In this study, we investigated the correlation between the condition of drivers and their expiration using a spirometer and a volatile organic compound (VOC) gas sensor on a driving simulator. Twenty-four participants with normal or corrected-to-normal vision (11 males and 13 females; age range = 19−58 years, mean age = 39.3 years) were enrolled in this study. All participants were licensed drivers who reported driving more than one day per week and never participated in any lectures for motorsports. They were equipped with air-seal masks and transducers of the spirometer (Minato Medical Science AE-310S). The spirometer measured flow rate, oxygen and carbon dioxide concentrations for output to several parameters, such as tidal volume, respiration rate, oxygen consumption, carbon dioxide excretion, end tidal oxygen and carbo dioxide etc. The masks connected to a two-way valve for dividing between inhaled and exhaled breaths (Hans Rudolph series 2600) and a gas sensor chamber for a homemade gas sensor of Pt, Pd, and Au-loaded SnO2. Resistance signal of the gas sensor affected by concentrations of volatile organic compounds (VOCs), so that the gas sensor can monitor to fluctuation of VOCs in exhaled breath. They drove a fixed-base driving simulator (Mitsubishi Precision), which had an automatic transmission system and right-hand-drive and consisted of a cockpit with a steering wheel, an accelerator pedal, a brake pedal, a side brake lever, and a shift lever, as well as a liquid crystal monitor (70-inch) and speakers (for simulated noise of engine and tires). They drove in the overtaking lane at 90−100 km/h on four different courses of varying difficulty for approximately 5 minutes each. All courses include straight roads, right-curves, and left-curves. All curves were shallow (1000R) and sharp (200R), and the frequency of curves were infrequent and frequent (0.8 and 0.2 km straight road between curves). The mean and standard deviation (SD) of all breath parameters from them were calculated during the cruising section of the courses. After driving each course, they assessed the “enjoyment” and “difficulty” of the course on a scale of one to seven. The mean and SD of all parameters were analyzed using box-and-whisker plots and two-way analysis of variance (ANOVA). There was no significant difference in the correlation between the questionnaire result of “difficulty” and each parameter of the spirometer and gas sensor. Also, the mean of all breath parameter shows no significant difference to the questionnaire result of “difficulty” and “enjoyment”. By contrast, the low (1, 2, and 3 points) and high (5, 6, and 7 points) assessment groups of "enjoyment" showed large and small SDs of all parameters from the spirometer and the gas sensor, respectively. Specifically, in the highest course difficulty (C4), there was a clear tendency between the SDs and the assessment of “enjoyment”. The box-and whisker plots show the tendency. Two-way ANOVA shows p-values classified according to the assessment, courses and, their interaction. The p-values, used in statistical study, mean the significant difference of the parameter. The parameter possesses the significant differences when the p-values of the parameter is less than 0.05. On the two-way ANOVA between “enjoyment” and courses of SDs from all parameters, the “enjoyment” and the interaction showed high significant differences with less than 0.01 of p-values. No significant differences were observed from the courses, so that there is no dependency of the running course and only the assessment of “enjoyment” was effective. Moreover, no differences were found in comparison with the parameters from the spirometer and the gas sensor so that the condition of the driver could be evaluated objectively even when only one parameter was monitored.Ref. T. Itoh, T. Sato, T. Akamatsu, W. Shin, J. Breath Res. 2019, 14, 016003. Figure 1
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