Method for Monitoring Rapid Eye Movement in Hospital Patients

Abstract

Rapid Eye Movement (REM) sleep is linked with improvements in brain development and physical health. Previous works in the field of monitoring REM sleep have utilized electrical response from brain activity in order to categorize sleep stages (N1, N2, N3, & REM) with the ‘gold standard’ polysomnography (PSG) tests. PSG utilizes extensive equipment, has large costs, and can be uncomfortable for patients to achieve relaxed sleep. Additionally, consumer products such as FitBit categorize sleep based on correlated vitals and are not approved for use in a clinical setting. As such, there is a need for an improved REM monitoring system that can detect the amplitude and velocity of eyeball movement and the duration of REM sleep that is easy to use and accurate. A FA22 MECHENG450 team prototyped an eye mask with optical sensors to achieve this, and was verified with a phantom-eye model. However, before the prototype can be validated in an Institutional Review Board (IRB) approved sleep study, the prototype needs to become self contained within the mask (cordless), and be capable of 8 hours of data storage for gyroscope and optical readings. This semester, the prototype was updated with the design of a custom printed circuit board (PCB), and selection of two new components: a rechargeable battery, and a microcontroller with smaller dimensions. With the finished assembly, the sleep mask will be usable to correlate optical sensor data to other sleep health metrics to determine the behavior of eye movement within a sleep cycle.