A method for testing the effect of indoor co2 concentration and temperature interaction on human cognition

Abstract

The application discloses a kind of indoor CO2 concentration and temperature interaction influence on human cognition test method, belong to indoor environment control field, mainly include: screening tester participating in experiment;Exposure environment construction: prepare environment cabin and set experimental condition, the experimental condition includes: set different CO2 concentration level, set different temperature level;Cognitive performance measurement: in exposure environment, different types of cognitive task test are carried out, and subjective response, physiological parameter and electroencephalogram are measured;Measurement data analysis: the measurement data under different types of cognitive tasks are processed, and the sensitivity of different types of cognitive tasks to different components in the environment is compared.The application supplements the existing evidence on the effects of increasing carbon dioxide concentration and temperature on humans by combining the use of psychological, physiological and neurological tests and comparing different cognitive tasks. At the same time, a deep learning cognitive comfort model is constructed based on time-domain EEG features, providing new insights into the effects of environmental factors on cognition and suggesting potential applications for optimizing cognitive comfort through environmental control.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of indoor environment control, and in particular to a method for testing the influence of indoor CO2 concentration and temperature interaction on human cognition. BACKGROUND

[0002] Carbon dioxide (CO2) is a normal atmospheric constituent with a concentration of about 400 ppm. According to ASHRAE Standard 62.1, CO2 concentration is considered an indoor air pollutant caused by human metabolism. In indoor environments, CO2 levels are higher due to human activity, and since people spend most of their time indoors, indoor air pollution has an impact on comfort, health, and cognitive ability. The Occupational Safety and Health Administration (OSHA) and the American Conference of Governmental Industrial Hygienists (ACGIH) set a maximum recommended occupational exposure limit of 5000 ppm for CO2 concentration for an 8-hour workday. The World Health Organization (WHO) and ASHRAE recommend keeping indoor carbon dioxide levels below 5000 ppm. In addition, temperature also significantly affects human cognitive ability and is widely discussed as an indoor factor. Among noise, carbon dioxide concentration, and temperature, temperature is the most important factor affecting cognitive ability.

[0003] Studies have shown that high CO2 concentration or high temperature can significantly reduce decision-making performance on complex cognitive tasks. Testers reported more headaches, fatigue, agitation, and depression, accompanied by heat discomfort and decreased sleepiness, body weight, respiratory rate, heart rate, skin temperature, eardrum temperature, and arterial oxygen saturation. There is also a significant correlation between electroencephalogram signals and thermal comfort. Cognitive performance in traditional environments is significantly lower than in green buildings, and testers have more symptoms and faster heart rates. However, these results are controversial, as some studies found no significant changes in acute health symptoms, perceived air quality, or task performance similar to typical office work, and no significant effects on physiological responses or simple cognitive tasks.

[0004] Further, previous studies focused on building comfort models using physiological signals by changing environmental conditions, mainly modeling thermal comfort, anxiety, and cognitive comfort. Features such as skin temperature (ST), heart rate (HR), electrodermal activity (EDA), and electroencephalogram signals have shown significant correlation with comfort. Among them, modeling methods include traditional machine learning methods such as k-nearest neighbors (KNN), random forests (RF), and support vector machines (SVM), as well as advanced deep learning models such as deep neural networks (DNN) and transformer-based networks. These techniques have been used to model comfort.

[0005] Most studies have been univariate, examining the effects of CO2 concentration and temperature increase on cognitive performance through a single higher-order cognitive task or similar office task. Some literature has used multi-channel functional near-infrared spectroscopy (fNIRS) to investigate cortical activation during the Stroop task under these conditions. However, there is still a gap in understanding how different types of higher-order cognitive tasks react to the same exposure conditions, and the physiological driving factors have not been fully explored. Electroencephalography is a non-invasive method of studying brain function that has not been used to examine the interaction of carbon dioxide concentration and temperature on cognitive performance, and there is a lack of cognitive comfort models specifically for indoor environments. SUMMARY

[0006] The purpose of the present application is to overcome the technical problems existing in the prior art, and provide a test method for the interaction of indoor CO2 concentration and temperature on human cognitive influence, aiming to supplement the existing evidence on the effects of carbon dioxide concentration and temperature increase on humans by combining the use of psychological, physiological and neurological tests and comparing different cognitive tasks.

[0007] The purpose of the present application is achieved by the following technical solutions:

[0008] The present application provides a test method for the interaction of indoor CO2 concentration and temperature on human cognitive influence, characterized in that it comprises:

[0009] Screening of test subjects participating in the experiment;

[0010] Exposure environment construction: preparation of the environmental cabin and setting of the experimental conditions, including setting of different CO2 concentration levels and setting of different temperature levels;

[0011] Measurement of cognitive performance: conducting different types of cognitive task tests in the exposure environment and measuring subjective responses, physiological parameters and electroencephalogram;

[0012] Analysis of measurement data: processing of measurement data under different types of cognitive tasks and comparison of the sensitivity of different types of cognitive tasks to different components in the environment.

