This paper is in the following e-collection/theme issue:

Wearable Devices and Sensors (876) Machine Learning (1434)

Published on in Vol 5, No 8 (2017): August

Feature-Free Activity Classification of Inertial Sensor Data With Machine Vision Techniques: Method, Development, and Evaluation

Feature-Free Activity Classification of Inertial Sensor Data With Machine Vision Techniques: Method, Development, and Evaluation

Feature-Free Activity Classification of Inertial Sensor Data With Machine Vision Techniques: Method, Development, and Evaluation

Authors of this article:

Jose Juan Dominguez Veiga1 Author Orcid Image ;   Martin O'Reilly2 Author Orcid Image ;   Darragh Whelan2 Author Orcid Image ;   Brian Caulfield2 Author Orcid Image ;   Tomas E Ward1 Author Orcid Image
Article Authors Cited by (16) Tweetations (19) Metrics

Journals

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  3. Zeng W, Ismail S, Pappas E. Detecting the presence of anterior cruciate ligament deficiency based on a double pendulum model, intrinsic time-scale decomposition (ITD) and neural networks. Artificial Intelligence Review 2020;53(5):3231 View
  4. O’Reilly M, Caulfield B, Ward T, Johnston W, Doherty C. Wearable Inertial Sensor Systems for Lower Limb Exercise Detection and Evaluation: A Systematic Review. Sports Medicine 2018;48(5):1221 View
  5. Lee J, Kang T, Choi B, Han I, Kim B, Ro J. Application of Deep Learning System into the Development of Communication Device for Quadriplegic Patient. Korean Journal of Neurotrauma 2019;15(2):88 View
  6. Dorschky E, Nitschke M, Martindale C, van den Bogert A, Koelewijn A, Eskofier B. CNN-Based Estimation of Sagittal Plane Walking and Running Biomechanics From Measured and Simulated Inertial Sensor Data. Frontiers in Bioengineering and Biotechnology 2020;8 View
  7. Prabhu G, O’Connor N, Moran K. Recognition and Repetition Counting for Local Muscular Endurance Exercises in Exercise-Based Rehabilitation: A Comparative Study Using Artificial Intelligence Models. Sensors 2020;20(17):4791 View
  8. Mangal N, Tiwari A. A review of the evolution of scientific literature on technology-assisted approaches using RGB-D sensors for musculoskeletal health monitoring. Computers in Biology and Medicine 2021;132:104316 View
  9. Donisi L, Cesarelli G, Coccia A, Panigazzi M, Capodaglio E, D’Addio G. Work-Related Risk Assessment According to the Revised NIOSH Lifting Equation: A Preliminary Study Using a Wearable Inertial Sensor and Machine Learning. Sensors 2021;21(8):2593 View
  10. Lee H, Youm S. Development of a Wearable Camera and AI Algorithm for Medication Behavior Recognition. Sensors 2021;21(11):3594 View
  11. Chong J, Tjurin P, Niemelä M, Jämsä T, Farrahi V. Machine-learning models for activity class prediction: A comparative study of feature selection and classification algorithms. Gait & Posture 2021;89:45 View
  12. Bochniewicz E, Emmer G, Dromerick A, Barth J, Lum P. Measurement of Functional Use in Upper Extremity Prosthetic Devices Using Wearable Sensors and Machine Learning. Sensors 2023;23(6):3111 View

Books/Policy Documents

  1. Mishra A, Mohapatra S, Bisoy S. Augmented Intelligence in Healthcare: A Pragmatic and Integrated Analysis. View
  2. Zapata B, Narváez F, García M, Zapata D. Systems, Smart Technologies and Innovation for Society. View