Machine Learning Based Human Activity Detection in a Privacy-Aware Compliance Tracking System
| Title | Machine Learning Based Human Activity Detection in a Privacy-Aware Compliance Tracking System |
| Publication Type | Conference Paper |
| Year of Publication | 2018 |
| Authors | Wu, Q., Zhao, W. |
| Conference Name | 2018 IEEE International Conference on Electro/Information Technology (EIT) |
| ISBN Number | 978-1-5386-5398-2 |
| Keywords | Back, back-bending activities detection, body mechanics, data acquisition, data privacy, expert rules, expert systems, field data acquisition, high-level bending activities, human activity detection, Human activity prediction, human factors, human skeleton data, Injuries, learning (artificial intelligence), lifting-pulling tasks, local nursing home, machine learning, machine learning techniques, Microsoft Kinect, Neural Network, nursing staffs baseline, object detection, PACTS, patient care, privacy, privacy-aware compliance tracking system, pubcrawl, Real-time Systems, Scalability, Skeleton, Support vector machines |
| Abstract | In this paper, we report our work on using machine learning techniques to predict back bending activity based on field data acquired in a local nursing home. The data are recorded by a privacy-aware compliance tracking system (PACTS). The objective of PACTS is to detect back-bending activities and issue real-time alerts to the participant when she bends her back excessively, which we hope could help the participant form good habits of using proper body mechanics when performing lifting/pulling tasks. We show that our algorithms can differentiate nursing staffs baseline and high-level bending activities by using human skeleton data without any expert rules. |
| URL | https://ieeexplore.ieee.org/document/8500131 |
| DOI | 10.1109/EIT.2018.8500131 |
| Citation Key | wu_machine_2018 |
- local nursing home
- Support vector machines
- Skeleton
- Scalability
- real-time systems
- pubcrawl
- privacy-aware compliance tracking system
- privacy
- patient care
- PACTS
- object detection
- nursing staffs baseline
- neural network
- Microsoft Kinect
- machine learning techniques
- machine learning
- Back
- lifting-pulling tasks
- learning (artificial intelligence)
- Injuries
- human skeleton data
- Human Factors
- Human activity prediction
- human activity detection
- high-level bending activities
- field data acquisition
- expert systems
- expert rules
- data privacy
- data acquisition
- body mechanics
- back-bending activities detection