The recording of high-frequency oscillations (HFO) through the skull has been investigated in the last years highlighting interesting new correlations between the EEG signals and common mental diseases. Therefore, since most of the commercially available EEG acquisition systems are focused on the low frequency signals, a wide-band EEG recorder is here presented. The proposed system is designed for those applications in which a wearable and user-friendly device is required. Using a standard Bluetooth (BT) module to transfers the acquired signals to a remote back-end, it can be easily interfaced with the nowadays widely spread smartphones or tablets by means of a mobile-based application. A Component Off-The-Shelf (COTS) device was designed on a 19 cm2 custom PCB with a low-power 8-channel acquisition module and a 24−bit Analog to Digital Converter (ADC). The presented system, validated through in-vivo experiments, allows EEG signals recording at different sample rates, with a maximum bandwidth of 524 Hz, and exhibits a maximum power consumption of 270 mW.
A wearable device for high-frequency EEG signal recording
Enzo Mastinu;
2015-01-01
Abstract
The recording of high-frequency oscillations (HFO) through the skull has been investigated in the last years highlighting interesting new correlations between the EEG signals and common mental diseases. Therefore, since most of the commercially available EEG acquisition systems are focused on the low frequency signals, a wide-band EEG recorder is here presented. The proposed system is designed for those applications in which a wearable and user-friendly device is required. Using a standard Bluetooth (BT) module to transfers the acquired signals to a remote back-end, it can be easily interfaced with the nowadays widely spread smartphones or tablets by means of a mobile-based application. A Component Off-The-Shelf (COTS) device was designed on a 19 cm2 custom PCB with a low-power 8-channel acquisition module and a 24−bit Analog to Digital Converter (ADC). The presented system, validated through in-vivo experiments, allows EEG signals recording at different sample rates, with a maximum bandwidth of 524 Hz, and exhibits a maximum power consumption of 270 mW.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
