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Surface electrogastrography (EGG) is a non-invasive technique that is used to record myoelectrical activity of the stomach using cutaneous electrodes placed on the abdomen. Gastric motility assessment by EGG is a candidate for standard clinical procedure based on the quantification of parameters characteristic of gastric motility disorders. Despite its noticeable benefits, EGG is not widely implemented in clinical practice. The main reasons are: (1) lack of standardization of electrode placement, (2) time-consuming diagnostic procedures and (3) a complex multi-channel recording setup. We proposed a methodology in which an easy-to-use single-channel EGG, with a less time-consuming protocol (<1 h), would provide sufficient information for gastric motility assessment. Recordings from the three anatomical landmarks in 20 healthy young subjects were compared under two conditions, fasting and postprandial by evaluating the dominant frequency (DF). Our results showed that there is a statistically significant increase of DF after meal ingestion (p<0.05) in each of the three channels. However, when the study group was divided into two subgroups based on body mass index (BMI), the most appropriate recording location was above the body of the stomach (according to statistical significance p=7.82×10−6). We showed that a less time-consuming recording session with light meal intake could be used for the assessment of gastric myoelectrical activity (GMA).

In the era of technological advances and innovations in transportation technologies, application of driving simulators for the investigation and assessment of the driving process provides a safe and suitable testing environment. Although driving simulators are crucial for further improvements in transportation, it is important to resolve one of their main disadvantages–simulator sickness. Therefore, suitable methods for the assessment of simulator sickness are required. The main aim of this paper was to present a non-invasive method for assessing simulator sickness by recording gastric myoelectrical activity–electrogastrography. Open-source hardware for electrogastrography together with recordings obtained in 13 healthy volunteers is presented, and the main aspects of signal processing for artifact cancellation and feature extraction were discussed. Based on the obtained results, it was concluded that slow-wave electrical gastric activity can be recorded during driving simulation by following adequate recommendations and that proposed features could be beneficial in describing non-ordinary electrogastrography signals.