# Biosignals Monitoring of First Responders for Cognitive Load Estimation in Real-Time Operation
Therefore, emergency situations in themselves can present a cognitive overload, due to the saturation of the working memory. During the last decade, new solutions have been emerging to provide FRs with technological tools and to improve their activities in emergency situations. Some of them focus on replicating activities in simulators or emulators, with the aim of training real activities with computer-based programs [28; 29] or virtual reality [30]. Regardless of the technology, as aforementioned, working memory is limited in both capacity and duration when dealing with novel information; but these limitations effectively disappear when working memory deals with information transferred from long-term memory. Thus, in stressful situations, the more information the FR has recorded in long-term memory by means of learning, the more capacity there will be in the working memory to deal with novel information related to the emergency. Some other approaches not focusing on training provide augmented senses to FRs in operation [31] (e.g., augmented vision, augmented information, real-time locations, auto-positioning, cognitive support, or increased communications between others). Most of these approaches rely on augmented reality (AR), because a lack of situational awareness is identified as one of the major challenges for supporting collaboration in emergencies [32]. However, the use of AR to increase sensations can influence CL in FRs [33]. Some researchers claim that when using AR, the success of a task is increased or made more likely through additional visual information being presented alongside the physical world [34]. However, the influence of AR on cognitive load has not been extensively investigated [35] and there are not many references on the emergency domain [33]. In these studies, the AR is only related to constructivist and learning approaches, not to the cognitive load. Unfortunately, although there has been a debate about whether AR increases CL [36], most studies report higher performance for participants using AR, but no evidence for cognitive overload compared to other conditions. Therefore, in this paper, under the European project RESCUER ([[https://rescuerproject.eu/](https://rescuerproject.eu/)]([https://rescuerproject.eu/](https://rescuerproject.eu/)), accessed on 12 June 2023), we designed a biosignals monitoring system to extract FRs' physical parameters and to infer their cognitive load in real time during operation. The system is designed to be autonomous in terms of communication, without the need to connect to an external server or cloud service. This is mandatory because of restrictions on emergency and disaster situations; the system cannot depend on having an external connection. Moreover, the system adapts to an AR framework that provides augmented information to the FRs and extracts biosignals information. These biosignals values will allow extraction of CL information and adjustment of the amount of information that FRs can safely assimilate, maintaining a compromise between the extra information provided and the capabilities to be acquired. The manuscript focuses on the design and development of a hardware and software framework, as well as its technical validation that: (i) allows real-time biosignals monitoring of FRs, (ii) analyzes the implication of spatial-temporal information provided in operation, and (iii) extracts information about the capability of information absorption helping or interfering in the tasks' execution. In the manuscript we perform a technical validation, but a longitudinal clinical study is relegated to a piloting period in real operation that must be synchronized with FRs' training maneuvers. The rest of the document is organized as follows. Section 2 describes the theoretical framework of biosignals measurement and cognitive load. Section 3 provides information about the sensors used in the framework and the system integration.