ABSTRACT
Despite the increasing degree of automation in industry, manual or semi-automated are commonly and inevitable for complex assembly tasks. The transformation to smart processes in manufacturing leads to a higher deployment of data-driven approaches to support the worker. Upcoming technologies in this context are oftentimes based on the gesture-recognition, − monitoring or–control. This contribution systematically reviews gesture or motion capturing technologies and the utilization of gesture data in the ergonomic assessment, gesture-based robot control strategies as well as the identification of COVID-19 symptoms. Subsequently, two applications are presented in detail. First, a holistic human-centric optimization method for line-balancing using a novel indicator–ErgoTakt–derived by motion capturing. ErgoTakt improves the legacy takt-time and helps to find an optimum between the ergonomic evaluation of an assembly station and the takt-time balancing. An optimization algorithm is developed to find the best-fitting solution by minimizing a function of the ergonomic RULA-score and the cycle time of each assembly workstation with respect to the workers' ability. The second application is gesture-based robot-control. A cloud-based approach utilizing a generally accessible hand-tracking model embedded in a low-code IoT programming environment is shown. © 2022 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group.
ABSTRACT
BACKGROUND: The Corona pandemic and ongoing mass vaccinations raise the question of the nocebo mechanisms involved. Since immunization is usually administered to healthy people as a preventive health measure, adverse events (AE) following immunization are less accepted and could contribute to vaccine hesitancy. Assuming that vaccinees experience nocebo responses, the aim of this meta-analysis was to investigate the effect sizes of solicited adverse events (or assumed reactogenicity) reported in placebo groups in RCTs on seasonal influenza vaccination. METHODS: Literature search via PubMed, Web of Science, and CENTRAL was conducted considering gray literature. Only RCTs with placebo groups using pharmacologically inert substances (like saline) were included. Quality was assessed using Cochrane Collaboration's Risk of Bias Tool. Effect sizes were estimated using a random mixed effects model based on k = 31 studies covering 14,326 participants in placebo groups. RESULTS: Reported solicited AEs in placebo groups showed significant effect sizes of proportions (ESp). In k = 13 analyzed placebo groups, 35 % of the participants reported at least one solicited systemic AE (p = 0.007). The most common particular solicited systemic AEs were headache (k = 27; 17 %; p = 0.001), malaise (k = 13; 12 %; p = 0.004), and hyperhidrosis (k = 4; 12 %; p < 0.001) within one week after vaccination. CONCLUSION: The results show significant solicited AEs in placebo groups, indicating substantial nocebo responses after vaccination. Based on the fact that most vaccination programs include similar groups of healthy people, we expect that comparable nocebo effects occur during other campaigns. Health care professionals should be aware of the nocebo response and take action to prevent or decrease the burden of adverse events following immunization. Fear of side effects must be addressed early in order to diminish vaccine hesitancy. Prospero identifier: CRD42020156287, October 2019.
ABSTRACT
Background: Due to immunosuppressive oncologic therapy patients are at risk for infections. In case of COVID-19, patients have a high risk even to die due to this infection, especially when they have a progressive disease. But also dose-reductions, -modifications or postponing of chemotherapy cycles result in disease-progression and are associated with early deaths (1,2). In this study we offer patients at risk user-friendly technologies for transmitting biosignal-data and patient reported outcome monitoring (PROM) data for early detection of infections. Method(s): We designed a monocenter prospective cohort study using PROM via app and remote monitoring via photoplethysmography (PPG). The application of these technologies enables an early detection of infections and therefore initiation of medical interventions. The study is conducted as feasibility analysis;primary endpoints are adherence (according to wearing time) and technical robustness. Result(s): We expect study results in 4th quarter 2022. Discussion(s): The applied user friendly technologies can be used in the out-patient setting for transmission of biodata and symptoms;but also for a better communication between patients and physicians. This results in medical interventions at an early stage for treatment of infections. This study is conducted in a cooperation with the department of cardiology, using the infrastructure of the TUM telemedicine-center. Long-term objective ist to establish an expandable remote-monitoring infrastructure for the public health sector. Conclusion(s): By the use of remote-monitoring and PROM, we obtain an increase in safety for cancer patients undergoing immunosuppressive oncologic therapy during COVID-19 pandemia.