Assessing exposure to slip, trip, and fall hazards based on abnormal gait patterns predicted from confidence interval estimation
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BiLSTM fuses forward/backward temporal information via bidirectional architecture, captures complete temporal context, and is used for gait phase segmentation and stair ascent/descent intent.
“| BiLSTM | Fuse forward/backward temporal information via | Capture complete temporal context | Gait phase segmentation, stair ascent/descent |”
From Recent advances in intelligent wearable systems: from multiscale biomechanical features towards human motion intent prediction (2026) · cites this paper as [168]
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- Authors
- Lee, H., Lee, G., Lee, S., & Ahn, C. R.
- Affiliations
- University of Michigan (US)
- Seoul National University (KR)
- Corresponding author
- Ahn, Changbum R.
- Venue
- Automation in Construction
- Publisher
- Elsevier BV
- Published
- 2022-07
- Volume
- 139
- Pages
- 104253
- ISSN
- 0926-5805 (ISSN-L)
- OpenAlex
- W4224254305
- Cited by
- 31
- References
- 65
- Citations by year
- 2026: 8 · 2025: 9 · 2024: 5 · 2023: 7 · 2022: 2
- FWCI
- 4.68
- Type
- journal article
- Language
- en
- Open access
- closed
- Licence
- Locations
- Automation in Construction (publishedVersion)
- Topics
- Health Sciences › Health Professions › Radiological and Ultrasound Technology › Occupational Health and Safety Research
- Health Sciences › Health Professions › Physical Therapy, Sports Therapy and Rehabilitation › Balance, Gait, and Falls Prevention
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Context-Aware Activity Recognition Systems
- Keywords
- occupational exposure assessment, abnormal gait detection, inertial measurement unit, Mahalanobis distance, bidirectional LSTM, confidence interval estimation, construction workers, fall prevention
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