Introduction
Basic theories and concepts
Cloud model (CM)
Basic operations of the CM
Cloud model conversion of uncertain language value
Research method
Cloud-AHP algorithm
Importance | Linguistic term | \({E}_{x}\) | \({E}_{n}\) | \({H}_{e}\) |
---|---|---|---|---|
1 | Index i and Index j are equally important | 1 | 0 | 0 |
3 | Index i is slightly more important than index j | 3 | 0.33 | 0.05 |
5 | Index i is obviously more important than index j | 5 | 0.33 | 0.05 |
7 | Index i is considerably more important than index j | 7 | 0.33 | 0.05 |
9 | Index i is absolutely more important than index j | 9 | 0.33 | 0.05 |
2, 4, 6, 8 | Index i is more important than index j between 1, 3, 5, and 9 | 2, 4, 6, 8 | 0.33 | 0.05 |
Group cloud multi-dimensional comprehensive decision-making (GC-MCDM) algorithm
Multi-dimensional cloud-TOPSIS (MDCT) algorithm
Linguistic judgments | \(\left({E}_{x},{E}_{n}{,H}_{e}\right)\) |
---|---|
Very low (VL) | (0.1, 0.1/3, 0.01) |
Low (L) | (0.2, 0.1/3, 0.01) |
Relatively low (RL) | (0.35, 0.2/3, 0.02) |
Medium (M) | (0.5, 0.1/3, 0.01) |
Relatively high (RH) | (0.65, 0.2/3, 0.02) |
High (H) | (0.8, 0.1/3, 0.01) |
Very high (VH) | (0.9, 0.1/3, 0.01) |
Assessment integration mechanism based on CM
Methodology
Case study (mental load test)
Experiment introduction
Preliminary selection of indices and hierarchical structure
Pair | Paired differences | t | p value | Pearson’s correlation | ||||||
---|---|---|---|---|---|---|---|---|---|---|
Mean | SD | Std. Error | 95 CI | Correlation | p value | |||||
Lower | Upper | |||||||||
1 | MeanIBI (RS)–meanIBI (ML) | 0.037 | 0.054 | 0.012 | 0.011 | 0.062 | 3.004 | 0.007 | 0.691 | 0.001 |
2 | MeanHR (RS)–meanHR (ML) | − 5.350 | 7.903 | 1.767 | − 9.049 | − 1.651 | − 3.028 | 0.007 | 0.697 | 0.001 |
3 | SDNN (RS)–SDNN (ML) | 0.077 | 0.127 | 0.028 | 0.018 | 0.136 | 2.727 | 0.013 | 0.709 | 0.000 |
4 | PNN50 (RS)–PNN50 (ML) | 0.048 | 0.131 | 0.029 | − 0.013 | 0.109 | 1.635 | 0.118 | 0.304 | 0.180 |
5 | LFnorm (RS)–LFnorm (ML) | − 0.057 | 0.199 | 0.045 | − 0.150 | 0.036 | − 1.280 | 0.216 | 0.243 | 0.303 |
6 | HFnorm (RS)–HFnorm (ML) | 0.057 | 0.199 | 0.045 | − 0.036 | 0.150 | 1.280 | 0.216 | 0.243 | 0.303 |
7 | LF/HF (RS)–LF/HF (ML) | − 4.423 | 15.871 | 3.549 | − 11.850 | 3.005 | − 1.246 | 0.228 | 0.469 | 0.037 |
8 | Theta (θ) (RS)–Theta (ML) | − 27.622 | 11.218 | 2.448 | − 32.729 | − 22.516 | − 11.283 | 0.000 | 0.895 | 0.000 |
9 | Alpha (α) (RS)–Alpha (ML) | − 20.185 | 29.964 | 6.539 | − 33.824 | − 6.545 | − 3.087 | 0.006 | 0.622 | 0.003 |
10 | Beta (β) (RS)–Beta (ML) | − 58.877 | 51.746 | 11.292 | − 82.431 | − 35.322 | − 5.214 | 0.000 | 0.875 | 0.000 |
11 | α/β (RS)–α/β (ML) | 1.175 | 3.632 | 0.793 | − 0.478 | 2.828 | 1.483 | 0.154 | 0.443 | 0.044 |
12 | θ/β (RS)–θ/β (ML) | 1.248 | 4.216 | 0.920 | − 0.671 | 3.167 | 1.357 | 0.190 | 0.616 | 0.003 |
13 | (α + θ)/β (RS)–(α + θ)/β (ML) | 2.423 | 7.822 | 1.707 | − 1.137 | 5.983 | 1.420 | 0.171 | 0.534 | 0.013 |
14 | (α + θ)/(α + β) (RS)–(α + θ)/(α + β) (ML) | 0.244 | 1.634 | 0.357 | − 0.499 | 0.988 | 0.685 | 0.501 | 0.095 | 0.682 |
