IOT BASED CORTIC PAD FOR SLEEP ANALYSIS.

摘要

Many existing Brain Computer Interface (BCI) wearables possess the functionality of detecting or classifying sleep stages so that the user can analyze his or her sleep patterns for optimizing their individual productivity. In some cases these BCI wearables also claim to wake the user whilst he/she is in the most appropriate sleep stage for waking up. The proposed invention is an Internet of Things (IoT) enabled wearable BCI design. The device has an analog front-end which does the job of pre-amplification and filtering of the acquired Electroencephalogram signal. This front-end also has a Sigma-Delta ADC and a micro-controller to collectively act as a data acquisition bridge. After acquisition of this data the remaining noisy frequency components are removed using digital filters, following which this noise-free signal is subjected to analysis for extracting important frequency component features. This digital domain filtering and analysis can be done using any computational software, DSP or FPGA. There are two types of communication bridges (Bluetooth Low Energy and Wifi), for the above signal processing platforms, that are used to send this data to the android platform. An attempt to perform -the same signal processing tasks on the android application itself is also available, thus making, such a comparative study of different platforms for processing EEG data, one of the objectives of the system. The main feature of the invention is the adaptive waking algorithm which can wake-up the user at the right moment of his/her sleep stages.