Lessons Learned: Gastric Motility Assessment During Driving Simulation
- Is it possible to reliably acquire slow-wave activity using a custom-made EGG sensing system during driving simulation?
- What EGG parameters are suitable for the analysis of recorded signals and, is there a correlation between them and subjective sickness assessment?
- Is there a clear difference in signals for resting, and the motion and no-motion drive?
2.2. EGG Sensing System
2.3. Driving Simulator
- reference electrode—tissue covering the iliac crest;
- common electrode—on the stomach, 8 cm straight above the navel;
- channel 1 electrode—8 cm left of the common electrode inclined by 20 degrees from the line that connects the navel and the sternum;
- channel 2 electrode—8 cm left of the common electrode inclined by 55 degrees from the line that connects the navel and the sternum;
- channel 3 electrode—8 cm left of the common electrode inclined by 90 degrees from the line that connects the navel and the sternum.
- Test drive—in order to enable participants to become familiar with the driving simulator operation (~ 5 min);
- Resting sequence—baseline slow-wave activity before driving simulation was recorded (~ 5 min);
- Drive with motion—driving simulation with haptic feedback included (~ 5 min);
- Drive without motion—driving simulation with no haptic feedback (~ 5 min).
2.5. EGG Analysis
2.5.1. Motion Artifact Cancellation
- automatic selection of a channel that was least affected by artifacts, and
- manual cancellation of the remaining artifacts on the chosen channel.
2.5.2. Feature Extraction
- Drop-out due to severe nausea and anxiety symptoms (in one subject);
- Severe artifacts present in the signal, most probably due to the electrodes detachment and movements (in three subjects).
4.1. Lessons Learned: Open-Source EGG
4.2. Lessons Learned: Protocol
- Firstly, subject’s movements can cause erroneous EGG, so body movements should be carefully controlled when recording EGG in a dynamic environment, such as driving simulation with haptic feedback.
- Secondly, EGG could be affected by the posture as stated in . Although the supine position is more preferable than the sitting position, the results presented in  showed that successful EGG assessment can be performed in the sitting position. We assumed that the posture did not significantly affect our recordings.
- Thirdly, we faced a problem with electrode detachment in two study participants, which caused the drop-out of those two subjects. Hence, we propose the application of an additional protective layer of adhesive bandage over the surface electrodes.
4.3. Lessons Learned: Channel Selection
4.4. Lessons Learned: Artifact Cancellation
4.5. Lessons Learned: Feature Extraction
4.6. Lessons Learned: Haptic Feedback in Relation to SS
4.7. Lessons Learned: Qualitative and Quantitative Nausea Assessment
- ID4 after driving with motion,
- ID5 after driving with motion, and
- ID9 after both driving with and without motion.
- Recording of EGG during driving simulation is possible using our custom-made open-source device with careful considerations regarding recording setup and the protocol. Despite that, its effectiveness for SS assessment is yet to be shown.
- RMS values might be used for the estimation of amplitude variations in EGG signals. Correlation between RMS and nausea should be examined in a future study. MF, CF, and DF could be used for the assessment of the EGG spectrum. In order to confirm these findings, future study should be performed on a larger sample.
- There was no clear difference between resting, motion, and no-motion sequences, except for an increase in RMS for driving sessions compared to resting.
- EGG under dynamic conditions should be recorded by carefully following protocol recommendations and the application of more than one EGG channel.
- The resting sequence of EGG recording should be obtained prior to any simulator activity.
- EGG signals should be visually examined in order to detect and manually extract motion artifacts.
- Features for a description of frequency content (DF, MF, and CF) should be carefully examined prior to any conclusions.
- Further improvement of the EGG device, primarily realization on a PCB with consideration regarding filter design.
- Assessment of nausea on a larger study group with higher statistical power in order to divide subjects into nausea and non-nausea groups. For the selection of target population, it could be beneficial to use a Motion Sickness Susceptibility Questionnaire to estimate susceptibility to suffer from SS.
Conflicts of Interest
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|Subject||Age [years]||Sex [F-Female, M-Male]||Height [cm]||Weight [kg]||Driving Experience [years]||Driving Simulator Experience [Yes/No]|
|Amplification||LP Filtering||HP Filtering|
|Instrumentation amplifier||Rg||Operational amplifier||Rlp||Clp||Operational amplifier||Rhp||Chp|
|INA114BP||50 Ω||TL072CP||15 kΩ||2.2 µF||TL072CP||10 MΩ||1 µF|
|Subject||Resting||No-Motion Drive||Motion Drive|
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Popović, N.B.; Miljković, N.; Stojmenova, K.; Jakus, G.; Prodanov, M.; Sodnik, J. Lessons Learned: Gastric Motility Assessment During Driving Simulation. Sensors 2019, 19, 3175. https://doi.org/10.3390/s19143175
Popović NB, Miljković N, Stojmenova K, Jakus G, Prodanov M, Sodnik J. Lessons Learned: Gastric Motility Assessment During Driving Simulation. Sensors. 2019; 19(14):3175. https://doi.org/10.3390/s19143175Chicago/Turabian Style
Popović, Nenad B., Nadica Miljković, Kristina Stojmenova, Grega Jakus, Milana Prodanov, and Jaka Sodnik. 2019. "Lessons Learned: Gastric Motility Assessment During Driving Simulation" Sensors 19, no. 14: 3175. https://doi.org/10.3390/s19143175