Research Paper | Computer Science & Engineering | India | Volume 3 Issue 9, September 2014
Energy Efficient QRS Detection Method for Portable and Personal Analysis of ECG Signal Obtained from Wearable Wireless ECG Body Sensors
Abstract: In this research, a novel heart beat signal propagation and heart rate computation model is developed for the patients using body wearable sensors for heart rate monitoring (also known as Holter) connected through Bluetooth Environment with the medical database through smart phone. These environments are usually designed to post-treatment or pre-treatment monitoring of the heart patients on the regular basis to avoid the critical health hazard situations, while they are at work, home, etc (out of the medical facility or controlled environment). In this research project, the aim is to improve the ECG QRS detection process by making the whole process energy efficient to maximize the smart phone battery life. In this research, a novel heart beat signal propagation from holter to smart phone and then towards the medical database. The smart phone is used as a transmission hub. The holter batteries choke more energy when running on the cellular networks than Bluetooth interface. Hence, the first objective was to maximize the holter battery life by making the connectivity of holter using bluetooth interface. Once the ECG data is obtained on the smart phone via Bluetooth connection, the second objective was to transmit the ECG data from smart phone towards medical database using the smart phone as transmission hub which utilizes cellular or wireless LAN network to send the ECG data. The third and the most important objective was to design and improve the heart beat detection using QRS detection algorithm to minimize the energy consumption by QRS detection using various programming methods. The proposed algorithm will take lesser time than usual added with effective energy consumption model to maximize the battery life of smart phone. The QRS algorithm for smart phones can be used to obtain the similar results they are getting from the medical databases. The QRS detection algorithm will generate the heart beat calculation results, which helps the patients to monitor themselves and to detect the emergency as earlier as possible. The medical databases monitor a number of patients at one point of time, hence, there is always a possibility of delay in case of emergency. Also, the medical services are hierarchical, which makes the process little slower which may put an adverse effect on the patients life. A little delay made while detecting the emergency and the service provided can cause casualty, which can be easily mitigated by using the localized monitoring. The results of the Bluetooth energy consumption has been obtained by using two Bluetooth enabled phones to transmit the data in the controlled environment where all other additional processes were shutdown on the receivers end. The receiver smart phone is running its essential processes along with the Bluetooth data channel. The smart phone energy computed adds the energy consumed by the initial processes also. The essential applications consist of operating system and other related essential processes. It is not possible to run the smart phone and its bluetooth without its operating and some essential processes. The recorded/computer heart beat is computer by performing QRS-detection algorithm on the medical database server by using the optimized ECG signal as the input signal for QRS-detection algorithm. The energy consumed and elapsed time has also been recorded for QRS detection on each patient dataset. The results have shown that the the new algorithm is very quick and consumed less than 1 joule energy for 90 seconds ECG data recorded at 512 samples per second.
Keywords: QRS detection, Peak analysis, ECG, Energy efficient algorithm
Edition: Volume 3 Issue 9, September 2014,
Pages: 846 - 851
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