Blast injury model estimates from multiple overpressure measurement locations on a single person-borne device

Towards a better characterization of the increasing blast overpressure threat, person-borne sensors are being considered for large military population segments potentially subjected to explosive blast and firing of crew served weapons. Training and field data, tracked longitudinally across a soldier’s entire career, can help with the diagnosis of blast injuries and the improvement of standard operating procedures for both explosive forced entry and large weapons firing. However, a current challenge with person-born blast dosimeters resides with the position of the overpressure sensors themselves. Often, the sensors are not fully exposed to the blast locally, resulting in pressure measurements not representative of the blast conditions surrounding an individual. While fielding multiple individual and uncoupled dosimeter units around the body increases the likeliness of catching the representative blast exposure, issues arise from differences in internal clock, potential partial triggering, and the complexity of merging data from different sources. Instead, integrating multiple overpressure sensors pointing in different directions, within a single device that captures and records all data simultaneously, proves highly beneficial for data analysis and interpretation. This paper presents algorithms that combine the overpressure data collected from such multiple coupled sensors for each blast event to minimize the effect of blast directionality. In particular, an algorithm estimating the equivalent side-on blast overpressure is presented, facilitating injury estimates from existing established blast injury models adapted for the outputs from the blast dosimeters. An algorithm is also presented that estimates the orientation or provenance of an explosive blast relative to the soldier.