This paper presents the design of a novel wireless sensor network structure to monitor patients with chronic diseases in their own homes through a remote monitoring system of physiological signals. Currently, most of the monitoring systems send patients' data to a hospital with the aid of personal computers (PC) located in the patients' home. Here, we present a new design which eliminates the need for a PC. The proposed remote monitoring system is a wireless sensor network with the nodes of the network installed in the patients' homes. These nodes are then connected to a central node located at a hospital through an Internet connection. The nodes of the proposed wireless sensor network are created by using a combination of ECG sensors, MSP430 microcontrollers, a CC2500 low-power wireless radio, and a network protocol called the SimpliciTI protocol. ECG signals are first sampled by a small portable device which each patient carries. The captured signals are then wirelessly transmitted to an access point located within the patients' home. This connectivity is based on wireless data transmission at 2.4-GHz frequency. The access point is also a small box attached to the Internet through a home asynchronous digital subscriber line router. Afterwards, the data are sent to the hospital via the Internet in real time for analysis and/or storage. The benefits of this remote monitoring are wide ranging: the patients can continue their normal lives, they do not need a PC all of the time, their risk of infection is reduced, costs significantly decrease for the hospital, and clinicians can check data in a short time.
This paper describes the use of a digital to analog converter (DAC) based circuit structure for generating modulated Gaussian pulses for low (3.1 to 5 GHz) and high (6 to 10.6 GHz) UWB bands. The voltage references in DAC circuit are obtained by piecewise constant approximation of the pulses. Experimental results with HSPICE using a 0.18µm CMOS technology with 1.8V power supply are given for modulated Gaussian pulses with 4 and 8GHz center frequencies, which resemble 4 th and 6 th order derivative of the Gaussian pulse.The power consumptions are, respectively, 0.82mW and 1.26mW for the main circuit in low and high UWB bands. Since the circuit structure is simple, both the power consumption and the area are relatively much lower than the existing pulse generators. Also, generating sub-nanosecond signals for high UWB band is due to simplicity of the circuit, which otherwise would require a CMOS technology with finer feature size.
In this study, the authors focus on utilising receiver-based MAC protocol (RB-MAC) and adaptive RB-MAC in routing protocol for low power and lossy wireless sensor networks routing protocol in low-power and lossy wireless channel. This results in a cross-layer approach in which routing decisions can be made based on MAC-layer functionalities. The authors study the effects of multiple receiver nodes, size of preamble and variable duty-cycle in number of retransmissions. Retransmissions increase energy consumptions and delay. Analytical and numerical results confirm that the RB-MAC and adaptive RB-MAC outperform the existing state-of-the art sender-based MAC protocols in terms of end-to-end energy-efficiency, reliability and delay. Simulation result demonstrates that using receiver-based MAC protocols in RPL-based lossy channel imply less retransmissions than sender-based MAC.
In preamble-sampling medium access control (PS-MAC) protocols, nodes spend most of their time in sleep mode, and wake up for a short duration every checking interval (CI) to check the channel for an ongoing transmission. To avoid deafness, each data packet is preceded by a preamble with the same length as CI, to make sure that all potential receivers detect the preamble. In this work, the authors extend the idea of receiver-based medium access control (MAC) protocol in which all potential neighbour nodes obtain the data frame. They propose and evaluate adaptive preamble MAC and adaptive sampling MAC in PS-MAC with multiple receiver nodes. The analytical and numerical results demonstrate how proposed adaptive PS-MAC outperforms the state-of-the-art sender-based and receiver-based PS-MAC protocols in terms of energy, while maintaining the comparable reliability in data delivery. In addition, overall lifetime of the involved sensor nodes has increased significantly.
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