Wireless LAN Based Experiment and Evaluation of Effect on the Two-State ECG Compression Algorithm
Main Article Content
Abstract
ECG signal tele-monitoring that uses WLAN has been investigated and developed in recent years in order to enhance the efficiency of cardiovascular disease treatment and monitoring. However, there are several problems that may occur during the ECG signal transmission-receiving process, including bit errors and data packet loss. The causes of such problems include obstructions signal weakening due to far distances, larger number of users accessing the network at the same time, the presence of different WiFi networks operating at the same frequencies as that of ECG-WLAN and especially transmitted data packet sizes, of which significant changes will result in data loss on the transmission line. ECG signal compressing before transmitting is, therefore, critical. A two-state ECG compression algorithm has been proposed by the same group of authors in [1] and [2]. This paper describes the experiment and evaluation of the efficiency of the proposed WLAN-based two-state ECG compression algorithm. ECG data used in this experiment was from an arrhythmia ECG database. The results of experiment were evaluated by comparing some parameters such as packet error rate-PER, signal throughput, percentage of RMS difference (PRD), PRD Normalized (PRDN) and time delay between compressed and uncompressed signals and showed that the two-state compression algorithm helped to improve efficacy in ECG signal- WLAN transmission.
Keywords
Two-state ECG compression, packet error, throughput, Wireless LAN, ECG data
Article Details
References
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[2]. Duong Trong Luong, Nguyen Duc Thuan, "Evaluation of packet errors in wireless electrocardiogram (ECG) signal transmission system using wifi technology". Journal of Science and Technology. Technical Universities, Vietnam, No.96, (2013), pp.40-46.
[3]. Upkar Varshney, "Patient monitoring using infrastructure-oriented wireless LANs". Int.J. Electronic Healthcare, Vol. 2, No. 2, (2006), pp. 149-164.
[4]. Kyungtae Kang, Kyung-Joon Park, Jae-Jin Song, Chang-Hwan Yoon, and Lui Sha "A Medical-Grade Wireless Architecture for Remote Electrocardiography". IEEE transactions on information technology in biomedicine, vol. 15, No.2, (2011), pp.260-267.
[5]. Kyungtae Kang, Junhee Ryu, Junbeom Hur, and Lui Sha, "Design and QoS of a Wireless System for Real-Time Remote Electrocardiography". IEEE journal of biomedical and health informatics, vol. 17, no.3, (2013), pp.745-755.
[6]. Rachana Khanduri, S.S. Rattan, "Performance Comparison Analysis between IEEE 802.11a/b/g/n Standards". International Journal of Computer Applications, Vol. 78, No.1, (2013), pp.13-20.
[7]. Kenguka M. Kenguka, Atindimile S. Kumchaya, "Improving WLAN performance with enhanced mac, node cooperation and two-stage FEC scheme". Journal of Theoretical and Applied Information Technology, (2006), pp.14-20.
[8]. Jun Yin, Xiaodong Wang and Dharma P. Agrawal "Optimal Packet Size in Error-prone Channel for IEEE 802.11 Distributed Coordination Function". WCNC/IEEE Communications Society, (2004), pp. 1654-1659.
[9]. Duong Trong Luong, Nguyen Minh Duc, Nguyen Tuan Linh, Nguyen Duc Thuan, "A novel two-state ECG compression Algorithm used in telemedicine". Tạp chí khoa học và công nghệ các trường Đại học 109 (2015), pp.022-027.
[10]. Duong Trong Luong, Nguyen Minh Duc, Nguyen Tuan Linh, Nguyen Thai Ha, Nguyen Duc Thuan, "Advanced Two-State Compressing Algorithm: A Versatile, Reliable and Low-Cost Computational Method for ECG Wireless Applications". International Journal of Soft Computing and Engineering (IJSCE), Volume-5 Issue-6, (2016), pp. 56-70.
[11]. http://physionet.org/cgi-bin/atm/ATM
[12]. Mr. Sankusu Sharma, Prof.Rinku Shah, "Comparitive Study of IEEE 802.11a, b, g & n Standards". International Journal of Engineering Research & Technology (IJERT), Vol. 3 Issue 4, (2014), pp. 1846-1851.
[13]. Álvaro Alesanco and JoséGarcía, "Clinical Assessment of Wireless ECG Transmission in Real-Time Cardiac Telemonitoring". IEEE transactions on information technology in biomedicine, vol. 14, no. 5, (2010), pp. 1144-1152.
[14]. Mohammadreza Balouchestani, Kaamran Raahemifar and Sridhar Krishnan "High Resolution QRS Detection Algorithm for Wireless ECG Systems Based on Compressed Sensing Theory". IEEE explore (2013), pp. 1326-1329.