[0013] In some embodiments, the screening of test subjects participating in the experiment comprises:

[0014] Selecting 24 healthy test subjects, 12 females and 12 males, aged 18-31 years old, with a body mass index of 18.3-28.8 kg / m 2 .

[0015] In some embodiments, the environmental cabin uses a cylinder to provide CO2 to the test subject's breathing zone to maintain a uniform CO2 concentration field, and the CO2 concentration and temperature are determined by a non-dispersive infrared carbon dioxide sensor.

[0016] In some embodiments, the different CO2 concentration levels include 500 ppm and 5000 ppm; and the different temperature levels include 22℃ and 28℃.

[0017] In some embodiments, the different types of cognitive tasks include reactive control tasks and proactive control tasks.

[0018] In some embodiments, the measurement of subjective responses includes collecting subjective answers through electronic questionnaires and scaling thermal sensation under different conditions; and the physiological parameters include blood pressure, body temperature, heart rate and cortisol.

[0019] In some embodiments, the measurement of electroencephalogram includes:

[0020] During the task, the electroencephalogram activity was continuously recorded from 32 electrodes at a sampling rate of 512 Hz using a Grael 45ch amplifier compatible with the green panel and Curry 9 software.

[0021] In some embodiments, the processing of the measurement data under different types of cognitive tasks includes:

[0022] The collected raw data was filtered; the noise in the electroencephalogram was removed by independent component analysis; for each task, the range of the slice was from -1s to 2s, the baseline correction was from -1 to 0, and the number of attempts with a positive and negative amplitude greater than 100 was deleted; the frequency band was divided into δ (0.5-4hz), θ (4-8hz), α (8-13hz) and β (14-27hz) according to the fast Fourier transform, and the power spectral density of each frequency band was calculated.

[0023] In some embodiments, the method further includes:

[0024] A cognitive comfort model is constructed using the sliced time domain signal.

[0025] In some embodiments, the cognitive comfort model includes EEG-TCNet64, SVM and RandomForest.

[0026] It should be further pointed out that the technical features corresponding to the above options can be combined or replaced with each other to form new technical solutions without conflict.

[0027] Compared with the prior art, the present application has the following advantages:

[0028] The present application supplements the existing evidence on the effects of carbon dioxide concentration and temperature increase on humans by combining the use of psychological, physiological and neurological tests and comparing different cognitive tasks. At the same time, the deep learning cognitive comfort model is constructed based on the time domain electroencephalogram features, which provides new insights into the effects of environmental factors on cognition and suggests potential applications for optimizing cognitive comfort through environmental control, providing important experimental evidence and support for healthy living in indoor environments. BRIEF DESCRIPTION OF DRAWINGS

[0029] Figure 1 Test procedure flow chart for Stroop and DMS tasks shown in embodiments of the present application;

[0030] Figure 2 EEG topographic frequency signal comparison chart shown in embodiments of the present application;

[0031] Figure 3 Reaction time and accuracy of Stroop and DMS tasks under different CO2 and temperature exposure conditions shown in embodiments of the present application;

[0032] Figure 4 Physiological indicators after task testing under different exposure conditions shown in embodiments of the present application;

[0033] Figure 5 ERP waveforms during STROOP and DMS tasks under four different environmental conditions shown in embodiments of the present application;

[0034] Figure 6 Results of the interaction of the five regions of the scalp under different exposure conditions shown in embodiments of the present application;

[0035] Figure 7 Classification results under four environmental conditions using three machine learning models shown in embodiments of the present application.

[0036] Note: C1T1: 500ppm, 22℃; C2T1: 5000ppm, 22℃; C1T2: 500ppm, 28℃; C2T2: 5000ppm, 28℃. DETAILED DESCRIPTION

[0037] The technical solutions of the present application will be described clearly and completely below in conjunction with the accompanying drawings. Obviously, the described embodiments are part of the embodiments of the present application, not all. The components of the embodiments of the present application described and shown in the drawings herein can be arranged and designed in various different configurations. Based on the embodiments in the present application, all other embodiments obtained by those of ordinary skill in the art without creative labor fall within the scope of protection of the present application.

[0038] It should be noted that the defects of the above prior art solutions are the results obtained by the inventors after practice and careful study, therefore, the discovery process of the above problems and the solutions proposed by the embodiments of the present application to the above problems should be the contributions made by the inventors to the present application in the process of invention and creation, and should not be understood as technical contents known to those skilled in the art.

[0039] The present technology is derived from the National Key R&D Program Project (Approval No: 2022YFF1202900), and in view of the technical problems pointed out in the background art, the embodiments provided by the present application are as follows:

[0040] In an exemplary embodiment, the specific effects of elevated carbon dioxide concentrations (500 ppm and 5000 ppm) and temperatures (22°C and 28°C) on cognitive performance and neural responses were explored, using EEG features to construct a cognitive comfort model. 24 test subjects were divided into four groups, each exposed to four conditions during two 2.5-hour sessions in a day. They completed computer-based cognitive tests and questionnaires in each case. Significant interactions between CO2 concentration and temperature were found on noise acceptability, thermal comfort, and EEG, theta, and delta bands. Electroencephalogram features from these tests were used to train a machine learning model to distinguish cognitive states, providing new insights into the effects of environmental factors on cognition.

