Home based Telehealth is a combination of communications, imaging, sensing and human computer interaction technologies targeted at diagnosis, treatment and monitoring patients without disturbing the quality of lifestyle. This paper proposes development of a low cost medical sensing, communication and analytics device that is real-time monitoring internet enabled patients physiological conditions. Internet of Things (IoT) network will provide active and real-time engagement of patient, hospitals, caretaker and doctors. Massaging and synchronising the system has been the based focus in this paper, where it applies the suggested algorithm to predict the minimum time period that separates two consecutive bursts of messages and measures the minimum queue sizes for the health care personals nods, to manage the traffic and avoid the dropping of messages. NS2 simulator was employed to simulate the Telehealth environment algorithm

No abstract

The University of Gloucestershire accepts no liability for any infringement of intellectual property rights in any material deposited but will remove such material from public view pending investigation in the event of an allegation of any such infringement.

In the last decade, Daubechies’ wavelets have been successfully used in many signal processing paradigms. The construction of these wavelets via two channel perfect reconstruction filter bank requires the identification of necessary conditions that the coefficients of the filters and the roots of binomial polynomials associated with them should exhibit. In this paper, orthogonal and Biorthogonal Daubechies families of wavelets are considered and their filters are derived. In particular, the Biorthogonal wavelets <i>Bior</i>3.5, <i>Bior</i>3.9 and <i>Bior</i>6.8 are examined and the zeros distribution of their polynomials associated filters are located. We also examine the locations of these zeros of the filters associated with the two orthogonal wavelets <i>db</i>6 and <i>db</i>8

No abstract