Force weighting approach to calculate spinal cumulative loading for ergonomic workforce planning in production

For the prevention of musculoskeletal disorders (MSD), the evaluation of manual materials handling (MMH) is important. In this context, cumulative loading can be used as an exposure index for the ergonomic assessment of workplaces. However, it was shown in previous empirical studies that most existing methods for calculating cumulative loading fail to completely capture the resulting physiological effects of working conditions on human workers. Therefore, this contribution outlines the development and validation of a novel force weighted approach to calculated spinal cumulative loading that reflects the muscular exposure. Empirical data from 36 individuals were used as the data basis for deriving and validating the calculation method. The results of the validation show a high prediction quality on the basis of the hold-out method. Hence, the method provides relevant indicators for the ergonomic assessment of MMH activities. Thus, it might be a useful tool for workforce planning in production

User-centered design in mobile human-robot cooperation: consideration of usability and situation awareness in GUI design for mobile robots at assembly workplaces

Mobile cobots can increase the potential for assembly work in industry. For human-friendly automation of cooperative assembly work, user-centered interfaces are necessary. The design process regarding user interfaces for mobile human-robot cooperation (HRC) shows large research gaps. In this article an exemplary approach is shown to design a graphical user interface (GUI) for mobile HRC at assembly workplaces. The design is based on a wireframe developed to support situation awareness. An interactive mockup is designed and evaluated. This is done in two iterations. In the first iteration, a user analysis is carried out using a quantitative survey with n = 31 participants to identify preferred input modalities and a qualitative survey with n = 11 participants that addresses touch interfaces. The interactive mockup is developed by implementing design recommendations of the usability standards ISO 9241 – 110, 112 and 13. A heuristic evaluation is conducted with n = 5 usability experts and the measurement of situation awareness with n = 30 end users. In the second iteration, findings from the preceding iteration are implemented in the GUI and a usability test with n = 20 end users is conducted. The process demonstrates a combination of methods that leads to high usability and situation awareness in mobile HRC

Künstliche Intelligenz in der Forschung

Dieses Buch ist eine Open Access Publikation. Der lange gehegte Traum von künstlicher Intelligenz (KI) wird in unserer Alltagswelt zunehmend Realität. Damit verbinden sich hohe gesellschaftliche Erwartungen, aber auch Sorgen hinsichtlich einer schleichenden Entmündigung des Menschen. Am Beispiel des Forschungssektors lotet dieser Band die Optionen, Entwicklungschancen und Risiken von KI-Techniken für die Zukunft des wissenschaftlichen Erkenntnisprozesses und der darauf beruhenden technischen Entwicklungen aus. Zu diesem Zweck wird zunächst der Stand der KI-Technik und ihrer Anwendungen dargestellt. Es folgen wissenschaftsphilosophische Untersuchungen zur Frage der Ersetzbarkeit des forschenden Menschen durch KI und zu erwartenden Veränderungen in der wissenschaftlichen Forschung. Weitere Abschnitte widmen sich den Folgen für die Arbeitswelt von Forschern/Forscherinnen sowie den durch KI erzeugten neuen Herausforderungen für die rechtliche Regulierung im Spannungsfeld von Wissenschaftsfreiheit und Datenschutz. Der Band schließt mit Empfehlungen für die verantwortlichen Akteure in Wissenschaft, Forschungspolitik und Gesellschaft aus interdisziplinärer Perspektive

Mild-to-Moderate Kidney Dysfunction and Cardiovascular Disease: Observational and Mendelian Randomization Analyses

BACKGROUND: End-stage renal disease is associated with a high risk of cardiovascular events. It is unknown, however, whether mild-to-moderate kidney dysfunction is causally related to coronary heart disease (CHD) and stroke. METHODS: Observational analyses were conducted using individual-level data from 4 population data sources (Emerging Risk Factors Collaboration, EPIC-CVD [European Prospective Investigation into Cancer and Nutrition-Cardiovascular Disease Study], Million Veteran Program, and UK Biobank), comprising 648 135 participants with no history of cardiovascular disease or diabetes at baseline, yielding 42 858 and 15 693 incident CHD and stroke events, respectively, during 6.8 million person-years of follow-up. Using a genetic risk score of 218 variants for estimated glomerular filtration rate (eGFR), we conducted Mendelian randomization analyses involving 413 718 participants (25 917 CHD and 8622 strokes) in EPIC-CVD, Million Veteran Program, and UK Biobank. RESULTS: There were U-shaped observational associations of creatinine-based eGFR with CHD and stroke, with higher risk in participants with eGFR values 105 mL·min-1·1.73 m-2, compared with those with eGFR between 60 and 105 mL·min-1·1.73 m-2. Mendelian randomization analyses for CHD showed an association among participants with eGFR 105 mL·min-1·1.73 m-2. Results were not materially different after adjustment for factors associated with the eGFR genetic risk score, such as lipoprotein(a), triglycerides, hemoglobin A1c, and blood pressure. Mendelian randomization results for stroke were nonsignificant but broadly similar to those for CHD. CONCLUSIONS: In people without manifest cardiovascular disease or diabetes, mild-to-moderate kidney dysfunction is causally related to risk of CHD, highlighting the potential value of preventive approaches that preserve and modulate kidney function

Mild-to-Moderate Kidney Dysfunction and Cardiovascular Disease: Observational and Mendelian Randomization Analyses

BACKGROUND: End-stage renal disease is associated with a high risk of cardiovascular events. It is unknown, however, whether mild-to-moderate kidney dysfunction is causally related to coronary heart disease (CHD) and stroke. METHODS: Observational analyses were conducted using individual-level data from 4 population data sources (Emerging Risk Factors Collaboration, EPIC-CVD [European Prospective Investigation into Cancer and Nutrition-Cardiovascular Disease Study], Million Veteran Program, and UK Biobank), comprising 648 135 participants with no history of cardiovascular disease or diabetes at baseline, yielding 42 858 and 15 693 incident CHD and stroke events, respectively, during 6.8 million personyears of follow-up. Using a genetic risk score of 218 variants for estimated glomerular filtration rate (eGFR), we conducted Mendelian randomization analyses involving 413 718 participants (25917 CHD and 8622 strokes) in EPIC-CVD, Million Veteran Program, and UK Biobank. RESULTS: There were U-shaped observational associations of creatinine-based eGFR with CHD and stroke, with higher risk in participants with eG FR values 105 mL.min(-1).1.73 m(-2), compared with those with eG FR between 60 and 105 mL.min(-1).1.73 m(-2). Mendelian randomization analyses for CHD showed an association among participants with eGFR 105 mL.min(-1).1.73 m(-2). Results were not materially different after adjustment for factors associated with the eGFR genetic risk score, such as lipoprotein(a), triglycerides, hemoglobin Alc, and blood pressure. Mendelian randomization results for stroke were nonsignificant but broadly similar to those for CHD. CONCLUSIONS: In people without manifest cardiovascular disease or diabetes, mild-to-moderate kidney dysfunction is causally related to risk of CHD, highlighting the potential value of preventive approaches that preserve and modulate kidney function