[0041] The specific test method includes the following parts:

[0042] 1、Testers

[0043] 24 (N = 24) healthy college students were recruited through social media in Tianjin, including 12 women and 12 men, aged 18-31, with a body mass index of 18.3-28.8 kg / m 2 They had no self-reported history of smoking, drinking or drug abuse. Exclusion criteria included self-reported or suspected: 1) claustrophobia, anxiety or depression history; 2) neurological diseases or brain trauma that may affect brain function and structure; 3) cognitive dysfunction; 4) cardiovascular, cerebrovascular, diabetes, hypertension or other chronic diseases; 5) asthma, allergic rhinitis, bronchitis or other respiratory diseases; 6) metal products or dentures in the body. Testers were told not to drink caffeine or alcohol, and to get enough sleep 24 hours before the experiment. Women participating in the experiment were not in the menstrual cycle during the exposure period. During the preparation process, the testers adjusted their clothes until they felt hot neutral. Then, they were asked to use the same clothing components throughout the exposure experiment.

[0044] 2、Exposure environment construction

[0045] Environmental chamber. Experiments were conducted in a small environmental chamber (3.24 m * 3.17 m * 2.55 m) at Tianjin University. Figure 1 A describes the structure of the CO2 concentration and temperature exposure chamber and the testers involved in the task. This room is equipped with two tables, each with a computer connected to the Internet. The cylinder provides CO2 to the tester's breathing zone to maintain a uniform CO2 concentration field. CO2 concentration and temperature are determined by a non-dispersive infrared carbon dioxide sensor. The sensor is located in three different directions for averaging.

[0046] Experimental conditions. Two CO2 levels were investigated: 500 ppm and 5000 ppm, and two temperature levels: 22°C and 28°C. The rationale for selecting these conditions is briefly described as follows:

[0047] Based on the ventilation rate and CO2 production rate of humans, the measured indoor CO2 levels rarely exceed 5000 ppm, which is the current 8-hour occupational exposure limit set by OSHA and ACGIH. To make a specific comparison, the reference exposure condition was set to 500 ppm when CO2 comes from outdoor air and the breath of the tester. ASHRAE-55 (2004) shows a thermal comfort range, with working temperatures of 20.5-25.5°C in winter and 24.5-28.0°C in summer. Therefore, 28°C was used as the high temperature condition, and 22°C was chosen as the neutral temperature condition. In a preliminary study of cancer patients, researchers also used a temperature contrast of 22°C and 28°C.

[0048] 3、Measurement

[0049] Measurement of cognitive performance. Neurobehavioral methods are commonly used to assess responses to external environmental stimuli. Human behavior itself is mainly classified according to emotions, cognition, and execution. Among them, cognition can be subdivided into four main functions: learning and memory, thinking, perception, and expression. According to the dual mechanism of control (DMC) framework of Braver (2012), reactive control is a post-correction process that occurs after detecting a conflict or error event. It allows the selection of appropriate responses by suppressing interfering responses. In contrast, proactive control is a top-down selection process that occurs before events with high cognitive demands. It maintains task goals and biased sensory processing to facilitate the processing of task-relevant information. Task selection is based on the two theories described above. The Stroop task is a reactive control task, falling into the categories of perception and thinking. The DMS task is a proactive control task, falling into the categories of perception and memory. All cognitive tasks are presented using E-Prime 2.0 software (Psychology Software Tools, Pittsburgh, USA).

[0050] Further, in the Stroop task, participants named the ink color under congruent and incongruent conditions, ignoring the color word; in the DMS task, the subjects simply maintained the stimulus under the maintenance condition, and mirrored the vertical stimulus midline in the color square under the manipulation condition; questionnaire i included the subjects' demographic information, perceived environment, and acute health symptoms; questionnaire ii included information about perceived environment, acute health symptoms, and task assessment; the Stroop task included congruent and incongruent trials Figure 1 B). The Stroop trials randomly appeared within 10 blocks, each consisting of 16 trials. Before the 160 task trials, the tester could familiarize the task in 16 practice trials. All stimuli appeared on a white background until the tester pressed a key and a central black fixation cross persisted for 500 ms. In the congruent trials, the Chinese color words of red, yellow, blue, and green were indicated by the corresponding ink color. In contrast, the incongruent trials were composed of color words and their meaning different colors. The tester was asked to indicate their respective ink color as accurately and quickly as possible, while ignoring the meaning of the color word. Responses were made by pressing the keys "J" and "K" on the keyboard with the right index finger and "F" and "D" with the left index finger.

