Awkward working posture recognition method for construction workers based on multimodal data fusion
Through multimodal data fusion method, including feature extraction and fusion of EEG, behavior and posture data, combined with BP neural network, the problem of inaccurate recognition of embarrassing work postures for construction workers in the existing technology is solved, and the embarrassing work postures for construction workers is realized. Automatic identification of work postures and improvement of occupational health and safety.
CN116115239BActive Publication Date: 2025-01-07SOUTHEAST UNIV
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Patent Information
- Application Number
- CN202211474969.3
- Authority / Receiving Office
- CN · China
- Patent Type
- Patents(China)
- Current Assignee / Owner
- Filing Date
- 2022-11-23
- Publication Date
- 2025-01-07
- Estimated Expiration
- 2042-11-23
Smart Images
Figure CN116115239B_ABST
Abstract
The present invention discloses a method for recognizing awkward working postures of construction workers based on multimodal data fusion, comprising collecting original EEG data, original behavior data and original posture images of a monitored person; preprocessing the original EEG data to extract time domain, frequency domain and nonlinear features; standardizing the original behavior data and extracting the mean as the behavior data feature; extracting the spatial coordinates of main points of the human body from the posture image of the monitored person as posture state features; fusing the extracted data features based on a preliminary fusion strategy; inputting the fused feature data set into a trained BP neural network, and outputting the embarrassing posture work category of the monitored person, thereby realizing automatic recognition of awkward working postures by extracting multimodal data fusion features of the EEG data, behavior data and posture images of the monitored person, and improving the limitations of insufficient accuracy in posture recognition based on single-modal data.
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