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Cuff-less blood pressure (BP) estimation using pulse transit time (PTT) is a promising method for long-term BP monitoring. However, state-of-art PTT models are unable to trace the change of pressure baseline in subjects, which limits their application in long-term BP tracking. This study investigated the relationship between the change of pressure baseline and pulse waveform in long-term BP monitoring...
In this paper we develop a fault detection and isolation method based on data-driven approach. Data-driven methods are effective for feature extraction and feature analysis using statistical techniques. In the proposal, the Cumulated Sum (CUSUM) efficiency is explored for incipient fault detection. The fault is assumed to be a Gain variation, an Offset evolution, a Phase shifting or one of the multiple...
Fine-grained runtime power management techniques could be promising solutions for power reduction. Therefore, it is essential to establish accurate power monitoring schemes to obtain dynamic power variation in a short period (i.e., tens or hundreds of clock cycles). In this paper, we leverage a decision-tree-based power modeling approach to establish finegrained hardware power monitoring on FPGA platforms...
The paper presents the application of sparse representation in feature extraction for the cuffless estimation of Blood Pressure (BP). The sparse coding dictionary learned from the signal of our interest can easily represent the signal in terms of sparse coefficients. Considering the similarity in the pulse shape of Photoplethysmogram (PPG) and Arterial Blood Pressure (ABP), the sparse coefficients...
In this paper, we propose a new characteristic measure relative people density and motion dynamics for the purpose of long-term crowd monitoring. While many related works focus on direct people counting and absolute density estimation, we will show that relative densities provide reliable information on crowd behaviour. Furthermore, we will discuss the derivation of a so-called Congestion Level of...
In this paper, we present TR-BREATH, a time-reversal (TR) based, contact-free, accurate breathing monitoring system capable of multi-person breathing rate estimation within a short period of time (e.g., around one minute) using off-the-shelf WiFi devices. TR-BREATH exploits the fine-grained channel state information (CSI) on WiFi devices to capture the minor variations caused by breathing. To amplify...
Texture feature is an important feature descriptor for many image analysis applications. The objectives of this research are to determine distinctive texture features for crowd density estimation and counting. In this paper, we have comprehensively reviewed different texture features and their different possible combinations to evaluate their performance on pedestrian crowds. A two-stage classification...
Cuff-less estimation of systolic (SBP) and diastolic (DBP) blood pressure is an efficient approach for non-invasive and continuous monitoring of an individual's vitals. Although pulse transit time (PTT) based approaches have been successful in estimating the systolic and diastolic blood pressures to a reasonable degree of accuracy, there is still scope for improvement in terms of accuracies. Moreover,...
In recent years, the Unmanned Aerial Vehicles (UAVs) technologies are widely employed in many fields such as disaster monitoring, map revision, and aerial imagery. A UAV aerial remote sensing system has several advantages such as low cost, high spatial resolution, and flexibility. However, one single UAV image can only cover a small area due to the limited altitude of the vehicle and the restricted...
We experience changes in stationarity/time variance in many practical applications. Since changes modify the operational framework the application is working with, its accuracy performance is in turn affected. When changes can occur, we need to detect them as soon as possible, in general by inspecting features extracted from data, and afterwards intervene to mitigate their effects. In this paper,...
Gaze movements play a crucial role in humancomputer interaction (HCI) applications. Recently, gaze tracking systems with a wide variety of applications have attracted much interest by the industry as well as the scientific community. The state-of-the-art gaze trackers are mostly non-intrusive and report high estimation accuracies. However, they require complex setups such as camera and geometric calibration...
In this demo, we present a network failure detection system that is constructed by extracting tweets related to network failures and estimating the failure area. The demo is based on the work “Early Network Failure Detection System by Analyzing Twitter Data” [1].
Air pollution has become one of the most pressing environmental issues in many countries, including China. Finegrained PM2:5 particulate data can prevent people from long time exposure and advance scientific research. However, existing monitoring systems with PM2:5 stationary sensors are expensive, which can only provide pollution data at sparse locations. In this paper we demonstrate for the first...
Performance analysis of instructors in the lecture room plays a significant role in maintaining the higher education quality and standards. This paper presents a novel approach for the evaluation of instructor's performance and behavior in the lecture room. Proposed approach employs the lecture video using face recognition and pose estimation of instructor. Instructor time-in and time-out monitoring;...
Eye gaze movements are considered as a salient modality for human computer interaction applications. Recently, cross-ratio (CR) based eye tracking methods have attracted increasing interest because they provide remote gaze estimation using a single uncalibrated camera. However, due to the simplification assumptions in CR-based methods, their performance is lower than the model-based approaches [8]...
A non-contact vision-based system is presented for continuous respiratory rate monitoring. The system identifies feature points in a video feed and tracks them over time. Two methods are presented for comparison — a method which uses principal component analysis (PCA) and a simple averaging approach. These methods condense the feature point trajectories into a compact set of representative signals...
This paper proposed a method to monitor systolic blood pressure (BP) variability without using a cuff during the daytime. In this method, BP variability of long-term and short-term were separated and estimated respectively from features of phoplethysmograph (PPG) through the use of a frequency filter. Then, total variability was obtained from the combination of long-term and short-term. BP by using...
In the Prognostics and Health Management domain, estimating the remaining useful life (RUL) of critical machinery is a challenging task. Various research topics as data acquisition and processing, fusion, diagnostics, prognostivs and decision are involved in this domain. This paper presents an approach for estimating the Remaining Useful Life (RUL) of equipments based on shapelet extraction and characterization...
Wearable monitoring systems have gained tremendous popularity in the health-care industry, opening new possibilities in diagnostic routines and medical treatments. Numerous hardware systems have been presented since, which allow for continuous acquisition of various biosignals like the ECG, PPG, EMG or EEG and which are suited for ambulatory settings. Unfortunately, these flexible systems are liable...
Automatic detection of the event of switching-on an electric load, estimation of that switch-on instant and subsequent automatic identification of that electric load using current transient signal around the switch-on instant are studied in this paper. The time variation of the current harmonics is used to first detect the event of switching-on an electric load and then spectral features extracted...
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