Sensors for Human Activity Recognition

Edited by
June 2023
216 pages
  • ISBN978-3-0365-7554-4 (Hardback)
  • ISBN978-3-0365-7555-1 (PDF)

This book is a reprint of the Special Issue Sensors for Human Activity Recognition that was published in

Chemistry & Materials Science
Environmental & Earth Sciences

Human activity recognition (HAR) and human behavior recognition (HBR) play increasingly important roles in the digital age. High-quality sensory observations applicable to recognizing users’ activities and behaviors, including electrical, magnetic, mechanical (kinetic), optical, acoustic, thermal, and chemical biosignals, are inseparable from sensors’ sophisticated design and appropriate application.

Traditional sensors suitable for HAR and HBR, including external sensors for smart homes, optical sensors such as cameras for capturing video signals, and bioelectrical, biomagnetic, and biomechanical sensors for wearable applications, have been studied and verified adequately. They continue to be researched in depth for more effective and efficient usage, and brand-new areas facilitated by sensor-based HAR/HBR are emerging, such as interactive edutainment, single-motion duration analysis, time series information retrieval, handcrafted and high-level feature design, and fall detection. Meanwhile, innovative sensor research for HAR or HBR is also very active in the academic community, including new sensors appropriate for HAR/HBR, new designs and applications of the above-mentioned traditional sensors, and the usage of non-traditional HAR-/HBR-related sensor types, among others.

  • Hardback
License and Copyright
© 2022 by the authors; CC BY-NC-ND license
human activity recognition; validation methodology; leave-one-subject-out cross-validation; explainable methods; Shapley additive explanations; machine learning; camera calibration; point-to-point camera distortion calibration; vision-based human activity recognition; speckle pattern; digital image correlation; human activity recognition; sensing technique; HAR; semi-supervised learning; adversarial learning; syn-LSTM; smart home; human activity recognition; Wi-Fi sensing; multi-location; deep complex network; ankle–foot orthoses; energy consumption; functional electrical stimulation; human in the loop; smart retail; in-store camera; customer behavior recognition; behavior reconstruction; indoor localization; pedestrian dead reckoning; deep learning; GPS; human activity recognition; deep learning; domain generalization; accelerometer; psychological stress; electrocardiogram; heart rate variability; gated recurrent unit; VR high-altitude experiment; wearable devices; n/a

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