Exploring the challenges and risks of dead body handling faced by healthcare professionals during the coronavirus pandemic: Cross sectional survey study.

The coronavirus pandemic shocked the already overwhelmed global healthcare system, challenging its preparedness to deal with mass fatalities. Our research examines the safety issues faced by healthcare workers when handling dead (deceased) bodies, highlighting the need for better strategies in the event of mass fatalities. Healthcare providers involved in dead body handling during the COVID-19 pandemic in the U.S. were eligible to participate in our study. Using a web-based survey, we analyzed responses of 206 participants across 43 U.S. states. We used the Systems Engineering Initiative for Patient Safety (SEIPS) framework to deduce themes from participants' open-ended responses. The study showed how routine tasks become extraordinarily challenging during pandemic due to increased workload, emotional stress, and resource constraints. Tasks such as lifting and transferring bodies, underscored physical and emotional toll on workers. The mental strain induced by mass fatalities and the complexities of communicating with families and peers were also prominent, adding to the overall burden on healthcare workers. The participants emphasized the importance of specialized training, policy refinements, and improvements in its implementation. In conclusion, our study contributes to understanding the complexities of dead body handling during a pandemic. It underscores the need for emergency response planning and systemic changes in healthcare policies and practices to ensure the safety and well-being of healthcare workers engaged in these critical tasks.

Inertial Motion Capture-Based Whole-Body Inverse Dynamics.

Inertial Motion Capture (IMC) systems enable in situ studies of human motion free of the severe constraints imposed by Optical Motion Capture systems. Inverse dynamics can use those motions to estimate forces and moments developing within muscles and joints. We developed an inverse dynamic whole-body model that eliminates the usage of force plates (FPs) and uses motion patterns captured by an IMC system to predict the net forces and moments in 14 major joints. We validated the model by comparing its estimates of Ground Reaction Forces (GRFs) to the ground truth obtained from FPs and comparing predictions of the static model's net joint moments to those predicted by 3D Static Strength Prediction Program (3DSSPP). The relative root-mean-square error (rRMSE) in the predicted GRF was 6% and the intraclass correlation of the peak values was 0.95, where both values were averaged over the subject population. The rRMSE of the differences between our model's and 3DSSPP predictions of net L5/S1 and right and left shoulder joints moments were 9.5%, 3.3%, and 5.2%, respectively. We also compared the static and dynamic versions of the model and found that failing to account for body motions can underestimate net joint moments by 90% to 560% of the static estimates.