Lora Cavuoto

TL;DR: The results show that the LASSO model performed well for both physical fatigue detection and modeling, and is not participant and/or workload regime specific and thus can be adopted for other applications.

TL;DR: The broad adoption of wearable technologies appears to depend largely on the scientific community’s ability to successfully address the identified barriers, and investigators may use the information provided to develop research studies that better address OSH practitioner concerns and help technology developers operationalize wearable sensors to improve employee health and well-being.

TL;DR: This method utilises the minimum amount of data and features from only one low-cost sensor to reliably classify the state of fatigue induced by a realistic manufacturing task using a simple machine learning algorithm that can be extended to real-time fatigue monitoring as a future technology to be employed in the manufacturing facilities.

TL;DR: A heuristic checklist for accessible smartphone interface design was developed through reviewing existing design standards and guidelines and validating these guidelines with user involvement, intended as a practical design support tool for use in early design phases of handheld products.

TL;DR: Anticipation and active engagement by the surgical team resulted in shorter operative time, and higher familiarity scores were associated with fewer inconveniences, and training efforts to increase anticipation and team familiarity can improve team efficiency.