Multicenter Data Sharing for Collaboration in Sleep Medicine

Clinical Sleep Research is an inherent multidisciplinary field, as many health issues may affect a person\´s sleep conditions and sleep disorders may cause several health problems. Many patients with chronic sleep disorders suffer from different further medical conditions - called multimorbidity. Due to the high variety of the reasons and the courses of sleep disorders, individual cases are difficult to compare. Therefore there is a high demand for sleep researchers to collaborate with each other to reach necessary participant numbers and multidisciplinary expertise. To date, inter-institutional sleep research is poorly supported by IT systems. In particular the heterogeneity and the quality variations within the acquired bio signal data - caused by different bio signal recorders or different measurement procedures - are impeding common bio signal data processing. In this manuscript we introduce a virtual research platform supporting inter-institutional data sharing and processing. The infrastructure is based on XNAT - a free and open-source neuroimaging research platform - a loosely coupled service oriented architecture and scalable virtualization in the backend. The system is capable of local pseudonymization of bio signal data, mapping to a standardized set of parameters and automatic quality assessment. Terms and quality measures are derived from the "Manual for the Scoring of Sleep and Associated Events" of the American Academy of Sleep Medicine, the de-facto standard for diagnostic bio signal analysis in sleep medicine.