Priority-based adaptive transmission algorithm for medical devices in wireless body area networks (WBANs)

Abstract

A wireless body area network offers cost-effective solutions for healthcare infrastructure. An adaptive transmission algorithm is designed to handle channel efficiency, which adjusts packet size according to the difference in feature-point values that indicate biomedical signal characteristics. Furthermore, we propose a priority-adjustment method that enhances quality of service while guaranteeing signal integrity. A large number of simulations were carried out for performance evaluation. We use electrocardiogram and electromyogram signals as reference biomedical signals for performance verification. From the simulation results, we find that the average packet latency of proposed scheme is enhanced by 30% compared to conventional method. The simulation results also demonstrate that the proposed algorithm achieves significant performance improvement in terms of drop rates of high-priority packets around 0.3%–0.9 %.

Keywords

wireless body area network / channel efficiency / quality of service

References

[1] MartelliF, BurattiC, VerdoneR. On the performance of an IEEE 802.15.6 wireless body area network [C]. Proceedings of Wireless Conference 2011-Sustainable Wireless Technologies (European Wireless). Vienna, Austria, 20111-6

[2] YangGBody sensor networks, 20142nd EdLondon, Springer: 4-13

[3] KimJ, SongI, JangE, ChoiS. A dynamic duty cycle mac algorithm for wireless body area networks [J]. International Journal of Bio-Science and Bio-Technology, 2012, 4(2): 84-92

[4] GoldbergerA L, AmaralL, GlassL, HausdorffJ M, IvanovP C H, MarkR G, MietusJ E, MoodyG B, PengC K, StanleyH E. PhysioBank, PhysioToolkit, and PhysioNet: Components of a new research resource for complex physiologic signals [J]. Circulation, 2000, 101(23): 215-220

[5] NikolicMDetailed analysis of clinical electromyography signals EMG decomposition, findings and firing pattern analysis in controls and patients with myopathy and amytrophic lateral sclerosis [D], 2001

[6] IEEE 802.15. 6. Standard for local and metropolitan area networks- Part 15.6: Wireless body area networks [S], 2012

[7] KimJ, HongC, ChoiS. Optimal allocation of random access period for wireless body area network [J]. Journal of Central South University, 2013, 20: 2195-2201

[8] LiuB, YanZ, ChenC W. MAC protocol in wireless body area networks for E-health: Challenges and a context-aware design [J]. Wireless Communications, 2013, 20(4): 64-72

[9] LeeR G, MustardB E. Relationship between EMG patterns and kinematic properties for flexion movements at the human wrist [J]. Experimental Brain Research, 1987, 66(2): 247-256

[10] NgB S W, LogothetisN K, KayserC. EEG phase patterns reflect the selectivity of neural firing [J]. Cerebral Cortex, 2013, 23(2): 389-398

[11] PanJ, TompkinsW J. A real-time QRS detection algorithm [J]. IEEE Transactions on Biomedical Engineering, 1985, 32(3): 230-236

[12] XuX, LinY. ECG QRS complex detection using slope vector waveform (SVW) algorithm [C]. Proceedings of the 26th Annual International Conference of the IEEE EMBS. San Francisco, USA, 20043597-3600

[13] ChuJ, MoonI, MunM. A real-time EMG pattern recognition system based on linear-nonlinear feature projection for a multifunction myoelectric hand [J]. IEEE Transactions on Biomedical Engineering, 2006, 53(11): 2232-2239

[14] NazimovA I, PavlovA N, HramovA E, GrubovV V, KoronovskiiA A, SitnikovaE Y. Adaptive wavelet-based recognition of oscillatory patterns on electroencephalograms [C]. SPIE Proceedings. San Francisco, USA, 20138580-8581

[15] MuhammadG. Extended average magnitude difference function based pitch detection [J]. The International Arab Journal of Information Technology, 2011, 8(2): 197-203

[16] AbhinandiniU, ArpithaV, MadhuriC R, VijayV. Comparative study on ECG data compression methods [J]. International Journal of Innovative Research and Development, 2013, 2(11): 413-415

[17] SetiaV, KumarV. Coding of DWT coefficients using run-length coding and Huffman coding for the purpose of color image compression [J]. International Journal of Computer and Communication Engineering, 2012, 6: 201-204