[0051] The DMS task contained two conditions, namely the maintenance trial and the manipulation trial, each including 54 task trials and 18 practice trials Figure 1 B). The stimuli included 1 or 4 color squares integrated into a 6 x 6 matrix, which were presented randomly. In the maintenance trial, the tester was asked to maintain the position of a green square for a delay time. The stimulus lasted for 500 milliseconds, followed by a 2000 millisecond delay period, during which the afterimage effect was prevented by providing a mask composed of a gradient gray square. In the manipulation trial, the tester mentally mirrored the position of four red squares on the vertical stimulus midline and maintained the mirrored position. The stimulus lasted for 1000 milliseconds, followed by a 2000 millisecond delay period, during which the afterimage effect was prevented by providing a mask composed of a gradient gray square. Then, a probe matrix was presented, whose gray squares matched or did not match the position of the color squares that coded the stimulus. The tester was instructed to determine whether the gray square of the probe was the same (match) or different (non-match) from the position of the color square maintained by pressing the key "F" on the keyboard with the left index finger or the key "J" with the right index finger, respectively. In the non-match trials of the manipulation trial, only one of the four squares did not match the correct mirrored position. Half of the trials were correct responses for the match, and the other half were for the non-match. During the probe presentation, the tester was asked to respond as accurately and quickly as possible. In the adjacent inter-trial interval (ITI), a central fixation cross appeared for a duration of 500-1500 ms. All stimuli appeared in the center of a white background.

[0052] Subjective measures. An electronic questionnaire was used to collect subjective answers. Questions about thermal acceptability (TA), thermal sensation (TS) and thermal comfort (TC); perceived air quality (PAQ), odor intensity (OI), noise, lighting; sick building syndrome symptoms (SBS). Given that there were only two completely different temperature conditions in the experiment, the 7-point scale of ASHRAE 38 was chosen to determine thermal sensation.

[0053] Measurement of physiological parameters. Physiological parameters included blood pressure, body temperature, heart rate and cortisol. The instruments used for the measurements were calibrated. Blood pressure and heart rate were measured with an Omron-U724J sphygmomanometer (40-180 beats / min ± 5% accuracy). A glass mercury thermometer was used to measure body temperature. Underarm temperature was measured. Saliva samples were collected before and after the contact for subsequent analysis of changes in the stress biomarker cortisol. The tester was asked to drool into a container to collect the sample. The saliva samples after collection were immediately stored in a refrigerator (-80°C) until analysis with a human saliva cortisol ELISA kit (Wuhan Adanti Biotechnology Co., Ltd.). Before using the ELISA kit, all samples were centrifuged at 2000 rpm for 20 minutes to obtain the supernatant. The ELISA kit was then used for a series of operations. Finally, the enzyme-labeled coated plate was placed in a wavelength of 450 nm (Multifunctional Microplate Detector-H1M, Guangzhou Daluikang Body Engineering Technology Co., Ltd.) to measure the OD value of each well.

[0054] Measurement of electroencephalogram. During the task, electroencephalogram activity was continuously recorded from 32 electrodes at a sampling rate of 512 Hz using a Grael 45ch amplifier compatible with green panels (Wuhan Green Tech Co., Ltd., China) and Curry 9 software. Given the extended 10-20 system, scalp electrodes were mounted on a suitable cap. During continuous electroencephalogram recording, electrode impedance was mostly kept below 5 kΩ. The signals obtained were referenced to M1 and M2. The EEGLAB toolbox in MATLAB was used to remove electromyographic artifacts and eye movements from the original recordings.

[0055] 4. Experimental procedure

[0056] During the experiment, individual differences were counteracted and a balanced Latin square design was used to control practice and fatigue effects, in which 24 subjects were divided into 4 groups, each with 6 subjects. Only one person from each group participated in the experiment at a time. In addition, each group was exposed to two temperature conditions for one day. Each temperature exposure condition lasted for 2.5 hours from 9:00 to 11:30 am or from 2:00 to 4:30 pm. Table 1 shows the standardized two-by-two balanced Latin square design, in which factor T represents the temperature variable (T1-22°C, T2-28°C), factor D refers to the four-day cycle, and factor C represents the carbon dioxide concentration variable (C1-500 ppm, C2-5000 ppm).

[0057] Table 1 Standardized two-by-two balanced Latin square design

[0058]

[0059] Figure 1 C shows the progress of the experiment. In the preparation phase, the subjects entered the chamber, wore electroencephalogram equipment, filled out questionnaire i, and took baseline physiological measurements for 30 minutes. The experiment was conducted in the order of exposure. The detailed experimental protocol for the first half of the day for Group 1 is shown in Table 2. Figure 1 C. Each CO2 concentration condition lasted for 60 minutes. First, the exposure level of CO2 concentration was adjusted to a specific concentration. Then, the subjects adapted to the indoor environment for 20 minutes. After exposure, the subjects were tested for 30 minutes to assess human cognitive performance and neural responses. After the test was completed, the physiological parameters of the subjects were continuously measured for 5 minutes. Finally, the subjects were required to complete questionnaire ii for about 5 minutes to assess their self-reported effort and acute health symptoms. During the 2.5-hour experiment, the subjects were not allowed to leave the environmental chamber. At the same time, all measurements were taken indoors.

[0060] 5. Data processing

[0061] Cognitive task performance. Accuracy (ACC) and reaction time (RT) were used as measurement indicators, which are important indicators of cognitive performance. The 36 data of each person, each condition, and each task were averaged, and extreme data were excluded.

