Motion coordination control of planar 5R parallel quadruped robot based on SCPL-CPG

The parallel leg of the quadruped robot has good structural stiffness, accurate movement, and strong bearing capacity, but it is complicated to control. To solve this problem, a series connection of parallel legs (SCPL) was proposed, as well as a control strategy combined with the central pattern generator (CPG). With the planar 5R parallel leg as the research object, the SCPL analysis method was used to analyze the leg structure. The topology of CPG network was built with the Hopf oscillator as the unit model, and the CPG was the core to model the robot control system. By continuously adjusting the parameters in the CPG control system and changing the connection weight, and the smooth transition between gaits was realized. The simulation results show that the SCPL analysis method can be effectively used in the analysis of parallel legs, and the control system can realize the smooth transition between gaits, which verifies the feasibility and effectiveness of the proposed control strategy.

The impact of intensive care unit physician staffing change at a community hospital

Objectives: A high-intensity staffing model has been defined as either mandatory intensivist consultation or a closed intensive care unit in which intensivists manage all aspects of patient care. In the current climate of limited healthcare resources, transitioning to a closed intensive care unit model may lead to significant improvements in patient care and resource utilization. Methods: This is a single-center, retrospective cohort study of all mechanically ventilated intensive care unit admissions in the pre-intensive care unit closure period of 1 October 2014 to 30 September 2015 as compared with the post-intensive care unit closure period of 1 November 2015 to 31 October 2016. Patient demographics as well as outcome data (duration of mechanical ventilation, length of stay, direct costs, complications, and mortality) were abstracted from the electronic health record. All data were analyzed using descriptive and inferential statistics. Regression analyses were used to adjust outcomes for potential confounders. Results: A total of 549 mechanically ventilated patients were included in our analysis: 285 patients in the pre-closure cohort and 264 patients in the post-closure cohort. After adjusting for confounders, there was no significant difference in mortality rates between the pre-closure (40.7%) and post-closure (38.6%) groups (adjusted odds ratio = 0.82; 95% confidence interval = 0.56–1.18; p = 0.283). The post-closure cohort was found to have significant reductions in duration of mechanical ventilation (3.71–1.50 days; p < 0.01), intensive care unit length of stay (5.8–2.7 days; p < 0.01), hospital length of stay (10.9–7.3 days; p < 0.01), and direct hospital costs (US $16,197–US $12,731; p = 0.009). Patient complications were also significantly reduced post-intensive care unit closure. Conclusion: Although a closed intensive care unit model in our analysis did not lead to a statistical difference in mortality, it did demonstrate multiple beneficial outcomes including reduced ventilator duration, decreased intensive care unit and hospital length of stay, fewer patient complications, and reduced direct hospital costs.

Adaptive Walking Control for a Quadruped Robot on Irregular Terrain Using the Complex-Valued CPG Network

In this paper, we propose a CPG (central pattern generator) network control system using motor dynamics for the gait planning of a quadruped robot with a trot walking pattern to climb up and down a slope and turn back and follow the symmetry of route. The CPG unit model, which includes two DC motors model, has the ability to generate the periodic joint angle with complex-value parameters. Through plural feedback parameters, the CPG network can adjust the frequency and amplitude of an internal neuron model such as a robot meeting an irregular surface of a road. Using the stride length and frequency of robot joint angles, the distance of walking with a trot pattern can be calculated. In order to confirm the validity of the proposed control system, a quadruped robot is produced to implement the adaptive walking system.

Impact of staffing model conversion from a mandatory critical care consultation model to a closed unit model in the medical intensive care unit

Background The intensive care unit (ICU) staffing model affects clinical outcomes of critically ill patients. However, the benefits of a closed unit model have not been extensively compared to those of a mandatory critical care consultation model. Methods This retrospective before-after study included patients admitted to the medical ICU. Anthropometric data, admission reason, Acute Physiology and Chronic Health Evaluation II score, Eastern Cooperative Oncology Group grade, survival status, length of stay (LOS) in the ICU, duration of mechanical ventilator care, and occurrence of ventilator-associated pneumonia (VAP) were recorded. The staffing model of the medical ICU was changed from a mandatory critical care consultation model to a closed unit model in September 2017, and indices before and after the conversion were compared. Results A total of 1,526 patients were included in the analysis. The mean age was 64.5 years, and 954 (62.5%) patients were men. The mean LOS in the ICU among survivors was shorter in the closed unit model than in the mandatory critical care consultation model by multiple regression analysis (5.5 vs. 6.7 days; p = 0.005). Central venous catheter insertion (38.5% vs. 51.9%; p < 0.001) and VAP (3.5% vs. 8.6%; p < 0.001) were less frequent in the closed unit model group than in the mandatory critical care consultation model group. After adjusting for confounders, the closed unit model group had decreased ICU mortality (adjusted odds ratio 0.65; p < 0.001) and shortened LOS in the ICU compared to the mandatory critical care consultation model group. Conclusion The closed unit model was superior to the mandatory critical care consultation model in terms of ICU mortality and LOS among ICU survivors.