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Fall detection

Radar-Based Fall Detection: A Survey [Survey]

September 16, 2024 by Shuting Hu, Siyang Cao, Nima Toosizadeh, Jennifer Barton, Melvin G. Hector, Mindy J. Fain,

Fall detection, particularly critical for high-risk demographics like the elderly, is a key public health concern, where timely detection can greatly minimize harm. With the advancements in radio frequency (RF) technology, radar has emerged as a powerful tool for human fall detection. Traditional machine learning (ML) algorithms, such as support vector machines (SVM) and k … [Read more...] about Radar-Based Fall Detection: A Survey [Survey]

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IEEE Robotics & Automation Magazine (RAM) has over 14,000 readers who are the people who drive this remarkable technology. More than half work in basic research and many of the others are top level engineers and decision-makers in industry.  This magazine highlights new concepts in Robotics and Automation that are applied to real-world systems. It delivers tutorial and survey papers by distinguished experts in the field, organizes focused special issues on hot topics, and provides a forum for disseminating and discussing emerging trends, novel achievements, and selected news relevant to the development of the whole community active in these fields worldwide.

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IEEE Robotics & Automation Magazine  publishes four issues per year: March, June, September and December.