[0062] Neural responses using electroencephalography. First, the direct current (DC) offset was removed by applying a 0.5-40 Hz band-pass filter to the raw data collected from each channel. Second, a notch filter was used to remove 50 Hz power-line interference. In addition, noise in the electroencephalography was removed by independent component analysis (ICA). Then, for each task, the range of the slice was from -1 s to 2 s, and the baseline correction was from -1 to 0. The number of trials with a positive or negative amplitude greater than 100 was deleted. Subsequently, the frequency bands were divided into delta (0.5-4 Hz), theta (4-8 Hz), alpha (8-13 Hz), or beta (14-27 Hz) according to the fast Fourier transform (FFT). Finally, the power spectral density (PSD) of each frequency band was calculated, specifically, the transformation formula of the time-domain signal is as follows:

[0063]

[0064] The calculation formula of the power spectral density is as follows:

[0065]

[0066] Where s(t) is the function of the time-domain signal; T is the time; is the time-domain discrete signal.

[0067] The cognitive comfort model was constructed using the sliced time-domain signal, 80% of the data as the training set, and 20% as the test set. Cross-validation and grid search were used to adjust the parameters of the SVM and random forest models. By testing different parameter values, the best cross-validation accuracy was selected as the final parameter of the trained model.

[0068] 6. Statistical analysis

[0069] The results were analyzed using SPSS 22.0 software (SPSS Inc., Chicago, IL, USA). Two-way repeated measures ANOVA was used to test the effects of CO2 levels, temperature levels, and the interaction between CO2 and temperature levels on the data. For significant results of the interaction ANOVA, simple effect analysis was used to compare the differences between different factor levels. When the main effect is significant, the multiple test correction (Bonferroni test) is used to compare the differences between different factor levels.

[0070] To measure the tester's response to different types of tasks, this study analyzed the differences between each task under two different conditions using a paired t-test. Then, the consistent and inconsistent trials were compared, including the mean and standard deviation, t-score, p-value, and effect size d of the results of the retention and manipulation trials. The results were statistically significant when the p-value was equal to or less than 0.05.

[0071] In one example, based on the above test method, specific test results are given, specifically including the following parts:

[0072] 1. Physical parameters

[0073] Table 2 shows the measured CO2 concentrations and temperatures. The temperature deviated no more than 0.5 °C from the intended level, and the CO2 concentrations fluctuated within a range not far from the intended level.

[0074] Table 2. Measured conditions during exposure in the test chamber (mean ± SD)

[0075]

[0076] 2. Cognitive performance

[0077] Figure 3 The results of the Stroop and DMS tasks under different CO2 and temperature exposure conditions were shown by repeated measures ANOVA, where in the Stroop task the blue line represents the congruent trials and the red line represents the incongruent trials; in the DMS task the blue line represents the maintenance trials and the red line represents the operation trials. For the Stroop task, there were no significant differences in accuracy and reaction time between the different exposure conditions in the congruent and incongruent trials. (All p values > 0.138). For the DMS task, the analysis of the operation trials showed that accuracy was marginally significant under the interaction (F(l,23) = 3.34, p = 0.081), while reaction time was marginally significant under the influence of temperature (F(l,23) = 3.20, p = 0.087), but in the maintenance trials (all p values > 0.181).

[0078] The effects on performance in the Stroop and DMS tasks were analyzed using paired t-tests to compare performance in the congruent and incongruent trials (accuracy: t(95) = 6.65, p < 0.001, d = 0.68, reaction time: t(95) = 11.48, p < 0.001, d = 1.17), and in the maintenance and operation trials (accuracy: t(95) = 21.90, p < 0.001, d = 2.23, reaction time: t(95) = 9.80, p < 0.001, d = 1.00). Overall, these results show that, regardless of the exposure condition, the congruent trials always had faster reaction times and higher accuracy than the incongruent trials; the maintenance trials always had faster reaction times and higher accuracy than the operation trials.

[0079] 3. Subjective reactions

[0080] Table 3 shows the results of the subjective assessments. Temperature had a significant main effect on nasal dryness (F(l,23) = 5.90, p = 0.023), with less dryness at lower temperatures. For this symptom, there was no significant interaction of C02 level with temperature. The other sick building syndrome symptoms showed no significant effects of C02 or temperature during the exposure (all p > 0.096). There were significant main effects of C02 (F(l,23) = 10.90, p = 0.003) and temperature (F(l,23) = 15.58, p = 0.001) on air quality perception, with fresher air perceived at lower C02 concentrations and temperatures. Acceptability of air quality was marginal in the main effect of temperature (F(l,23) = 4.18, p = 0.053). For noise, there was a significant main effect in the interaction (F(l,23) = 4.39, p = 0.047). Simple effect analysis showed that at low temperatures, higher C02 concentrations were more acceptable (p = 0.057); at high C02 concentrations, lower temperatures were more acceptable (p = 0.056), but neither reached significance. This can be because the ventilation required at low C02 concentrations interfered with the participants' perception of the noise. For odour, C02 had a main effect (F(l,23) = 8.10, p = 0.009), with higher concentrations being less acceptable. C02 (F(l,23) = 12.55, p = 0.002) and temperature (F(l,23) = 32.30, p < 0.001) also affected thermal sensation, with participants feeling warmer at higher levels. Thermal comfort showed a significant interaction effect (F(l,23) = 8.42, p = 0.008); higher C02 concentrations at low temperatures made participants more comfortable (p = 0.007). A significant interaction effect was found for acceptability of temperature (F(l,23) = 5.24, p = 0.032). At high temperatures, lower C02 levels made temperature more acceptable (p = 0.036); at high C02, lower temperatures were more acceptable (p = 0.012). Lighting had no significant effect (all p > 0.103).

