4.6 Article

A Novel Gesture Recognition System for Intelligent Interaction with a Nursing-Care Assistant Robot

Journal

APPLIED SCIENCES-BASEL
Volume 8, Issue 12, Pages -

Publisher

MDPI
DOI: 10.3390/app8122349

Keywords

HMT gesture recognition; smart infrastructure; nursing-care assistant robot; wearable wrist-worn camera; continuous gesture segmentation; human-robot interaction

Funding

  1. National Key R&D Program of China [2017YFB1301203]
  2. Fundamental Research Funds for the Central Universities
  3. National Natural Science Foundation of China [U1509204]
  4. Science Fund for Creative Research Groups of the National Natural Science Foundation of China [51521064]
  5. China's Thousand Talents Plan Young Professionals Program
  6. Robotics Institute of Zhejiang University [K18-508116-008-03]

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The expansion of nursing-care assistant robots in smart infrastructure has provided more applications for homecare services, which has raised new demands for smart and natural interaction between humans and robots. This article proposed an innovative hand motion trajectory (HMT) gesture recognition system based on background velocity features. Here, a new wearable wrist-worn camera prototype for gesture's video collection was designed, and a new method for the segmentation of continuous gestures was shown. Meanwhile, a nursing-care assistant robot prototype was designed for assisting the elderly, which is capable of carrying the elderly with omnidirectional motion and grabbing the specified object at home. In order to evaluate the performance of the gesture recognition system, 10 special gestures were defined as the move commands for interaction with the robot, and 1000 HMT gesture samples were obtained from five subjects for leave-one-subject-out (LOSO) cross-validation classification with an average recognition accuracy of up to 97.34%. Moreover, the performance and practicability of the proposed system were further demonstrated by controlling the omnidirectional movement of the nursing-care assistant robot using the predefined gesture commands.

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