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The respiratory rate is a vital sign that can provide important information about the health of a patient, especially that of the respiratory system. The aim of this study is to develop a simple method that can be applied in wearable systems to monitor the respiratory rate automatically and continuously over extended periods of time. In this paper, a novel respiratory rate estimation method is presented...
Clinical assessment scales to evaluate motor abilities in stroke survivors could be used to individualize rehabilitation interventions thus maximizing motor gains. Unfortunately, these scales are not widely utilized in clinical practice because their administration is excessively time-consuming. Wearable sensors could be relied upon to address this issue. Sensor data could be unobtrusively gathered...
In order to denote the abnormalities of the patients, we propose a novel approach to detect anomaly in biomedical monitoring using density ratio values as the Patient Status Index (PSI). The key idea of the proposed method is to define the ratio of training and testing data densities, where training dataset only consist of normal data and testing dataset consist of both normal and abnormal data, and...
Seismocardiography is the body-surface recording of vibrations produced by the beating heart. A high frequency (HF) accelerometric component of the seismocardiogram (SCG) is related to the heart sounds generated by the closure of atrio-ventricular and semilunar valves. This paper evaluates the feasibility of recording the SCG component associated to cardiac sounds by means of a wearable device originally...
The CHRONIOUS system has been developed based on an open architecture design that consists of a set of subsystems which interact in order to provide all the needed services to the chronic disease patients. An advanced multi-parametric expert system is being implemented that fuses information effectively from various sources using intelligent techniques. Data are collected by sensors of a body network...
Early mental stress detection can prevent many stress related health problems. This study aimed at using a wearable sensor system to measure physiological signals and detect mental stress. Three different stress conditions were presented to a healthy subject group. During the procedure, ECG, respiration, skin conductance, and EMG of the trapezius muscles were recorded. In total, 19 physiological features...
This work presents an investigation of the potential benefits of customizing the analysis of long-term ECG signals, collected from individuals using wearable sensors, by incorporating small amount of data from these individuals in the training set of our classifiers. The global training dataset selected was from the MIT-BIH Arrhythmias Database. This proposal is validated on long-term ECG recordings...
A primary difficulty in physiological monitoring is detecting changes of health status for patients. In order to address this difficulty, we propose a new framework in patient-specific physiological monitoring by defining a density ratio using the training density and testing density to denote the changes of patient status, such as health, sub-health and abnormalities. We use a Least Square-based...
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