[0081] The exposure conditions did not significantly affect task difficulty, effort, perceived stress, or self-perceived performance (all p > 0.183).

[0082] Table 3 Subjective assessment of acute health symptoms under different exposure conditions

[0083]

[0084]

[0085]

[0086] 4. Physiological parameters

[0087] A series of physiological parameters were measured during the experiment. Analysis of variance of repeated measures showed that temperature had a significant effect on body temperature and heart rate. Blood pressure results showed little variation across the different CO2 and temperature exposure conditions. There was no significant interaction of CO2 and temperature, but a slight significant effect on Cortisol concentration. For body temperature, there was a main effect of temperature (F(l,23) = 40.75, p < 0.001). Body temperature was significantly higher in the high temperature condition than in the low temperature condition, irrespective of CO2. For heart rate, temperature had a main effect (F(l,23) = 8.26, p = 0.009). Heart rate was significantly higher in the high temperature condition than in the low temperature condition, irrespective of CO2. Blood pressure was not affected by carbon dioxide and temperature, remaining stable over time Figure 4 A). Cortisol concentration was found to be marginally significant (F(l,23) = 3.57, p = 0.072 Figure 4 B) under the interaction. Moreover, no significant differences were found between pre- and post-measures (all p-values were greater than 0.146).

[0088] 5. Electroencephalogram

[0089] Event-related potentials (ERPs) are a non-invasive measure of human brain activity that reflects a range of sensory, cognitive, emotional, and motor processes. Figure 5 ERP waveforms under the four different environmental conditions during the STROOP and DMS tasks are depicted, giving the average of the scalp potentials measured at electrodes FZ, CZ, and PZ under the four exposure conditions, Stroop task. Orange lines represent consistent trials, blue lines represent inconsistent trials. Goal-directed management system task. Orange lines represent retention trials, blue lines represent manipulation trials. Two-way repeated measures ANOVA of the average amplitude over the 0 to 1 second interval did not reveal any significant differences. Figure 5 A focuses on the ERP differences under inconsistent and consistent conditions, which can quantify to some extent the cognitive effort required in inconsistent trials. Differences were observed in the 0.3-0.6 second interval. Therefore, average amplitude comparisons were performed in this interval, revealing marginal main effects of temperature on electrodes FZ (F(l,23) = 3.33, p = 0.081) and CZ (F(l,23) = 2.68, p = 0.061). Figure 5 B illustrates the ERP waveform differences under retention and manipulation conditions in the DMS task, thus quantifying the influence of memory processes under manipulation conditions. No significant differences were found in the 0.3-0.6 second interval.

[0090] Time-frequency plots for the four exposure conditions during the Stroop and DMS tasks are shown in Figures Figure 5 A significant temperature main effect was found for the theta (F(l,23) = 5.12, p = 0.033) and beta bands (F(l,23) = 9.98, p = 0.004) for the incongruent trials only. For the DMS task, a significant alpha band main effect of performance condition was found for the 0-1 s (F(l,23) = 4.55, p =.044) and 1-2 s (F(l,23) = 6.84, p =.015) trials. The theta power spectral density was consistently increasing in the 1-2 s time interval for the performance condition of the DMS task. This suggests that ongoing cognitive processing involved updating or manipulating working memory content, reflecting the dynamic demands of cognitive control and manipulation strategies in this stage of the task. Simple effect analysis showed that the lower the CO2 concentration, the higher the amplitude of alpha at low temperature (p = 0.003); the lower the temperature, the higher the amplitude of alpha at low CO2 concentration (p =.016). Significant concentration main effects in the beta band were found for both the 0-1 s (F(l,23) = 5.99, p =0.022) and 1-2 s (F(l,23) = 7.44, p =0.012) trials.

[0091] Topographical maps for the three bands (theta, alpha, and beta) during the Stroop and DMS tasks for the four exposure conditions are shown in Figures Figure 2 A significant temperature main effect was found for the theta (F(l,23) = 5.12, p = 0.033) and beta bands (F(l,23) = 9.98, p = 0.004) for the incongruent trials only. For the DMS task, a significant alpha band main effect of performance condition was found for the 0-1 s (F(l,23) = 4.55, p =.044) and 1-2 s (F(l,23) = 6.84, p =.015) trials. The theta power spectral density was consistently increasing in the 1-2 s time interval for the performance condition of the DMS task. This suggests that ongoing cognitive processing involved updating or manipulating working memory content, reflecting the dynamic demands of cognitive control and manipulation strategies in this stage of the task. Simple effect analysis showed that the lower the CO2 concentration, the higher the amplitude of alpha at low temperature (p = 0.003); the lower the temperature, the higher the amplitude of alpha at low CO2 concentration (p =.016). Significant concentration main effects in the beta band were found for both the 0-1 s (F(l,23) = 5.99, p =0.022) and 1-2 s (F(l,23) = 7.44, p =0.012) trials.