15 | θ/(α + β) (RS)–θ/(α + β) (ML) | 0.097 | 0.892 | 0.195 | − 0.309 | 0.503 | 0.499 | 0.623 | 0.096 | 0.680 |
16 | Pupil diameter (RS)–Pupil diameter (ML) | − 1.192 | 0.404 | 0.088 | − 1.376 | − 1.008 | − 13.525 | 0.000 | 0.802 | 0.000 |
17 | Fixation time (RS)–Fixation time (ML) | 234.000 | 211.802 | 46.219 | 137.589 | 330.411 | 5.063 | 0.000 | 0.496 | 0.022 |
18 | Blink frequency (RS)–Blink frequency (ML) | 25.952 | 128.852 | 28.118 | − 32.701 | 84.605 | 0.923 | 0.367 | 0.550 | 0.012 |
19 | Questionnaire score (RS)–Questionnaire score (ML) | − 0.775 | 1.340 | 0.245 | − 1.275 | − 0.275 | − 3.169 | 0.004 | − 0.237 | 0.207 |
20 | Error value (RS)–Error value (ML) | − 0.340 | 0.487 | 0.109 | − 0.568 | − 0.112 | − 3.124 | 0.006 | 0.711 | 0.000 |
21 | Total relative error (RS)–Total relative error (ML) | − 0.175 | 0.266 | 0.060 | − 0.300 | − 0.050 | − 2.941 | 0.008 | 0.651 | 0.002 |
22 | Positive relative error (RS)–Positive relative error (ML) | − 0.050 | 0.099 | 0.022 | − 0.096 | − 0.003 | − 2.229 | 0.038 | 0.387 | 0.092 |
23 | Negative relative error (RS)–Negative relative error (ML) | − 0.048 | 0.122 | 0.027 | − 0.105 | 0.009 | − 1.746 | 0.097 | 0.345 | 0.136 |
Index | Unit | Description |
---|---|---|
HR (X1) | bpm | The number of heart beats per minute of a normal person in a quiet state |
IBI (X2) | ms | The time interval between two heart beats |
SDNN (X3) | ms | Standard deviation of all heartbeat intervals which evaluates the overall heart rate variability and reflects the slow changes in heart rate. It is a sensitive index for evaluating parasympathetic nerve activity |
LF/HF (X4) | – | The ratio of low-frequency power to high-frequency power, which reflects the balance control of the autonomic nervous system |
Alpha (α) (X5) | Hz | The α-energy is a wave with a frequency in the 8–13 Hz band. The waveform is similar to a sine wave. Normal human brain electrical signals are mostly alpha waves, which are dominant among the five wave types. It is easy to detect, especially in a quiet and awake state |
Beta (β) (X6) | Hz | The β wave is a typical fast wave. It is in a high frequency, low amplitude, and an asynchronous state; the amplitude is between 5 and 30 microvolts They are generally, evenly, and symmetrically distributed on both sides of the brain, and the forehead will be more obvious. Beta waves often appear during serious thinking, concentration, tension, and excitement |
Theta (θ) (X7) | Hz | The frequency band of wave θ is 4–8 Hz. This type of wave mainly appears in adolescence (adults are usually in the workplace). It is easy to detect this kind of wave when a person is frustrated and depressed |
Pupil diameter (X8) | mm | The pupil diameter is controlled by the sympathetic and parasympathetic nerves of the autonomic nervous system. The two kinds of nerves drive the dilated pupil and the pupillary sphincter to contract and adjust the pupil size. The range of changes is 2–8 mm |
Fixation time (X9) | ms | The duration of the gaze activity during the experiment. This index reflects the difficulty of the study participants in extracting information and their attention distribution |
