Online we are all able bodied : Online psychological sense of community and social support found through membership of disability-specific websites promotes well-being for people living with a physical disability

People with a physical disability are a population who for a number of reasons may be vulnerable to social isolation. Research into Internet-based support sites has found that social support and an online sense of community can be developed through computer mediated communication channels. This study aims to gain an understanding of the benefits that membership of disability-specific online communities may have for people with a physical disability. An online survey was administered to a sample of users of such sites (N = 160). Results indicated that users did receive moral support and personal advice through participating in such online communities. Further, results indicated that online social support and feeling a sense of community online were positively associated with participants' well-being in the areas of personal relations and personal growth.

Cardiac health diagnosis using higher order spectra and support vector machine

The Electrocardiogram (ECG) is an important bio-signal representing the sum total of millions of cardiac cell depolarization potentials. It contains important insight into the state of health and nature of the disease afflicting the heart. Heart rate variability (HRV) refers to the regulation of the sinoatrial node, the natural pacemaker of the heart by the sympathetic and parasympathetic branches of the autonomic nervous system. The HRV signal can be used as a base signal to observe the heart's functioning. These signals are non-linear and non-stationary in nature. So, higher order spectral (HOS) analysis, which is more suitable for non-linear systems and is robust to noise, was used. An automated intelligent system for the identification of cardiac health is very useful in healthcare technology. In this work, we have extracted seven features from the heart rate signals using HOS and fed them to a support vector machine (SVM) for classification. Our performance evaluation protocol uses 330 subjects consisting of five different kinds of cardiac disease conditions. We demonstrate a sensitivity of 90% for the classifier with a specificity of 87.93%. Our system is ready to run on larger data sets.

Available evidence does not support routine administration of antipyretics to reduce duration of fever or illness

Commentary on : Carey JV. Literature review : should antipyretic therapies routinely be administered to patients with [corrected] fever? J Clin Nurs 2010;19:2377–93.