We will develop and test a system for long-term monitoring of motion during REM sleep. This system will incorporate consumer-grade sensors such as inexpensive mobile phones and single channel EEG monitors. The goal is to provide real-time logging of both EEG (to partition sleep state) and accelerometer-derived motion signals (to identify abnormal motor activity during REM sleep).
People who develop Parkinson's Disease later in life sometimes have sleep disorders when they are younger. In particular, they sometimes move around when they are sleeping - especially when they are in the dreaming or 'REM' stage of sleep. Identifying young people with these 'REM Sleep Disorders' might help us diagnose their Parkinson's Disease earlier and provide better treatment. We are planning to develop a system for measuring how much people move around during REM sleep. To do this we will use off-the-shelf electronic devices like mobile phones to measure both brain activity and motion throughout the night. The goal is to make this type of monitoring fast, effective and inexpensive.
The project successfully developed a code base that did what we planned - linked together Android devices and bluetooth sensors to measure both motion and EEG at the same time.
|Effective start/end date
|8/08/16 → 31/03/17