We are conducting human trials utilizing VR technology to induce motion sickness, enabling us to study its physiological effects in a controlled environment. During these trials, we collect pre- and post-exposure biological samples, including saliva and breath, to identify any chemical changes associated with motion sickness. Additionally, we perform pre- and post-exposure balance tests and administer detailed questionnaires to participants to assess their motion sickness symptoms. This comprehensive approach allows us to correlate biological markers with self-reported and observed symptoms, advancing our understanding of motion sickness and informing the development of our sensor technology for self-driving vehicles.

After gathering the data from our human trials, we will analyze it to identify specific biomarkers associated with motion sickness, focusing particularly on volatile compounds. Using advanced methods such as mass spectrometry, we aim to detect and quantify these compounds in the collected saliva and breath samples. This detailed analysis will help us pinpoint the chemical changes that occur during motion sickness, providing critical insights for developing our motion sickness sensor for self-driving vehicles.

In the data analysis phase, we meticulously compare the pre- and post-exposure results from all collected data to determine if participants experienced motion sickness and identify which compounds were produced. By plotting these compounds against one another, we visualize the changes and correlations, enabling us to pinpoint specific biomarkers associated with motion sickness. This thorough analysis not only validates our findings but also enhances our understanding of the physiological processes involved, guiding the further development of our motion sickness sensor for self-driving vehicles.

Upon obtaining significant results in the testing and analysis phases, particularly in identifying volatile compounds associated with motion sickness, we will begin the development of a sensor tailored for self-driving cars. This sensor will be designed to detect the presence of specific biomarkers in real-time, using advanced technology capable of monitoring and analyzing breath and environmental conditions within the vehicle. By integrating this sensor into the autonomous vehicle system, we aim to provide early warnings of motion sickness, allowing for immediate adjustments to driving patterns or passenger alerts. This innovation will enhance passenger comfort and safety, addressing a critical challenge in the adoption of self-driving technology.