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- EEG/non-EEG Data for Epileptic Seizure Study
This research, "A Wrist-Worn Biosensor System for Epileptic Seizure Alert", started in 2013 and was partially supported by Texas Medical Research Collaborative. We collected EEG and non-EEG (5-sensor wrist-worn device) from 20 patients in a Dallas Hospital's Epilepsy Monitoring Unit (EMU).
Our data analysis and findings are partially reported in the following publications:
- J. Birjandtalab, M. James, M. Nourani and J. Harvey, "Learning from Non-Seizure Clusters for EEG Analytics," in Proceedings of the IEEE/CAS-EMB Biomedical Circuits and Systems Conference (BioCAS), Oct. 2018.
- J. Birjandtalab, M. Baran Pouyan, D. Cogan, M. Nourani and J. Harvey, "Automated Seizure Detection Using Limited-Channel EEG and Non-Linear Dimension Reduction," in Elsevier Computers in Biology and Medicine - Chosen as a 2017 Esteemed Paper, vol. 82, no. C, pp. 49-58, March 2017.
- D. Cogan, J. Birjandtalab, M. Nourani, J. Harvey and V. Nagaraddi, "Multi-Biosignal Analysis for Epileptic Seizure Monitoring," International Journal of Neural Systems (IJNS), pp. 1-18, May 2016.
- D. Cogan, M. Nourani, J. Harvey and V. Nagaraddi, "Seizure Detection by Multi Extracerebral Biosignal Analysis," The American Epilepsy Society Annual Meeting Society (AES), Dec. 2015.
- In-Bed Posture Data for Smart Bed Study
This research, "Pressure Map Analytics for Ulcer Prevention", started in 2011 and was partially supported by National Science Foundation. This was an SBIR award done in Dena Technologies, Inc. a spin-off of University of Texas at Dallas to implement a continuous cloud-based pressure monitoring platform for prevention and management of pressure ulcers. The pressure image data was collected from 13 subjects in 29 in-bed postures.
Our data analysis and findings are partially reported in the following publications:
- M. Baran Pouyan, J. Birjandtalab, M. Nourani and M. Pompeo, "Automatic Limb Identification and Sleeping Parameters Assessment for Pressure Ulcer Prevention," Elsevier Computers in Biology and Medicine, vol. 75, no. 1, pp. 98-108, Aug. 2016.
- S. Ostadabbas, R. Yousefi, M. Nourani, M. Faezipour, L. Tamil and M. Pompeo, "Resource-Efficient Planning for Pressure Ulcer Prevention," IEEE Transactions on Information Technology in BioMedicine (TITB), vol. 16, no. 6, pp. 1265-1273, Nov. 2012
- M. Baran Pouyan, J. Birjandtalab, M. Nourani and S. Ostadabbas, "Pressure Map Dataset for Posture and Subject Analytics," in Proceedings of the IEEE International Conference on Biomedical and Health Informatics (BHI), pp. 65-68, Feb. 2017.
- M. Baran Pouyan, M. Nourani and M. Pompeo, "Clustering-Based Limb Identification for Pressure Ulcer Risk Assessment," in Proceedings of the International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), pp. 4230-4233, Aug. 2015.
- Single-Cell Data Analytics
This research, "Single-Cell Flow Cytometry Data Analytics", started in 2015 and was partially supported by The University of Texas at Dallas. We have made our data analysis, R codes for machine learning techniques, for the particular field of single-cell technology and drug discovery available.
Our data analysis and findings are partially reported in the following publications:
- M. Baran Pouyan and M. Nourani, "Identifying Cell Populations in Flow Cytometry Data Using Phenotypic Signatures," IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB), vol. 14, no. 4, pp. 880-891, July 2017.
- M. Baran Pouyan and M. Nourani, "Clustering Single-Cell Expression Data Using Random Forest Graphs," IEEE Journal of Biomedical and Health Informatics (J-BHI), vol. 21, no. 4, pp. 1172-1181, July 2017.
- M. Baran Pouyan, V. Jindal, J. Birjandtalab and M. Nourani, "Single and Multi-Subject Clustering of Flow Cytometry Data for Cell-Type Identification and Anomaly Detection," BMC Medical Genomics, vol. 9 (Suppl 2), no. 41, pp. 100-110, Dec. 2016.
- M. Baran Pouyan, V. Jindal and M. Nourani, "Clinical Outcome Prediction Using Single-Cell Data," IEEE Transactions on Biomedical Circuits and Systems (TBioCAS), vol. 10, no. 5, pp. 1012-1022, Oct. 2016.