Bangaru, S S (2021) Fatigue monitoring through wearable sensors for construction workers. PhD thesis, Louisiana State University and Agricultural & Mechanical College, USA.
Abstract
About 40% of the US construction workforce experiences high-level fatigue, which leads to poor judgment, increased risk of injuries, a decrease in productivity, and a lower quality of work. Excessive fatigue from working in unpleasant working conditions, long working hours, or heavy workloads can aggravate fatigue's adverse effects, leading to work-related musculoskeletal disorders (WMSDs) and productivity loss. Therefore, it is essential to monitor fatigue to reduce the adverse effects and preventing long-term health problems. However, since fatigue demonstrates itself in several complex processes, there is no single standard measurement method for fatigue detection. This research aims to develop a system for continuous workers' fatigue monitoring by predicting aerobic fatigue threshold (AFT) according to forearm muscle activity and motion data. The forearm muscle activity and motion data were acquired using a low-cost, non-invasive, wearable sensor. The proposed fatigue monitoring system consists of multiple measurable frameworks with five objectives: (1) assess the data quality and reliability of forearm motion and muscle activity data, (2) develop and validate the construction workers' activity recognition framework, (3) estimate construction activity-specific maximum aerobic capacity, (4) develop and validate continuous oxygen uptake prediction framework, and (5) develop fatigue level classifier using AFT features and validate the proposed fatigue monitoring system. The proposed system was evaluated on the participants performing fourteen scaffold building activities. The results show that the AFT features have achieved a higher accuracy of 92. 31% in assessing the workers' fatigue level compared to heart rate (51. 28%) and percentage heart rate reserve (50. 43%) features. Moreover, the overall performance of the proposed fatigue monitoring system on unseen data using average 2-min AFT features was 76. 74%. The study validates the feasibility of using forearm muscle activity and motion data to monitor the workers' fatigue level continuously. The performance of the proposed system shows some promising potentials that it can be applied on the construction field to help assess worker's physiological status, evaluate the physical workload of the activity, quantify the direct impacts of the fatigue level on the accidents, and enhance the workers' safety, health, and productivity through early detection of risk.
| Item Type: | Thesis (Doctoral) |
|---|---|
| Thesis advisor: | Wang, C |
| Uncontrolled Keywords: | accuracy; construction activity; fatigue; measurement; measurement method; monitoring; productivity; reliability; safety; sensors; workforce; working conditions; working hours |
| Index terms: | working conditions, workload, construction worker, measurement method, judgment, wearable sensor, heart, monitoring, working hours, estimate, productivity, accuracy, activity recognition, fatigue, injury, construction activity |
| Subjects: | financial and cost management, health conditions and diseases, practitioner, modelling and simulation, computer vision, professional development, medical science and clinical practice, dispute resolution, construction operations, control systems, employment law, management |
| Topics: | Legal Issues, Information Management, Cost Management, Health and Safety, Design Practice, Site Management, Business Strategy, Human Resources, Digital Applications, Roles and Professions |
| Descriptive scope: | 2 PC |
N.B. Descriptive scope is a count of how many of the five facets of empirical research are indicated by the words used in title, abstract and keywords. It is not intended as a judgement on the research; merely a count of the kind of word we would expect to indicate Phenomenon, Concepts, Theoretical framing, Empirical techniques, Analytical techniques. If all five are present, then a code of “5 PCTEA” will indicate this. If you feel the coding for this record is questionable, we welcome discussion around the terms we matched or the way we categorized them. The facet you would expect may not be coded, or a facet may be coded inappropriately. This can also bear on a larger question, of which facets should be treated as defining in construction management research. Please get in touch, and we will look at it. More details here