Non-invasive detection of mental fatigue in construction equipment operators through geometric measurements of facial features.

INTRODUCTION: Prolonged operation of construction equipment could lead to mental fatigue, which can increase the chances of human error-related accidents as well as operators' ill-health. The objective detection of operators' mental fatigue is crucial for reducing accident risk and ensuring operator health. Electroencephalography, photoplethysmography, electrodermal activity, and eye-tracking technology have been used to mitigate this issue. These technologies are invasive and wearable sensors that can cause irritation and discomfort. Geometric measurements of facial features can serve as a noninvasive alternative approach. Its application in detecting mental fatigue of construction equipment operators has not been reported in the literature. Although the application of facial features has been widespread in other domains, such as drivers and other occupation scenarios, their ecological validity for construction excavator operators remains a knowledge gap. METHOD: This study proposed employing geometric measurements of facial features to detect mental fatigue in construction equipment operators' facial features. In this study, seventeen operators performed excavation operations. Mental fatigue was labeled subjectively and objectively using NASA-TLX scores and EDA values. Based on geometric measurements, facial features (eyebrow, mouth outer, mouth corners, head motion, eye area, and face area) were extracted. RESULTS: The results showed that there was significant difference in the measured metrics for high fatigue compared to low fatigue. Specifically, the most noteworthy variation was for the eye and face area metrics, with mean differences of 45.88% and 26.9%, respectively. CONCLUSIONS: The findings showed that geometrical measurements of facial features are a useful, noninvasive approach for detecting the mental fatigue of construction equipment operators.

The use of mobile health technology in the management of osteoarthritis: A scoping review with scientometric analyses.

INTRODUCTION: Although mHealth technology is an emerging approach for enabling self-management/education of hip/knee osteoarthritis (OA) that may reduce burdens in primary and secondary care, no scoping review has been conducted to comprehensively review the scope of mHealth technology in managing hip/knee OA. This scoping review and scientometric analyses aimed to summarize the current state of research on the use of mHealth technology (mobile applications/web-based interventions) for self-management/education of adults with hip/knee OA, identify key research activities, and provide future directions on the development/usage of mHealth technology. METHODS: The Arksey and O'Malley methodological framework was employed, augmented with scientometric analyses. Six databases were searched from inception to 31 May 2021. Findings were reported according to the PRISMA extension for scoping review. Co-word, co-author, and co-citation scientometric analyses were conducted to examine the social and intellectual connections of the research field (e.g., research hotspots and researcher collaborations). RESULTS: Twenty mHealth programs for promoting self-management of hip/knee OA were identified. The programs mainly included exercises or directives on performance of exercises. Compared to no interventions, mHealth technology was usable and might be more effective in improving pain, physical function, and quality of life in individuals with OA. The scientometric analyses identified multiple co-occurring keywords that reflected conceptual properties of this research domain. Although some intellectual connections among authors, research articles, and journals were noted, there were insufficient international collaborations in this field. DISCUSSION: While individual small-scale studies highlighted promising short-term effects of mHealth technology in self-managing hip/knee OA, many mHealth technologies were developed without clinicians' and/or patients' contributions. Future mHealth programs should be developed based on a strong theoretical background and professional inputs. The long-term benefits and cost-effectiveness of mHealth technologies, user experience, as well as cross-cultural adaptation of these technologies should be evaluated.