The results suggest that the proposed wearable actigraphy system is practical for the in-home screening of objective sleep measurements and objective evaluation of sleep improvement after treatment.

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.

Conventional image interpolation methods such as the bilinear and bicubic algorithms determine the weights of the reference pixels based on the special distance between the supplementary pixel and the reference pixels. They suffer from some problems such as blurring and jagging around the edges since the edge structure is not considered in interpolation. In this paper, a coordinate rotation and kernel stretch strategy combined with the bilinear or bicubic algorithm is proposed to tackle these problems. For the edge regions, the spatial coordinate axes are rotated to the edge direction and the edge normal to calculate the distances between the supplementary pixel and the original reference pixels. The kernel function is also stretched along the estimated edge direction so that the weights of the reference pixels along the edge direction would be higher than the others to smooth the edge and prevent the jagging artifacts. An edge enhancement method is also proposed to further reduce the interpolation error and sharpen the edge. The experiment results demonstrate that conventional bilinear and bicubic image interpolation methods combined with the proposed strategy can greatly improve the quantitative and qualitative performance for image enlargement.

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