[0092] To determine whether these effects were related to scalp regions, the relative power of the four frequency bands (alpha, beta, theta, and delta) of the five scalp regions (frontal, central, parietal, occipital, and temporal) were calculated. For the task trials, the relative frequency band power of the frontal (FP1, FP2, F3, FZ, F4), central (C3, CZ, C4), parietal (P7, P3, PZ, P4, P8), occipital (O1, OZ, O2), and temporal (T7, T8) electrodes of each EEG recording were calculated. Figure 6 The main effects of the relative optical power of the five scalp regions under different exposure conditions are shown. The black line represents the frontal lobe, the red line represents the central lobe, the blue line represents the parietal lobe, the pink line represents the occipital lobe, and the green line represents the temporal lobe. As Figure 2 As shown in Figures 2A and 2B, the relative power changes in the alpha and beta bands were more pronounced than those in the other frequency bands. However, the scalp regions were not particularly sensitive to the interaction between CO2 and temperature. In the alpha band, the central (inconsistent: F(l,23) = 4.17, p = 0.053), parietal (consistent: F(l,23) = 3.60, p = 0.070 inconsistent: F(l,23) = 6.17, p = 0.021), and occipital (overall: F(l,23) = 3.45, p = 0.076 inconsistent: F(l,23) = 4.88, p = 0.037). In the theta and delta bands, only the temporal lobe of the inconsistent test showed significant differences (theta: F(l,23) = 4.89, p = 0.037; delta: F(l,23) = 5.43, p = 0.029). As Figure 6 As shown in Figures 2C and 2D, no interaction was found to be affected by exposure conditions (all p values > 0.083).

[0093] Figure 6 The main effects of the relative optical power of the five scalp regions under different exposure conditions are shown. For the Stroop task, the main effects were reflected in the beta band (central: F(l,23) = 8.24, p = 0.009 parietal: F(l,23) = 6.01, p = 0.022 occipital: F(l,23) = 3.46, p = 0.076 temporal: F(l,23) = 6.57, p = 0.017) and beta (central: F(l,23) = 10.77, p = 0.003 parietal: F(l,23) = 6.42, p = 0.019 temporal: F(l,23) = 7.49, p = 0.012) and delta bands (parietal: F(l,23) = 3.49, p = 0.075), as Figure 6 A and Figure 6 B. Among them, only the beta band of the occipital lobe and the delta band of the parietal lobe were related to the main effect of temperature, and the rest were related to the main effect of CO2 concentration. As Figure 6 C and Figure 6As shown in D, DMS task was significantly affected by the main effect of temperature. For the retention test, the main effect was reflected in the alpha band (occipital: F(l,23) = 3.26, p = 0.084), beta band (central: F(l,23) = 3.42, p = 0.078 parietal: F(l,23) = 3.18, p = 0.088 occipital: F(l,23) = 3.79, p = 0.064), theta band (occipital: F(l,23) = 3.15, p = 0.089), delta band (central: F(l,23) = 4.26, p = 0.051 parietal: F(l,23) = 3.69, p = 0.067 time: F(l,23) = 4.29, p = 0.050). Among them, only the delta band of the central lobe and parietal lobe was related to the main effect of temperature, and the rest was related to the main effect of CO2 concentration. For the operation test, the main effect was reflected in the alpha band (occipital: F(l,23) = 3.17, p = 0.088), beta band (frontal: F(l,23) = 4.02, p = 0.057 occipital: F(l,23) = 4.02, p = 0.057), and delta band (frontal: F(l,23) = 7.89, p = 0.010 central: F(l,23) = 3.88, p = 0.061 parietal: F(l,23) = 4.62, p = 0.042 time: F(l,23) = 3.56, p = 0.072). Among them, only the alpha band of the occipital lobe was related to the main effect of CO2 concentration, and the rest was related to the main effect of temperature. No other main effect was found to be affected by exposure conditions (all p values > 0.105).

[0094] 6. Cognitive comfort model. In the present invention, the effects of four environmental conditions on electroencephalographic activity were investigated. Using three machine learning models (EEG-TCNet64, SVM, and RandomForest), we classified the EEG data to discern the effects of these conditions and cognitive states. Figure 7 The classification results are shown. Figure 7 A shows the classification accuracy for each subject, indicating the significant effect of different environments on electroencephalographic activity. The high accuracy between subjects indicates that environmental changes result in significant and measurable differences in EEG signals. Figure 7 B shows the overall classification accuracy when combining data from all subjects, demonstrating that environmental conditions consistently affect EEG responses at the group level. Figure 7 C provides a cumulative confusion matrix highlighting correct and incorrect classifications under various conditions. The matrix shows that while most classifications are correct, some confusion occurs under similar conditions. For example, the effect of CO2 concentration is confounded under DMS task conditions. The effects of temperature and carbon dioxide on the STROOP task are clearly classifiable.

