International conference on signal processing proceedings. International Conference on Signal Processing最新文献

It has been reported that the pulse transit time (PTT), the interval between the peak of the R-wave in electrocardiogram (ECG) and the fingertip photoplethysmogram (PPG), is related to arterial stiffness, and can be used to estimate the systolic blood pressure (SBP) and diastolic blood pressure (DBP). This phenomenon has been used as the basis to design portable systems for continuously cuff-less blood pressure measurement, benefiting numerous people with heart conditions. However, the PTT-based blood pressure estimation may not be sufficiently accurate because the regulation of blood pressure within the human body is a complex, multivariate physiological process. Considering the negative feedback mechanism in the blood pressure control, we introduce the heart rate (HR) and the blood pressure estimate in the previous step to obtain the current estimate. We validate this method using a clinical database. Our results show that the PTT, HR and previous estimate reduce the estimated error significantly when compared to the conventional PTT estimation approach (p<0.05).

Position localization is essential for visually impaired individuals to live independently. Comparing with outdoor environment in which the global positioning system (GPS) can be utilized, indoor positioning is more difficult due to the absence of the GPS signal and complex or unfamiliar building structure. In this paper, a novel landmark-based assistive system is presented for indoor positioning. Our preliminary tests in several buildings indicate that this system can provide accurate indoor location information.

The electroencephalography (EEG) is a widely used diagnostic tool for a number of clinical applications, such as diagnosis of epilepsy and study of sleep. Traditionally, to acquire a single channel of EEG signal, at least three electrodes must be installed on the skin separated at certain distances. They must also be connected to an amplifier by electrode leads. These basic requirements are acceptable in most clinical laboratories, but are unacceptable in certain point-of-care applications, such as during patient transportation. In order to remove these requirements, we are designing a single-unit EEG sensor in the size of a U.S. penny. It contains multiple closely spaced dry electrodes that can hook onto the skin, an electronic circuitry for signal amplification, digitization and wireless transmission, and a battery providing power. In this paper, we answer two key questions regarding the feasibility of the single-unit design: 1) can the closely-spaced electrodes obtain EEG signal reliably? and 2) will the electrodes orientated in certain ways improve signal quality? We conducted experiments utilizing closely spaced electrodes to record the alpha wave in the EEG. Our results have shown positive answers to the two feasibility questions.

The rapid advance in three-dimensional (3D) confocal imaging technologies is rapidly increasing the availability of 3D cellular images. However, the lack of robust automated methods for the extraction of cell or organelle shapes from the images is hindering researchers ability to take full advantage of the increase in experimental output. The lack of appropriate methods is particularly significant when the density of the features of interest in high, such as in the developing eye of the fruit fly. Here, we present a novel and efficient nuclei segmentation algorithm based on the combination of graph cut and convex shape prior. The main characteristic of the algorithm is that it segments nuclei foreground using a graph cut algorithm and splits overlapping or touching cell nuclei by simple convex and concavity analysis, using a convex shape assumption for nuclei contour. We evaluate the performance of our method by applying it to a library of publicly-available two-dimensional (2D) images that were hand-labeled by experts. Our algorithm yields a substantial quantitative improvement over other methods for this benchmark. For example, our method achieves a decrease of 3.2 in the Hausdorff distance and an decrease of 1.8 per slice in the merged nuclei error.