||The electroencephalography (EEG) is a technique commonly used for detecting symptoms of neurological diseases such as epilepsy, sleep disorders, anxiety and learning disabilities that are quite diffused and with a great impact on people common life. Most of the mentioned mental disorders require long term EEG monitoring, possibly during daily life activities, to follow the course of the disease and sometimes to prevent further degradations of the patient condition. Generally, the longer the EEG measurement period isthe higher is the probability of a successful event detection. Allowing only few hours of observation time with high costs and resource overheads, traditional inpatient ambulatory EEG systems don’t satisfy these requirements. It is only recently that technology innovations have led to new outpatient EEG systems. They are mobile solutions that overcome some of these limitations reducing the overall patient monitoring costs and increasing the effectiveness of the measurements . Despite their benefits, such systems are still cumbersome with some problems related to the electrode-skin adherence, to the data storage capability and to the battery life time. Wearable EEG such as those presented in  and , are aimed to overcome these issues, allowing the recording of a longer temporal window that includes all stages of sleep and wakefulness and increasing the likelihood of recording typical symptoms. The wearable EEG system proposed in this paper is based on a custom PCB with off-the-shelf components. Being a wearable device, special efforts were made in reducing its power consumption and in device miniaturization. As a result, only the essential components were included in the project: an amplyfing/filtering block, an analog todigital converter, a micro-controller, a bluetooth transceiver and a power management module. The designed system, depicted in Fig. 1, contains a differential 8 channel recording unit. The EEG signals detected with a standard EEG cap are first amplified and then converted into a 24-bit digital signals by an ADS1299 from Texas Instrument. Once acquired, digital signals are transmitted to a remote backend by means of a Microchip Bluetooth RN-42 module. Moreover, a USB connection was introduced to charge the EEG recorder battery and as additional channel for data transfer. A custom firmware was written for a Microchip PIC18F46J50 to coordinate data exchange between ADCand Bluetooth or USB external controller. The main constraint was the real time data exchange at sampling frequency up to 2000SPS. In addition a power management unit generates all digital and analog voltage supplies from a 3.7V-950mAh LiPo battery. Even the battery charging circuit was implemented on the board. The EEG recorder was realized on the 5.5cm X 3.5cm double face board depicted in Fig.2. Possible remote controllers for wearable EEG recording applicationsare the nowadays widely diffused smartphone or tablet. So that an open source and user-friendly software application based, for example, on Android operative system, can be a target solution to interface our EEG recorder. At this first stage of the system development a Visual C++ application was written for the EEG recorder testing purpose. The small dimensions of the realized system and its maximum 270mW of power consumption make it suitable for up to 13 hours of continuous EEG recording without encumbering any daily life activity. As depicted in Fig. 3 and Fig. 4, some in-vivo measurements were performed comparing our device with a standard laboratory equipment.