Epidemiological studies in Latin America suggest indigenous people lack proper healthcare for musculoskeletal (MSK) and rheumatic diseases. Objectives This study aimed to estimate the prevalence of MSK disorders and rheumatic diseases in eight Latin American indigenous communities, and to identify which factors influence such prevalence using network analysis and syndemic approach. Methods This is a cross-sectional, community-based census study according to Community-Oriented Program for the Control of Rheumatic Diseases methodology. Individuals with MSK pain, stiffness or swelling in the past and/or during the last 7 days were evaluated by participating physicians. A descriptive, univariable and multivariable analysis was performed, followed by a network analysis. Results We surveyed 6155 indigenous individuals with a mean age of 41.2 years (SD 17.6; range 18–105); 3757 (61.0%) were women. Point prevalence in rank order was: low back pain in 821 (13.3%); osteoarthritis in 598 (9.7%); rheumatic regional pain syndromes in 368 (5.9%); rheumatoid arthritis in 85 (1.3%); undifferentiated arthritis in 13 (0.2%); and spondyloarthritis in 12 (0.1%). There were marked variations in the prevalence of each rheumatic disease among the communities. Multivariate models and network analysis revealed a complex relationship between rheumatic diseases, comorbidities and socioeconomic conditions. Conclusions The overall prevalence of MSK disorders in Latin American indigenous communities was 34.5%. Although low back pain and osteoarthritis were the most prevalent rheumatic diseases, wide variations according to population groups occurred. The relationship between rheumatic diseases, comorbidities and socioeconomic conditions allows taking a syndemic approach to the study.

We investigated calibration procedures of multiple Kinect sensors simultaneously. Through standard calibration algorithms our multi-Kinect system is accurately registered. We propose and implemented a multi-Kinect system to seamlessly render a scene from a wide range of angles. Such a system is capable of real-time operation. We also investigated the problem of inconsistent depth measurement between different Kinect units, and arrived at the same conclusion as the state-of-the-art regarding the characteristics of depth measurement errors in the Kinect sensor. In order to compensate these errors for live acquisition and display of multi-Kinect systems, we introduced an offline ICP calibration of multiple Kinect data. Our experimental results provide a robust way to properly align multiple Kinect data.