The Infona portal uses cookies, i.e. strings of text saved by a browser on the user's device. The portal can access those files and use them to remember the user's data, such as their chosen settings (screen view, interface language, etc.), or their login data. By using the Infona portal the user accepts automatic saving and using this information for portal operation purposes. More information on the subject can be found in the Privacy Policy and Terms of Service. By closing this window the user confirms that they have read the information on cookie usage, and they accept the privacy policy and the way cookies are used by the portal. You can change the cookie settings in your browser.
The distribution and structure of leaves and branches influence the rainfall interception ratio (RIR) and water cycling processes in forests. However, measuring the three‐dimensional structure features of canopy organs to evaluate their effects on the RIR is labour‐intensive and time‐consuming. Modelling the spatial distribution of the RIR within a forest canopy after rainfall thus remains challenging...
Heart Rate Variability (HRV) is proven to be related to critical cardiovascular diseases. However, HRV is related to other factors as well, among which the activity is the major one. A novel activity-aware HRV analysis method is proposed to improve its performance on daily life ECG data. First, activity types and intensity are obtained by processing 3-axis acceleration signals. Then heart rate data...
With the availability of ubiquitous healthcare based on wireless sensor network, heart rate variability (HRV) analysis, as a valuable evaluation tool of cardiovascular mortality should be utilized more pervasively and accurately. We propose a ubiquitous HRV analysis system using people's daily life heart monitor data. The system consists of a sensor node recording electrocardiography (ECG) and acceleration...
Body sensor networks provide a platform for ubiquitous healthcare, driving the diagnosis in hospital static environment to the daily life dynamic context. We realized the importance of sensing of activities, which is not only a dimension of human health but also important context information for diagnosis based on the physiologic data. This paper presents our ubiquitous healthcare system, uCare. It...
Automatic detection of life threatening abnormal beats in electrocardiogram (ECG) signal is of importance in many healthcare applications. The ECG beat signal variations in both shape and time impose great challenges to automatic detection tasks. To address those challenges and for high accuracy automatic detection, we present here a two stage abnormal beats detection algorithm. Normal and abnormal...
This study focuses on physical activity classification method using a single triaxial accelerometer attached on chest. With acceleration data acquired by a wearable wireless device, features are extracted using sliding window to describe different activity types. Hidden Markov Model (HMM) is used to recognize physical activity sequence. A modified Viterbi algorithm is used to find the optimal state...
Set the date range to filter the displayed results. You can set a starting date, ending date or both. You can enter the dates manually or choose them from the calendar.