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Lymphedema Characterization Using Segmental Bio-Impedance Signals and Early Detection with Machine Learning

Principal Investigator: Jayasree K. R.,Faculty Associate, Electronics and Electrical Department, School of Engineering, PhD Scholar, Amrita WNA

AmritaTeam Members: Dr.Rahul Krishnan Pathinarupothi, Amrita WNA

Indian Collaborators: Dr.Vijaykumar D. K., Head of Department, Professor, Department of Gynecological Oncology, AIMS, Kochi

International Collaborators: Dr. Vijayan Sugumaran, Ph.D., Distinguished Professor, Management Information Systems, Chair, Department of Decision and Information Sciences,
Co-Director, Center for Data Science and Big Data Analytics, School of Business Administration, Oakland University, USA

Lymphedema Characterization Using Segmental Bio-Impedance Signals and Early Detection with Machine Learning

The term lymphedema is associated with breast cancer. After oncological treatment on this issue, in most of the cases, the lymph fluid in our lymphatic system gets blocked and creates swelling in the arms of patients even after undergoing a painful surgery. If proper quantification of lymphatic fluid and early diagnosis is done, the percent of lymphedema in patients can be decreased tremendously. Early detection of lymphedema can help physicians to provide patients interventions (surgical or otherwise) that can avoid debilitating swelling. Aim is to develop a proof of concept – segmental bioimpedance based measurement and early warning system to address this challenge.

Future Works

Data driven approach on patients for early diagnosis of lymphedema using Bio impedance monitoring kit-MAX30001 EVSYS.

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