Atrial fibrillation detection service validation tool

Faust, O., Kareem, M., & Lei, N. (2021). Atrial fibrillation detection service validation tool. Software Impacts, 10, 100117.

Automated classification of five arrhythmias and normal sinus rhythm based on RR interval signals

Faust, O., & Acharya, U. R. (2021). Automated classification of five arrhythmias and normal sinus rhythm based on RR interval signals. Expert Systems with Applications, 181, 115031.

Automated arrhythmia detection based on RR intervals

Faust, O., Kareem, M., Ali, A., Ciaccio, E. J., & Acharya, U. R. (2021). Automated arrhythmia detection based on RR intervals. Diagnostics, 11(8), 1446.

A review of patient-led data acquisition for atrial fibrillation detection to prevent stroke

Kareem, M., Lei, N., Ali, A., Ciaccio, E. J., Acharya, U. R., & Faust, O. (2021). A review of patient-led data acquisition for atrial fibrillation detection to prevent stroke. Biomedical Signal Processing and Control, 69, 102818.

A smart sleep apnea detection service

Barika, R., Shenfield, A., Razaghi, H., & Faust, O. (2021, June). A smart sleep apnea detection service. In 17th International Conference on Condition Monitoring and Asset Management, CM 2021. The British Institute of NDT.

Accurate detection of sleep apnea with long short-term memory network based on RR interval signals

Faust, O., Barika, R., Shenfield, A., Ciaccio, E. J., & Acharya, U. R. (2021). Accurate detection of sleep apnea with long short-term memory network based on RR interval signals. Knowledge-Based Systems, 212, 106591.

Hybrid decision support to monitor atrial fibrillation for stroke prevention

Lei, N., Kareem, M., Moon, S. K., Ciaccio, E. J., Acharya, U. R., & Faust, O. (2021). Hybrid decision support to monitor atrial fibrillation for stroke prevention. International Journal of Environmental Research and Public Health, 18(2), 813.

Application of nonlinear methods to discriminate fractionated electrograms in paroxysmal versus persistent atrial fibrillation

Acharya, U. R., Faust, O., Ciaccio, E. J., Koh, J. E. W., Oh, S. L., San Tan, R., & Garan, H. (2019). Application of nonlinear methods to discriminate fractionated electrograms in paroxysmal versus persistent atrial fibrillation. Computer methods and programs in biomedicine, 175, 163-178.

Validating the robustness of an internet of things based atrial fibrillation detection system

Faust, O., Kareem, M., Shenfield, A., Ali, A., & Acharya, U. R. (2020). Validating the robustness of an internet of things based atrial fibrillation detection system. Pattern Recognition Letters, 133, 55-61.

Comprehensive electrocardiographic diagnosis based on deep learning

Lih, O. S., Jahmunah, V., San, T. R., Ciaccio, E. J., Yamakawa, T., Tanabe, M., … & Acharya, U. R. (2020). Comprehensive electrocardiographic diagnosis based on deep learning. Artificial intelligence in medicine, 103, 101789.

Automated Detection of Sleep Stages Using Deep Learning Techniques: A Systematic Review of the Last Decade (2010–2020)

Loh, H. W., Ooi, C. P., Vicnesh, J., Oh, S. L., Faust, O., Gertych, A., & Acharya, U. R. (2020). Automated Detection of Sleep Stages Using Deep Learning Techniques: A Systematic Review of the Last Decade (2010–2020). Applied Sciences, 10(24), 8963.

A smart service platform for cost efficient cardiac health monitoring

Faust, O., Lei, N., Chew, E., Ciaccio, E. J., & Acharya, U. R. (2020). A smart service platform for cost efficient cardiac health monitoring. International journal of environmental research and public health, 17(17), 6313.

A review of atrial fibrillation detection methods as a service

Faust, O., Ciaccio, E. J., & Acharya, U. R. (2020). A review of atrial fibrillation detection methods as a service. International journal of environmental research and public health, 17(9), 3093.

Establishing the safety of a smart heart health monitoring service through validation

Kareem, M., & Faust, O. (2019, December). Establishing the safety of a smart heart health monitoring service through validation. In 2019 IEEE International Conference on Big Data (Big Data) (pp. 6089-6091). IEEE.

Improving the safety of atrial fibrillation monitoring systems through human verification

Faust, O., Ciaccio, E. J., Majid, A., & Acharya, U. R. (2019). Improving the safety of atrial fibrillation monitoring systems through human verification. Safety science, 118, 881-886.

