Discrete wavelet transform-based freezing of gait detection in Parkinson’s disease

References

• Ahmed, S. S., Dey, N., Ashour, A. S., Sifaki-Pistolla, D., Bălas-Timar, D., Balas, V. E., & Tavares, J. M. R. (2017). Effect of fuzzy partitioning in Crohn’s disease classification: A neuro-fuzzy-based approach. Medical & Biological Engineering & Computing, 55(1), 101–115.
   PubMed Web of Science ®Google Scholar
• Altman, D. G., & Bland, J. M. (1994). Statistics notes-diagnostic-tests-1-sensitivity and specificity. British Medical Journal, 308(6943), 1552–1552.
   PubMed Web of Science ®Google Scholar
• Bächlin, M., Plotnik, M., Roggen, D., Maidan, I., Hausdorff, J. M., Giladi, N., & Tröster, G. (2010). Wearable assistant for Parkinson’s disease patients with the freezing of gait symptom. IEEE Transactions on Information Technology in Biomedicine, 14(2), 436–446.
   PubMedGoogle Scholar
• Bibicu, D., Moraru, L., & Biswas, A. (2013). Thyroid nodule recognition based on feature selection and pixel classification methods. Journal of Digital Imaging, 26(1), 119–128.
   PubMed Web of Science ®Google Scholar
• Dey, N., & Ashour, A. (2016). Classification and Clustering in Biomedical Signal Processing (pp. 1-463). Hershey, PA: IGI Global. doi:10.4018/978-1-5225-0140-4.
   Google Scholar
• Han, J., Pei, J., & Kamber, M. (2011). Data mining: Concepts and techniques. Elsevier.
   Google Scholar
• Hemalatha, S., & Anouncia, S. M. (2017). Unsupervised segmentation of remote sensing images using FD based texture analysis model and ISODATA. International Journal of Ambient Computing and Intelligence (IJACI), 8(3), 58–75.
   Web of Science ®Google Scholar
• Hore, S., Chatterjee, S., Sarkar, S., Dey, N., Ashour, A. S., Balas-Timar, D., & Balas, V. E. (2016). Neural-based prediction of structural failure of multistoried RC buildings. Structural Engineering and Mechanics, 58(3), 459–473.
   Web of Science ®Google Scholar
• Jha, A. K. (2016). Sensing and supervising through IOT. International Journal of Computer Applications, 152, 9.
   Google Scholar
• Karamizadeh, S., Abdullah, S. M., Halimi, M., Shayan, J., & Javad Rajabi, M. (2014, September). Advantage and drawback of support vector machine functionality. 2014 IEEE International Conference on Computer, Communications, and Control Technology, pp. 63–65
   Google Scholar
• Kotsiantis, S. B., Zaharakis, I., & Pintelas, P. (2007). Supervised machine learning: A review of classification techniques. Emerging Artificial Intelligence Applications in Computer Engineering, (2007(160), 3–24.
   Google Scholar
• Li, Z., Shi, K., Dey, N., Ashour, A. S., Wang, D., Balas, V. E., … Shi, F. (2017). Rule-based back propagation neural networks for various precision rough set presented KANSEI knowledge prediction: A case study on shoe product form features extraction. Neural Computing and Applications, 28(3), 613–630.
   Web of Science ®Google Scholar
• Mazilu, S., Blanke, U., Dorfman, M., Gazit, E., Mirelman, A., M Hausdorff, J., & Tröster, G. (2015). A wearable assistant for gait training for Parkinson’s disease with freezing of gait in out-of-the-lab environments. ACM Transactions on Interactive Intelligent Systems, 5(1), 5.
   Web of Science ®Google Scholar
• Mazilu, S., Calatroni, A., Gazit, E., Roggen, D., Hausdorff, J. M., & Tröster, G. (2013, July). Feature learning for detection and prediction of freezing of gait in Parkinson’s disease. In Petra Perner, editor. International workshop on machine learning and data mining in pattern Recognition (pp. 144–158). Berlin, Heidelberg: Springer.
   Google Scholar
• Moore, S. T., MacDougall, H. G., & Ondo, W. G. (2008). Ambulatory monitoring of freezing of gait in Parkinson’s disease. Journal of Neuroscience Methods, 167(2), 340–348.
   PubMed Web of Science ®Google Scholar
• Obaidullah, S. M., Roy, K., & Das, N. (2013, September). Comparison of different classifiers for script identification from handwritten document. In Signal Processing, Computing and Control (ISPCC), 2013 IEEE International Conference on (pp. 1–6). IEEE.
   Google Scholar
• Rezvanian, S., & Lockhart, T. E. (2016). Towards real-time detection of freezing of gait using wavelet transform on wireless accelerometer data. Sensors, 16(4), 475.
   Web of Science ®Google Scholar
• Saba, L., Dey, N., Ashour, A. S., Samanta, S., Nath, S. S., Chakraborty, S., & Suri, J. S. (2016). Automated stratification of liver disease in ultrasound: An online accurate feature classification paradigm. Computer Methods and Programs in Biomedicine, 130, 118–134.
   PubMed Web of Science ®Google Scholar
• Sghaier, S., Farhat, W., & Souani, C. (2018). Novel technique for 3D Face Recognition using anthropometric methodology. International Journal of Ambient Computing and Intelligence, 9(1), 60–77.
   Web of Science ®Google Scholar
• Sharma, K., & Virmani, J. (2017). A decision support system for classification of normal and medical renal disease using ultrasound images: A decision support system for medical renal diseases. International Journal of Ambient Computing and Intelligence (IJACI), 8(2), 52–69.
   Web of Science ®Google Scholar
• Sutagundar, A. V., & Hatti, D. (2017). Data Management in Internet of Things. In I. Management Association (Ed.), The Internet of Things: Breakthroughs in Research and Practice (pp. 365-382). Hershey, PA: IGI Global. doi:10.4018/978-1-5225-1832-7.ch017.
   Google Scholar
• Swets, J. A. (2014). Signal detection theory and ROC analysis in psychology and diagnostics: Collected papers. Psychology Press.
   Google Scholar
• Wang, D., Li, Z., Cao, L., Balas, V. E., Dey, N., Ashour, A. S., … Shi, F. (2016). Image fusion incorporating parameter estimation optimized gaussian mixture model and fuzzy weighted evaluation system: A case study in time-series plantar pressure data set. IEEE Sensors Journal, 17(5), 1407–1420.
   Web of Science ®Google Scholar
• Webb, A. R. (2003). Statistical pattern recognition. John Wiley & Sons.
   Google Scholar
• Zabaleta, H., Keller, T., & Masso, J. M. (2009). Power spectral distribution analysis for detection of freezing of gait in patients with Parkinson’s disease. In J. Vander Sloten, P. Verdonck, M. Nyssen, J. Haueisen (Eds.) 4th European conference of the international federation for medical and biological engineering (pp. 2089–2092). Berlin, Heidelberg: Springer.
   Google Scholar