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Implementation of Ultra Low Power Wireless ECG Signal Monitor in Nurse Auto Calling System 實現低功率無線 ECG 訊號偵測於護士自動呼叫系統. Presenter : Shao-Kai Liao Adviser : Tsung-Fu Chien Chairman : Hung-Chi Yang Date : 5.22.2013. Outline. Paper Review Purpose Introduction Methods Conclusions Future Work
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Implementation of Ultra Low Power Wireless ECG Signal Monitor in Nurse Auto Calling System實現低功率無線ECG訊號偵測於護士自動呼叫系統 Presenter : Shao-Kai Liao Adviser : Tsung-Fu Chien Chairman : Hung-Chi Yang Date : 5.22.2013
Outline • Paper Review • Purpose • Introduction • Methods • Conclusions • Future Work • References
Paper Review (a) Example of a synchronously sampled signal. (b) Example of an adaptive asynchronously sampled signal modeled after our prior approach Input-Feature Correlated Asynchronous Analog to Information Converter for ECG Monitoring Ritika Agarwal, Student Member, IEEE, and Sameer R. Sonkusale, Member, IEEE
Paper Review Dotted line: input ECG signal. Bold line: input-feature-correlated asynchronously taken samples.
Introduction • Electrocardiogram (ECG) P wave atrial contraction • T wave • repolarisation of the ventricles • QRS complex • ventricular contraction
Introduction • Wireless ECG signal transmission system Wireless ECG signal transmission system
Purpose • Reduce the burden of the nurses caring for patients. • Monitor environmental information for each ward. • Immediately notify the nurse at physiological signal abnormalities.
Methods • Software • TinyOS platform • AVR Studio 4 • NesC
Methods • Hardware ZigbeX Mote
Methods • Hardware Wireless ECG signal transmission system
Methods • Hardware The measured ECG signals Biomedical remote home care wireless sensor BIO module patch position
Methods • Hardware Nurse Auto Calling System UD-885
Methods • Software • ECG asynchronous sampling ECG asynchronous sampling trigger physiological signal high / low threshold
Conclusions • Highly efficient to bring a revolutionary change in ambulatory health monitoring. • Make emergency room abnormal physiological signals machine noise reduction. • reduce the number of wireless signal through asynchronous sampling algorithm
Future Work • Detect the P, Q, R, S and T waves. • Collected from the raw data is stored to the SD card is easy to observe when the error occurred • Integrated ECG physiological signal monitoring in the nurse call system.
References [1] M. S. Manikandan and S. Daudapat, Quality Controlled Wavelet Compression of ECG Signals by WEDD. Los Alamitos, CA: IEEE Comput. Soc, 2007. [2] L. Zhitao, K. Dong Youn, and W. A. Pearlman, “Wavelet compression of ECG signals by the set partitioning in hierarchical trees algorithm,” IEEE Trans. Biomed. Eng. , vol. 47, no. 7, pp. 849–856, Jul. 2000. [3] E. J. Candes, J. Romberg, and T. Tao, “Robust uncertainty principles: exact signal reconstruction from highly incomplete frequency information,” IEEE Tran˙s. Inf. Theory, vol. 52, no. 2, pp. 489–509, Feb. 2006. [4] E. J. Candes and M. B. Wakin, “An introduction to compressive sampling,” IEEE Signal Process. Mag., vol. 25, no. 2, pp. 21–30, Mar. 2008. [5] E. J. Candes and T. Tao, “Near-optimal signal recovery from random projections: Universal encoding strategies?,” IEEE Trans. Inf. Theory, vol. 52, no. 12, pp. 5406–5425, Dec. 2006. [6] M. F. Duarte, M. A. Davenport, D. Takhar, J. N. Laska, S. Ting, K. F. Kelly, and R. G. Baraniuk, “Single-pixel imaging via compressive sampling,” IEEE Signal Process. Mag., , vol. 25, no. 2, pp. 83–91, Mar. 2008.
