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A Body Area Network through Wireless Technology

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A physiological signal monitoring system and alerting system using wireless technology is presented. The two types of physiological signal monitoring are captured from the body through leads and using the radio-frequency transmitting and receiving module the data are interfaced to computer systems. Furthering using a developed user interface module the captured signals are analyzed for checking abnormality. Any significant recordings are transmitted to the physicians hand phone by using external serial SMS modem. ECG signal de-noising is conducted by using low-pass and high-pass filters. EEG signals de-noising is conducted by using band-pass filters set. A comparative evaluation of the module with the manual recording shows encouraging results. The ECG and EEG pattern are presented in this paper.
Keywords:bio signals, advanced signal processing.
Wearable health monitoring systems integrated into a telemedicine system are novel information technology that will be able to support early detection of abnormal conditions and prevention of its serious consequences [1,2]. A continuous monitoring diagnostic procedure of a chronic condition or during supervised recovery from an acute event or surgical procedure is needed these days. Wireless Body Area Network, (WBAN) consists of a set of mobile and compact intercommunicating sensors, either wearable or implanted into the human body, which monitor vital body parameters and movements [3-5]. This paper aims to present the design and implement of a portable device that can capture ECG (Electrocardiogram) and EEG (Electroencephalography) signals from the human body and send those signals into Personal Computer (PC) for continuous monitoring and analysis. In the event of any abnormal changes of in the captured signal, the PC sends a message to doctor’s hand phone. ECG and EEG signals are captured from the electrodes and it is send to the portable device that fixed on body. Here these signals will be amplified before sending it to RF transmitting device. Transmitted signal is collected from the receiving module and the signals through a low pass filter before recording in the database for analyzing.
Inside the developed program of the software ECG signals are de-noised using low-pas filter (FIR) and low-pass filter (FIR). Using de-noised ECG signals, heart beat and amplitude of the R intervals are analyzed. EEG signal are de-noised by using band pass-filters (FIR). EEG signals are then categorized according to the frequency ranges. This system was mainly designed to analyze alpha-wave (α-wave). Leads and the potentials recorded at the various point in the test object is as shown in Fig.1 The physiological signals are of low amplitude signals; therefore it is very important to amplify these signals before being transmitted. Instrumentation amplifier can be used to amplify these mV range physiological signals. Fig.2 shows the block diagram representation of the set-up.
Electrocardiogram Testing:
Lead one signal was captured by placing electrodes in left hand, right hand and left leg signal was connected to the common ground. Figure 3(a). shows the signal that was collected by placing the left leg signal in common ground and Figure 3(b) represents the signal that was captured without placing left leg signal to the common ground. Lead two signals were captured by placing electrodes on the right arm and left leg and left arm was connected to the common ground. Figure 3(c). shows signals that were captured with common ground and Figure 3(d) shows signals that were captured without common ground. Lead three signals were captured by placing electrodes on the left leg, left arm and the right arm was connected to the common ground. Figure 3(e). shows signals that were captured with common ground and Figure 3(f) shows signals that were captured without common ground.


  1. Istepanian, RSH; Jovanov, E; Zhang, YT. Guest Editorial Introduction to the Special Section on M-Health: Beyond Seamless Mobility and Global Wireless Health-Care Connectivity. IEEE Transactions on Information Technology in Biomedicine. 2004;8:405–414. [PubMed]
  2. Wearable Technology. Special Issue of the IEEE Engineering in Medicine and Biology Magazine. 2003;22
  3. Emil Jovanov, Aleksandar Milenkovic, Chris Otto,Piet C de Groen ―A wireless body area network of intelligent motion sensors for computer assisted physical rehabilitation‖ J Neuroengineering Rehabil. 2005; 2: 6.
  4. Otis, BP; Rabaey, JM. A 300-μW 1.9-GHz CMOS Oscillator Utilizing Micromachined Resonators. IEEE Journal of Solid-State Circuits. 2003;38:1271–1274.
  5. Ghovanloo, M; Najafi, K. A BiCMOS Wireless Stimulator Chip for Micromachined Stimulating Microprobes. Proceedings of the Second Joint EMBS/BMES Conference. 2002. pp. 2113–2114.