IEEE Journal of Emerging and Selected Topics in Circuits and Systems (JETCAS)
MASSOUD PEDRAM, Editor-in-Chief (EiC)
MANUEL DELGADO-RESTITUTO, Deputy EiC
Volume 1, Issue 4
Special Issue on Brain-Machine Interface
BMI/BCI topics cover many disciplines related to several IEEE societies. The resulting devices and algorithms translate physiological activity into machine control, which can be used to restore or enhance, either partially or completely, human perception or sensory-motor function. The multidisciplinary nature of BMI/BCI has made it one of the most dynamic and interesting topics in the IEEE society. The implementation of a complete BMI/BCI offers many circuits and systems design challenges, which include neural and chemical sensors, signal processing activities, low-power and low-voltage circuits, wireless transmission, harvesting energy, material sciences, and biocompatibility issues. The research community is now especially focused on the implementation of wireless sensors and biosignal processing.
The selected papers reflect continuing trends toward higher levels of circuits and systems techniques covering a wide variety of subjects within the analog and RF integrated circuits and signal processing fields, ranging from basic analog building blocks to system applications in several related domains such as telecommunications and biomedical technology.
Sawan, M. Mohseni, P. Sajda, P. Sanchez, J. C., Guest Editorial
Chang, D.-W. Liang, S.-F. Young, C.-P. Shaw, F.-Z. Su, A. W. Y. Liu, Y.-D. Wang, Y.-L. Liu, Y.-C. Chen, J.-J. Chen, C.-Y., A Versatile Wireless Portable Monitoring System for Brain-Behavior Approaches
It is critical to set up a precise and feasible monitoring system for a variety of animal and human studies. A multichannel wireless system for monitoring physiological signals of freely moving rats is presented. This system combines electroencephalogram (EEG) and acceleration signals, enabling the study of association between brain and behavior. A combination of EEG and accelerometers eliminates the necessity for complicated video installation as well as time-consuming and tedious analysis of recorded videos. The IEEE 802.15.4 based wireless communication frees the experimental subject from the hassle of wires and reduces wire artifacts during recording. Long-period continuous recording was possible because of the low power feature of the system. Methods for automatic wake-sleep state discrimination and temporal lobe epileptic seizure detection are also proposed to demonstrate the advantages of the system. An accuracy of up to 96.22% for the automatic discrimination of wake-sleep states is an advantage of our system. In addition, the detection of amygdala-kindling temporal lobe seizures reaches 100% with zero false alarms, greatly saving manpower in the identification of temporal lobe epilepsy.