[0095] 7、Conclusion

[0096] The present study investigated the effects of the interaction of carbon dioxide concentration and temperature on human cognitive performance and neural responses. No significant effects of the interaction of exposure conditions on behavioral performance were found. Increasing carbon dioxide concentration made the air and nose feel drier for the participants. Increasing temperature made the participants feel more thermal discomfort. Drier air and nose led to a substantial increase in body temperature and heart rate. At the neural level, the interaction of CO2 concentration and temperature had a greater adverse effect on the Stroop task, while temperature had a greater adverse effect on the DMS task. Finally, the confusion matrix of the cognitive comfort model reached consistent conclusions and provided a basis for determining the cognitive comfort level of the participants. In summary, different control types of cognitive tasks have different sensitivities to different components in the environment. Exposure to high CO2 concentration and adverse conditions of temperature affects physiological indicators and comfort, which in turn affects cognitive performance and neural responses. Therefore, it is reasonable to construct a cognitive comfort model based on neural responses.

[0097] The above detailed description of the present application is not intended to limit the present application to only the specific embodiments described, as the present application is susceptible to modification and adaptation by those skilled in the art without departing from the spirit or scope of the present application.

Claims

1. A method of testing the effect of indoor CO2 concentration and temperature interaction on human cognition, characterized by, The method comprises: Screening test subjects participating in the experiment; Exposure environment construction: preparing the environmental chamber and setting the experimental conditions, including setting different CO2 concentration levels and different temperature levels; Cognitive performance measurement: conducting different types of cognitive task tests in the exposure environment and measuring subjective responses, physiological parameters, and electroencephalograms; the different types of cognitive tasks include reactive control tasks and proactive control tasks, wherein the reactive control tasks include consistent and inconsistent tests, and the proactive control tasks include maintenance tests and operation tests; The measurement of electroencephalogram includes: During the task, the Grael 45ch amplifier compatible with the green panel and the Curry 9 software are used to continuously record the electroencephalogram activity from 32 electrodes at a sampling rate of 512 Hz; Measurement data analysis: processing the measurement data under different types of cognitive tasks and comparing the sensitivity of different types of cognitive tasks to different components in the environment; The processing of measurement data under different types of cognitive tasks includes: Filtering the collected raw data; removing noise in the electroencephalogram by independent component analysis; for each task, the range of the slice is from -1s to 2s, the baseline correction is from -1 to 0, and the number of attempts with a positive and negative amplitude greater than 100 is deleted; according to the fast Fourier transform, the frequency band is divided into δ (0.5-4hz), θ (4-8hz), α (8-13hz) and β (14-27hz), and the power spectral density of each frequency band is calculated; Comparing the amplitudes of the four frequency bands under different exposure conditions of the FZ channel; Comparing the power spectral densities of the four frequency bands under different exposure conditions and marking the significance of the FZ channel in the topographic map; Calculating the relative power of the four frequency bands in five scalp regions to determine whether the effect is related to the scalp region; Comparing the significant main effects of the relative focal length of the five scalp regions under different exposure conditions; Further comprising: Using the sliced time domain signal to build a cognitive comfort model, and using the cognitive comfort model to classify the electroencephalogram data to distinguish the effects of these conditions and cognitive states.

2. The method of claim 1, wherein the method is a method of testing the effect of indoor CO2 concentration and temperature interaction on human cognition, characterized by, The screening of test subjects participating in the experiment comprises: Twenty-four healthy subjects were selected, 12 females and 12 males, aged 18-31 years, with a body mass index of 18.3-28.8 kg / m 2 .

3. The method of claim 1, wherein the method is a method of testing the effect of indoor CO2 concentration and temperature interaction on human cognition, characterized by, The environmental chamber uses a cylinder to provide CO2 to the test subject's breathing zone to maintain a uniform CO2 concentration field, and the CO2 concentration and temperature are determined by a non-dispersive infrared carbon dioxide sensor.

4. The method of claim 1, wherein the method is a method of testing the effect of indoor CO2 concentration and temperature interaction on human cognition, characterized by, The different CO2 concentration levels include 500ppm and 5000ppm; the different temperature levels include 22℃ and 28℃.

5. The method of claim 1, wherein the method is a method of testing the effect of indoor CO2 concentration and temperature interaction on human cognition, characterized by, The measurement of subjective responses includes collecting subjective answers through electronic questionnaires and scaling the thermal sensation under different conditions; the physiological parameters include blood pressure, body temperature, heart rate, and cortisol.

6. The method of claim 1, wherein the method is a method of testing the effect of indoor CO2 concentration and temperature interaction on human cognition, characterized by, The cognitive comfort model includes EEG-TCNet64, SVM, and RandomForest.

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