A review of automated sleep stage scoring based on physiological signals for the new millennia

Faust, O., Razaghi, H., Barika, R., Ciaccio, E. J., & Acharya, U. R. (2019). A review of automated sleep stage scoring based on physiological signals for the new millennia. Computer methods and programs in biomedicine176, 81-91.

Application of nonlinear methods to discriminate fractionated electrograms in paroxysmal versus persistent atrial fibrillation

Acharya, U. R., Faust, O., Ciaccio, E. J., Koh, J. E. W., Oh, S. L., San Tan, R., & Garan, H. (2019). Application of nonlinear methods to discriminate fractionated electrograms in paroxysmal versus persistent atrial fibrillation. Computer methods and programs in biomedicine, 175, 163-178.

Automated characterization of cardiovascular diseases using wavelet transform features extracted from ECG signals

Mohsin, A., & Faust, O. (2019). Automated characterization of cardiovascular diseases using wavelet transform features extracted from ECG signals. Journal of mechanics in medicine and biology, 19(01), 1940009.

Heart-rate based sleep apnea detection using Arduino

Pearson, M., & Faust, O. (2019). Heart-rate based sleep apnea detection using Arduino. Journal of mechanics in medicine and biology19(01), 1940006.

Automated detection of atrial fibrillation using long short-term memory network with RR interval signals

Faust, O., Shenfield, A., Kareem, M., San, T. R., Fujita, H., & Acharya, U. R. (2018). Automated detection of atrial fibrillation using long short-term memory network with RR interval signals. Computers in biology and medicine, 102, 327-335.

Deep learning for healthcare applications based on physiological signals: A review

Faust, O., Hagiwara, Y., Hong, T. J., Lih, O. S., & Acharya, U. R. (2018). Deep learning for healthcare applications based on physiological signals: A review. Computer methods and programs in biomedicine, 161, 1-13.

Automated diagnosis of depression electroencephalograph signals using linear prediction coding and higher order spectra features

Bairy, G. M., Lih, O. S., Hagiwara, Y., Puthankattil, S. D., Faust, O., Niranjan, U. C., & Acharya, U. R. (2017). Automated diagnosis of depression electroencephalograph signals using linear prediction coding and higher order spectra features. Journal of Medical Imaging and Health Informatics, 7(8), 1857-1862.

Algorithm for the detection of congestive heart failure index

Kang, Y. D., Zhuo, D., Foo, R. E. A., Lim, C. M., Faust, O., & Hagiwara, Y. (2017). Algorithm for the detection of congestive heart failure index. Journal of Mechanics in Medicine and Biology, 17(07), 1740043.

Nonlinear analysis of coronary artery disease, myocardial infarction, and normal ECG signals

Hagiwara, Y., & Faust, O. (2017). Nonlinear analysis of coronary artery disease, myocardial infarction, and normal ECG signals. Journal of Mechanics in Medicine and Biology, 17(07), 1740006.

Computer aided diagnosis for cardiovascular diseases based on ecg signals: a survey

Faust, O., & Ng, E. Y. (2016). Computer aided diagnosis for cardiovascular diseases based on ecg signals: a survey. Journal of Mechanics in Medicine and Biology, 16(01), 1640001.

A review of ECG-based diagnosis support systems for obstructive sleep apnea

Faust, O., Acharya, U. R., Ng, E. Y. K., & Fujita, H. (2016). A review of ECG-based diagnosis support systems for obstructive sleep apnea. Journal of Mechanics in Medicine and Biology, 16(01), 1640004.

The role of real-time in biomedical science: A meta-analysis on computational complexity, delay and speedup

Faust, O., Yu, W., & Acharya, U. R. (2015). The role of real-time in biomedical science: A meta-analysis on computational complexity, delay and speedup. Computers in biology and medicine, 58, 73-84.

Automated classification of normal and premature ventricular contractions in electrocardiogram signals

Jenny, N. Z. N., Faust, O., & Yu, W. (2014). Automated classification of normal and premature ventricular contractions in electrocardiogram signals. Journal of Medical Imaging and Health Informatics, 4(6), 886-892.

Wavelet based machine learning techniques for electrocardiogram signal analysis

Zhi, K. Y., Faust, O., & Yu, W. (2014). Wavelet based machine learning techniques for electrocardiogram signal analysis. Journal of Medical Imaging and Health Informatics4(5), 737-742.

Linear and nonlinear analysis of normal and CAD-affected heart rate signals

Acharya, U. R., Faust, O., Sree, V., Swapna, G., Martis, R. J., Kadri, N. A., & Suri, J. S. (2014). Linear and nonlinear analysis of normal and CAD-affected heart rate signals. Computer methods and programs in biomedicine, 113(1), 55-68.