The use of precordial Doppler monitoring to prevent decompression sickness (DS) is well known by the scientific community as an important instrument for early diagnosis of DS. However, the timely and correct diagnosis of DS without assistance from diving medical specialists is unreliable. Thus, a common protocol for the manual annotation of echo Doppler signals and a tool for their automated recording and annotation are necessary. We have implemented original software for efficient bubble appearance annotation and proposed a unified annotation protocol. The tool auto-sets the response time of human “bubble examiners,” performs playback of the Doppler file by rendering it independent of the specific audio player, and enables the annotation of individual bubbles or multiple bubbles known as “showers.” The tool provides a report with an optimized data structure and estimates the embolic risk level according to the Extended Spencer Scale. The tool is built in accordance with ISO/IEC 9126 on software quality and has been projected and tested with assistance from the Divers Alert Network (DAN) Europe Foundation, which employs this tool for its diving data acquisition campaigns.

INTRODUCTION: Decompression sickness (DCS) is a complex and poorly understood systemic disease caused by inadequate desaturation after a decrease of ambient pressure. Strong variability between individuals is observed for DCS occurrence. This raises questions concerning factors that may be involved in the interindividual variability of DCS occurrence. This study aimed to experimentally assess the existence of heritable factors involved in DCS occurrence by selectively breeding individuals resistant to DCS from a population stock of Wistar rats.

Introduction: The popularity of SCUBA diving is steadily increasing together with the number of dives and correlated diseases per year. The rules that govern correct decompression procedures are considered well known even if the majority of Decompression Sickness (DCS) cases are considered unexpected confirming a bias in the "mathematical ability" to predict DCS by the current algorithms. Furthermore, little is still known about diving risk factors and any individual predisposition to DCS. This study provides an in-depth epidemiological analysis of the diving community, to include additional risk factors correlated with the development of circulating bubbles and DCS.

Introduction: There is a need to evaluate the influence of risk factors such as patency of foramen ovale (PFO) or “daredevil” psychological profile on contra-indication policy after a decompression sickness (DCS). Methods: By crossing information obtained from Belgian Hyperbaric Centers, DAN Emergency Hotline, the press, and Internet diving forums, it was possible to be accountable for the majority if not all DCS, which have occurred in Belgium from January 1993 to June 2013.

Drowning is the major cause of death in self-contained underwater breathing apparatus (SCUBA) diving. This study proposes an embedded system with a live and light-weight algorithm which detects the breathing of divers through the analysis of the intermediate pressure (IP) signal of the SCUBA regulator. A system composed mainly of two pressure sensors and a low-power microcontroller was designed and programmed to record the pressure sensors signals and provide alarms in absence of breathing. An algorithm was developed to analyze the signals and identify inhalation events of the diver. A waterproof case was built to accommodate the system and was tested up to a depth of 25 m in a pressure chamber.