Home Phoneline Research Articles

Video Over Intranet (VDOIT)

Video calling or voice calling through the use of the internet is a very common thing in today's world. Nevertheless, users have to pay charges directly or indirectly, tolerating all the delays even if you use the facility within the same network or sub-network. Over 30 million US households used Voice over IP (VoIP) until the end of 2010. Specialist found that 31.4% of the household used VoIP as the main and only home phone line by 2012. Users up till now have multiplied by a huge factor. There are several drawbacks of using video calling over the internet within a small network such as delay of packets (travel to the main server outside network and reenter the same network again), direct or indirect costs, users need to be always connected online and efficiency and speed of the user's system vary according to connection quality and bandwidth. In this project, we implemented a WebRTC enabled web application which provides free peer to peer video calling and conferencing tool for any private organization on top of their existing private network.

Abstract 221: The Impact of Using Mobile-enabled Devices on Patient Engagement in a Blood Pressure Remote Monitoring Program

Objectives: Home monitoring of blood pressure has been shown to improve care as opposed to only the traditional office BP monitoring. The blood pressure connect program is a remote blood pressure monitoring program on a secured web-based platform where patients upload their blood pressure readings which are automatically shared with their providers, thereby facilitating timely feedback and intervention, like medications changes. Different data transfer technologies enable the uploading of the blood pressure readings from the blood pressure meters to the secure website: modem connection through a home phone line (iMetrikus) and more recently, wireless blood pressure devices (MedApps). Patients exhibit different engagement patterns with these linking technologies. This study aimed to compare how patients in the program engage using the 2 types of linking technologies, and its potential impact program design and outcomes. Methods: Thirty patients, aged 23-84 years (62 ± 14years), currently enrolled in the blood pressure connect program, who had completed at least 2 months in the program and not participating in any other clinical trial were included in the analysis. Half of these patients used MedApps while the other half used iMetrikus. The patients were matched by practice and age. Indices used to assess how device type affects engagement include number of days to first BP reading (measurement) and upload, total number of measurements and uploads/day. These indices were compared in both groups using the Wilcoxon-Mann-Whitney two-sample rank-sum test. Results: Measurements/day and uploads/day were significantly higher in the MedApps group vs. iMetrikus group (Median = 0.66 vs. 0.2 measurements/day; p-value= 0.0136 and 0.46 vs. 0.01 uploads/day; p-value = 0.0001 respectively). Number of days to first upload was significantly lower in the MedApps group (median = 4 vs.7days; p-value= 0.017). Number of days to first measurement did not differ between the groups (median= 2 vs. 1day p-value=0.9827). Conclusions: Wireless transmission made possible by the MedApps devices ensures that readings taken are transmitted to the web instantaneously, as seen from the significantly lower time to first upload. As a program design measure, this is extremely critical, as it provides clinicians timely data to intervene on. We hypothesize that the increased feedback resulting from this instantaneous upload leads to better engagement in the program, as demonstrated by the significantly higher number of measurements in the MedApps group. There is now overwhelming evidence that more frequent testing results in better clinical outcomes. The study is extremely significant in demonstrating the impact of mobile enabled wireless technologies on patient engagement and outcomes in remote patient monitoring programs.

Channel modeling and system performance for HomePNA 2.0

The new Home Phoneline Networking Alliance (HomePNA) 2.0 system is an attractive proposition for home networking since it potentially allows transmission rates comparable to those of Ethernet, using the existing installed telephone wiring. However, although the transmission standard is designed to be variable rate (variable symbol rate and bits/symbol), not all combinations are mandatory and it is, therefore, instructive to determine the level of receiver complexity required to handle the optional higher rates. An accurate channel model is devised, characterizing the home phone line network around 7 MHz, which allows the performance of the HomePNA 2.0 physical layer to be evaluated. The very good agreement obtained between the measured and modeled channel responses, in both time and frequency domains, enables a high degree of confidence in the simulation results. Due to the considerable dispersion observed in some home phone line channels, a number of equalizer structures are proposed to improve performance in the receiver. These are compared for each of the two possible symbol rates. Computer simulations show that the performance of the system can be greatly improved at the lower rate with a low complexity equalizer, but at the higher rate, which is not mandatory, a much more complex equalizer is required.

Connecting the home with a phone line network chip set

In addition to shared Internet access for PCs, the home network will connect to every consumer electronic device. To make this possible, we must consider robust system requirements, home phone line standards, costs, and implementation of a supporting iline10 chip set.

Wide band home phone line characterization

This paper presents data characterizing the household phone line in the 1-60 MHz band. Two types of measurements were performed: transmission and noise sampling. The transmission measurements were done by using the impulse channel sounding method, so both the line attenuation and the delay spread were obtained. The noise measurements include: phone line background noise, phone noise, and noise sampled over a 24 hour period. Statistical characteristics of the delay spread, frequency response and noise can be extracted from the data and used in the design of phone line based communications systems.