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Dr. Saman Parvaneh received his Bachelors in electrical engineering in 2003 followed by MSc and PhD degree in biomedical engineering in 2005 and 2011, respectively. During his PhD, his primary focus was on algorithm development and bio-signal processing to predict spontaneous termination of atrial fibrillation. Specifically, he developed a novel geometric algorithm based on the chaos theory for this purpose.
During his service at the University of Arizona as a postdoctoral research associate, he developed an innovative algorithm for assessing physiological stress response using a wearable device and employed it for assessing stress in the patient population (e.g. diabetes patient) as well as surgeons during surgery. He also worked on a fusion of cardiac response (e.g. heart rate and heart rate variability) and human movement monitoring and analysis in real-world conditions mainly based on wearable technologies and inertial sensors for objective risk and performance assessment. He used his expertise for frailty and risk of fall assessment in older adults as well as a risk of fall assessment in ICU patients.
He is currently a Principal Data Scientist at Edwards Lifesciences, Irvine-California. Previously, he was a Senior Data Scientist at the Clinical Analytics and Therapy Decision Support Solutions team in Philips Research North America. His research interests include the development of clinical decision support systems and predictive modeling. He is author or co-author of more than 40 scientific papers published in peer-reviewed journals and presented at international conferences.
Research Interests
- Biomedical signal processing and modeling
- Algorithm development for body-worn sensors (e.g. accelerometer/gyroscope/pressure sensor/ECG monitoring)
- Emotion assessment and affective computing using bio-signals (e.g. heart rate and HRV)
- Outcome Evaluation (e.g. gait, balance, physical activity, and physiological response)
- Development of clinical decision support
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- Invited Speaker at the Deep Learning in Healthcare & Pharma Summit, Boston-MA. - Presented two articles and chaired one session at Computing in Cardiology 2023. - Invited speaker at 47th Annual Scientific Conference of International Society for Computerized Electrocardiology (ISCE 2023), Indian Wells-CA. - Presented three articles and chaired one session at Computing in Cardiology 2022. - Presented two articles and chaired one special session on "Cardiac autonomic nervous system, heart rate response, and recovery in response to activity: Implication of wearable sensors for frailty assessment" at Computing in Cardiology 2021. - Paper entitled "Frailty and Heart Response to Physical Activity" has been published in the Archives of Gerontology and Geriatrics. - Paper entitled "Pervasive Lying Posture Tracking" has been published in the Sensors. - Presented one article at Computing in Cardiology 2020. - Paper entitled "Path to precision: prevention of post-operative atrial fibrillation" has been published in the Journal of Thoracic Disease. - Paper entitled "Can motor function uncertainty and local instability within upper-extremity dual-tasking predict amnestic mild cognitive impairment and early-stage Alzheimer's disease?" has been published in Computers in Biology and Medicine. - Joined Edwards Lifesciences as Principal Data Scientist - Presented five articles at Computing in Cardiology 2019. - Selected as the winner (2nd place) in the international annual PhysioNet/Computing in Cardiology Hackathon 2019. - Paper entitled "Cardiac Arrhythmia Detection using Deep Learning: A review" has been published in the Journal of Electrocardiology. - Invited speaker at 44th Annual Scientific Conference of International Society for Computerized Electrocardiology (ISCE 2019), Atlantic Beach-FL. - Awarded a grant on "Unobtrusive Machine Learning-Driven Home Safety Solution for Veterans" from the Department of Veterans Affairs - Invited Speaker at MIT IEEE Undergraduate Research Technology Conference, Boston-MA. - Presented "Electrocardiogram Monitoring and Interpretation: From Traditional Machine Learning to Deep Learning, and Their Combination" in a special session at Computing in Cardiology 2018. - Presented two articles at Computing in Cardiology 2018. - Paper entitled "Densely Connected Convolutional Networks for Detection of Atrial Fibrillation from Short Single-Lead ECG Recordings" has been published in the Journal of Electrocardiology. - Paper entitled "Analyzing single-lead short ECG recordings using dense convolutional neural networks and feature-based post processing to detect atrial fibrillation" has been published in the Physiological Measurement. - Awarded a grant on "In-home Assistive Technology for Reducing Risk of Pressure Ulcers in Veterans with Compromised Mobility" from the Department of Veterans Affairs. - Presented a poster at the 43rd Annual Scientific Conference of International Society for Computerized Electrocardiology (ISCE 2018). - Presented seven articles at Computing in Cardiology 2017. - Invited Speaker at the Deep Learning in Healthcare Summit, Boston-MA. - Paper entitled "Postural Transitions during Activities of Daily Living Could Identify Frailty Status: Application of Wearable Technology to Identify Frailty during Unsupervised Condition" has been published in the Journal of Gerontology. - Selected as winner (first prize) in the international annual PhysioNet/Computing in Cardiology Challenge 2016. - Presented three articles at Computing in Cardiology 2016. - Paper entitled "Stress among surgical attendings and trainees: A quantitative assessment during trauma activation and emergency surgeries" has been published in the Journal of Trauma and Acute Care Surgery. - Awarded a grant on "Personalized Location-aware Assisted Technology for Improving Quality of Life and Independence in Individuals with Mild Cognitive Impairment" from the Department of Veterans Affairs. - Presented a poster at 41st Annual Scientific Conference of International Society for Computerized Electrocardiology (ISCE 2016).
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