrated that Hyperbaric oxygen therapy (HBOT) could induce neuroplasticity that leads to the enhancement of cognitive functions and improve quality of life in patients suffering from chronic neuro-cognitive impairment. Here we propose to test the feasibility of using our passive sensing technology to track the kinetics of MCI treatment. We will detect the behavioral changes in MCI patients and in normal aging volunteers by comparing the digital markers of behavior counter a clinical cognitive assessment. We will also test changes in the severity of MCI that is expected to be induced by HBOT and by rehabilitative treatment.
Our vision is that passive sensing will become a clinical modality allowing sensitivity to deterioration or to the effect of treatment in MCI and in other neurological disorders.