OBJECTIVE: Develop an advanced decision-support medical monitor driven by algorithms that provide real-time processing of physiologic signals for the purpose of guiding accurate fluid resuscitation in humans who are hypovolemic due to hemorrhaging. The algorithm will run in real time on a resource constrained portable device. The final device should provide a wireless connection between the patient and monitor, and the system should be capable of monitoring multiple patients simultaneously as well as forwarding clinical data to a central location. DESCRIPTION: Emergency medical treatment is imperative when time and distance limit quick casualty evacuation. Early intervention during the"golden hour"(the first 60 minutes following a traumatic injury) has long been recognized by medical personnel as vital to saving lives. Since hemorrhagic shock remains a leading cause of death on the battlefield (1), it is critical to provide medics with real time monitoring of soldiers with traumatic injuries and real-time fluid resuscitation support. Current fluid resuscitation strategies are based on standard vital signs, including blood pressure, heart rate and arterial saturation. We know from experience, however, that humans are unable to recognize subtle changes in these parameters until late in the course of ongoing blood loss (2-4). Inadequate resuscitation poses the risk of inadequate tissue perfusion and end organ damage. Conversely, overly aggressive fluid resuscitation may result in hemodilution of clotting factors resulting in coagulopathy (5,6), or elevated arterial blood pressure that can dislodge clots from vascular injuries (6), resulting in further blood loss and possibly death. How to best proceed when one is dealing with a multiple-injured patient who has a traumatic brain injury and exsanguinating hemorrhage can be especially difficult. A small portable device is needed that continuously evaluates an injured soldier"s hemodynamic status in a beat-to-beat fashion and periodically updates or alerts a medic if a change in the injured soldier"s clinical status is detected or an adjustment in IV fluid therapy is warranted. PHASE I: Demonstration of a proof-of-concept algorithm to provide moment-to-moment integration of standard vital signs or other novel physiological signals capable of tracking hemodynamic compensations due to alterations of central blood volume in humans during fluid resuscitation. Contractors should explore novel approaches for the analysis of physiological signals which can lead to the development an effective plan for real-time implementation. In Phase I, the algorithm will process, in near real time, continuous physiological signals related to alterations in central blood volume. The contractor is encouraged to explore novel physical signals, with the understanding that current non-invasive physiological signals such as the electrocardiogram (ECG), photoplethysmogram (PPG), oxygen saturation (SpO2), respiratory measures and blood pressure (BP) may provide a good starting point to derive the necessary physiological information. The algorithm will process one or more of the individual physiological signals and extract the necessary parameters to robustly determine the circulating blood volume status of an individual patient and how that individual is responding to fluid resuscitation. In order to accomplish this objective, the use of machine-learning techniques to implement the algorithm is encouraged. The successful algorithm will be required to process noisy physiological signals, while still maintaining robust performance in tracking fluid resuscitation during hemorrhaging. The contractor will be given access to a progressive hypovolemia data set produced at the US Army Institute for Surgical Research. Contractors are also encouraged to use other data sets relevant for the development of their fluid resuscitation algorithm. PHASE II: The contractor will further develop and optimize the resuscitation algorithm across various data sets. Optimization of the algorithm should utilize both simulated and actual trauma patient data. The contractor will integrate the algorithm software for tracking changes in central blood volume (i.e., hemorrhage severity detection and accurate resuscitation) in a real-time portable device. The device will display and archive the collected data. The device will be tested with both actual and simulated data sets. Evaluations of the system will encompass: data quality, real-time operation, performance measures, robustness, and consistency. PHASE III: The contractor will produce a working device capable of providing beat-to-beat real-time fluid resuscitation decision support to assist combat and civilian medics in fluid management and triage prioritization. The device should provide a wireless connection between the patient and monitor, and also be capable of monitoring multiple patients simultaneously. The final device must provide IEEE compliant wireless and a physical connector to allow connection to individual computers and computer networks. Such a device could save lives by providing critical information on hemorrhage, fluid resuscitation and triage priority. The device should be of great commercial interest for all branches of the U.S. armed services as well as pre-hospital and trauma centers around the world. The final device must provide IEEE compliant wireless and a physical connector to allow connection to individual computers and computer networks. Such a device could save lives by providing critical information on hemorrhage severity, and should be of great commercial interest for all branches of the U.S. armed services as well as civilian critical care professionals working in the pre-hospital transport setting and trauma centers around the world. REFERENCES: 1. Bellamy RF. The causes of death in conventional land warfare: implications for combat casualty care research. Mil Med 1984; 149:55-62. 2. Convertino VA, Ryan KL, Rickards CA, Salinas J, McManus JG, Cooke WH, Holcomb JB. Physiological and medical monitoring for en route care of combat casualties. J Trauma Supp, 2008; 64:S342-S353. 3. Cooke WH, Convertino VA. Heart rate variability and spontaneous baroreflex sequences: implications for autonomic monitoring during hemorrhage. J Trauma, 2005; 58:798-805. 4. Orlinsky M, Shoemaker W, Reis ED, Kerstein MD. Current controversies in shock and resuscitation. Surg Clin North Am 2001; 81:1217-1262. 5. Hirshberg A, Hoyt D, Mattox K. From"leaky buckets"to vascular injuries: Understanding models of uncontrolled hemorrhage. JACS. 2007; 204:665-72. 6. Blackbourne LH, Czarnik J, Mabry R, Eastridge B, Baer D, Butler F, et al. Decreasing killed-in-action and died-of-wounds rates in combat wounded. J Trauma. 2010; 69:S1-S4.