Serwis Infona wykorzystuje pliki cookies (ciasteczka). Są to wartości tekstowe, zapamiętywane przez przeglądarkę na urządzeniu użytkownika. Nasz serwis ma dostęp do tych wartości oraz wykorzystuje je do zapamiętania danych dotyczących użytkownika, takich jak np. ustawienia (typu widok ekranu, wybór języka interfejsu), zapamiętanie zalogowania. Korzystanie z serwisu Infona oznacza zgodę na zapis informacji i ich wykorzystanie dla celów korzytania z serwisu. Więcej informacji można znaleźć w Polityce prywatności oraz Regulaminie serwisu. Zamknięcie tego okienka potwierdza zapoznanie się z informacją o plikach cookies, akceptację polityki prywatności i regulaminu oraz sposobu wykorzystywania plików cookies w serwisie. Możesz zmienić ustawienia obsługi cookies w swojej przeglądarce.
In this paper, we will propose method to separate biosignals such as breath, blood, heart signal from mixed signals in body. As a result, we could get only target signal which is breath, blood and heart signals from actual mixture signals of carotid artery sound that extracted from a healthy human subject in a real environment using our algorithms and microphone sensors. Although this method is first...
Repeated exposures to psychological stress can lead to or worsen diseases of slow accumulation such as heart diseases and cancer. The main challenge in addressing the growing epidemic of stress is a lack of robust methods to measure a person's exposure to stress in the natural environment. Periodic self-reports collect only subjective aspects, often miss stress episodes, and impose significant burden...
Currently, as a effort to reduce a rate of death by cardiovascular diseases, a lot of researches have been studied regarding real-time diagnosis system. So, we implement a prototype which is contained of stream data processor and incremental data mining module for automatic diagnosis of cardiovascular diseases. In the prototype, (i)ECG signal data which is transported from body-attached sensor is...
The possibility to study graphic recording (PCG -Phonocardiography) of auscultator findings is a helpful diagnostic tool for the clinician and forms the basis of early detection of the heart problems. Due to its dispersed nature and overlapping with breathing sounds Heart Sound Signals (HSS) is difficult to detect and comprehend in conventional PCG. We present a Hardware system utilizing Frequency-Domain...
Myolectric control is nowadays the most used approach for electrically-powered upper limb prostheses. The myoelectric controllers use electromyographic (EMG) signals as inputs. These signals can be collected from the skin surface using surface EMG sensors, or intramuscular, using needle sensors. No matter which method is used, they have to be processed before being used as controller inputs. In this...
This paper concerns artifact removal from multichannel EEG data. It has already been demonstrated that independent component analysis (ICA) can be an effective and applicable method for EEG de-noising. The goal of this paper is to propose a framework, based on ICA and wavelet denoising (WD), to improve the pre-processing of EEG signals. In particular we employ the concept of spatially constrained...
Extra-corporal Circulation Support Systems (ECCS) are used in cardiac surgery on a daily basis. Surgeons and perfusionists supervise patients' vital signals such as heart rate or blood pressure and ensure secure and errorless operation of the ECCS. Latest developments clear the way to use an ECCS for emergency circulatory resuscitation in non-clinical environments, even when trained staff is sparse...
In this paper, we propose a system and methodology for using mobile phones for monitoring physical activities of a user, and its applications in assisting elderly or people with need for special care and monitoring. The method is based on processing acceleration data provided by accelerometers integrated in new mobile phones. As the mobile phone is carried regularly by the user, the acceleration pattern...
This paper presents the architecture, sensing and results of a context-aware smart home monitoring system based on pressure measurement sequences. It focuses on the analysis of transfers performed by the occupant in the bedroom and bathroom to assess if their behavior is within a normal range of motion. Pressure sensors are placed under the bed mattress and embedded in the grab bars of a toilet commode...
This work proposes a novel foetal electrocardiogram (FECG) extraction approach based on the cyclostationary properties of the signal of interest. The problem of FECG extraction can easily fit in a blind source separation (BSS) framework; taking into account specific statistical nature of the signal, that one wants to extract, leads to an algorithm able to estimate the FECG contribution to ECG recordings...
The fetal magnetoencephalogram (fMEG) is measured in the presence of large interference from maternal and fetal magnetocardiograms (mMCG and fMCG). These cardiac interferences can be attenuated by orthogonal projection (OP) technique of the corresponding spatial vectors. However, the OP technique redistributes the fMEG signal among the channels and also leaves some cardiac residuals (partially attenuated...
This study presents different methods for automatic sleep classification based on heart rate variability (HRV), respiration and movement signals recorded through bed sensors. Two methods for feature extraction have been implemented: time variant-autoregressive model (TVAM) and wavelet discrete transform (WDT); the obtained features are fed into two classifiers: Quadratic (QD) and Linear (LD) discriminant...
To evaluate the proficiency level of an operating myoelectric hand, we proposed an evaluation index consisting of the accuracy and the reproducibility of electromyography (EMG) signal patterns. Our proposed method is not an absolute evaluation because we use bio-signals, so it is necessary to verify the correlation between the proposed index and performance evaluation to confirm the usefulness of...
We present an approach to wearable sensor-based assessment of motor function in individuals post stroke. We make use of one on-body inertial measurement unit (IMU) to automate the functional ability (FA) scoring of the Wolf Motor Function Test (WMFT). WMFT is an assessment instrument used to determine the functional motor capabilities of individuals post stroke. It is comprised of 17 tasks, 15 of...
A real-time method using only accelerometer data is developed for classifying basic human static postures, namely sitting, standing, and lying, as well as dynamic transitions between them. The algorithm uses discrete wavelet transform (DWT) in combination with a fuzzy logic inference system (FIS). Data from a single three-axis accelerometer integrated into a wearable headband is transmitted wirelessly,...
Several efforts have been carried out to enhance dexterous hand prosthesis control by impaired individuals. Choosing which voluntary signal to use for control purposes is a critical element to achieve this goal. This review presents and discusses the recent results achieved by using electromyographic signals, recorded either with surface (sEMG) or intramuscular (iEMG) electrodes, and electroneurographic...
A Mechanomyography (MMG) based hand-motion patterns recognition approach was proposed in this paper. With the MMG signal acquired in the upper arm via a single sensor, eleven original features were extracted, and they were further processed by principal components analysis (PCA) in order to reduce the dimension of the feature space. Quadratic discriminant analysis (QDA) was used for four hand-motion...
This paper presents a myoelectric knee joint angle estimation algorithm for control of active transfemoral prostheses, based on feature extraction and pattern classification. The feature extraction stage uses a combination of time domain and frequency domain methods (entropy of myoelectric signals and cepstral coefficients, respectively). Additionally, the methods are fused with data from proprioceptive...
This paper describes the classification of walking patterns on ascending and descending slopes based on features extracted from data recorded using a single waist-mounted tri-axial accelerometer. A 19-dimensional set of salient features representing the hill walking patterns were obtained based on gait cycle analysis related to the acceleration data in the anterior-posterior (AP), medio-lateral (ML),...
In this paper, a method for extracting and classifying movement-related brain signals is proposed. A single-trial MEG observation is first processed with a pre-whitening filter so that strong stationary interference is eliminated. Next, a brain signal effective for classification is extracted using an adaptive spatial filter. The extracted signal is then classified with a support vector machine. From...
Podaj zakres dat dla filtrowania wyświetlonych wyników. Możesz podać datę początkową, końcową lub obie daty. Daty możesz wpisać ręcznie lub wybrać za pomocą kalendarza.