Blink frequency (X10) | count/s | The number of eye blinking activities in unit time |
Time requirement (X11) | Point | The time required to complete the experiment or task |
Mental tension (X12) | Point | Difficult mood changes encountered when completing experiment or task |
Performance level (X13) | Point | The expected level of final completion when completing an experiment or task |
Task difficulty (X14) | Point | The overall difficulty of the experiment or task upon the completion of the experiment or task |
Response time error (X15) | s | The study participants are presented with a time value, required to estimate the actual length, and the difference between the estimated time and the actual time is calculated |
Total relative error rate (X16) | % | The relative error rate between the study participant’s estimated time value and the actual time value |
Prioritization of indices based on MDCT
Dimension | CM scale: (expected value, entropy, hyper entropy)\(\left({E}_{x},{E}_{n}{,H}_{e}\right)\) | ||
---|---|---|---|
Accessibility | Operability | Sensitivity | |
Accessibility | (1, 0, 0) | (1/2, 0.33/4, 0.05/4) | (1/3, 0.33/9, 0.05/9) |
Operability | (2, 0.33, 0.05) | (1, 0, 0) | (1/2, 0.33/4, 0.05/4) |
Sensitivity | (3, 0.33, 0.05) | (2, 0.33, 0.05) | (1, 0, 0) |
Weight calculation of attribute parameter | |||
---|---|---|---|
Multiply the rows | |||
\({E}_{{x}_{i}}\) | 0.1667 | 1 | 6 |
\({E}_{{n}_{i}}\) | 0.0331 | 0.2333 | 1.1898 |
\({H}_{{e}_{i}}\) | 0.0050 | 0.0354 | 0.1803 |
Square roots | |||
\(E^{\prime}_{{x_{i} }}\) | 0.5503 | 1 | 1.8171 |
\(E^{\prime}_{{n_{i} }}\) | 0.0630 | 0.1347 | 0.2080 |
\(H^{\prime}_{{e_{i} }}\) | 0.0095 | 0.0158 | 0.0315 |
Normalization | |||
\(\omega\; \left({E}_{{x}_{i}}\right)\) | 0.1634 | 0.2970 | 0.5396 |
\(\omega\; \left({E}_{{n}_{i}}\right)\) | 0.0225 | 0.0459 | 0.0741 |
\(\omega\; \left({H}_{{e}_{i}}\right)\) | 0.0033 | 0.0057 | 0.0110 |
Dimension | Description | Cloud | Weight |
---|---|---|---|
Accessibility | Difficulty in collecting indices | (0.1634, 0.0225, 0.0033) | 0.1634 |
Operability | Difficulty in dealing with indices | (0.2970, 0.0459, 0.0057) | 0.2970 |
Sensitivity | Significant change in indices | (0.5396, 0.0741, 0.0110) | 0.5396 |
Title | Experience | Education | Age | Weight | |
---|---|---|---|---|---|
Expert I | 4 | 3 | 5 | 4 | 0.372 |
Expert II | 4 | 2 | 5 | 4 | 0.349 |
Expert III | 3 | 2 | 4 | 3 | 0.279 |
Parameter | Accessibility | Operability | Sensitivity | |||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|
E-I | E-II | E-III | \({E}_{\mathrm{wa}}\) | E-I | E-II | E-III | \({E}_{\mathrm{wa}}\) | E-I | E-II | E-III | \({E}_{wa}\) | |
X1 | H | RH | H | (0.7477, 0.0477, 0.0143) | H | H | RH | (0.7582, 0.0452, 0.0136) | RH | H | RH | (0.7024, 0.0573, 0.0172) |
X2 | M | RL | M | (0.4477, 0.0477, 0.0143) | RH | H | H | (0.7442, 0.0485, 0.0145) | RH | H | RH | (0.7024, 0.0573, 0.0172) |
X3 | M | RL | M | (0.4477, 0.0477, 0.0143) | RH | RH | M | (0.6082, 0.0593, 0.0178) | RH | RH | H | (0.6919, 0.0593, 0.0178) |
X4 | M | RL | M | (0.4477, 0.0477, 0.0143) | RH | M | RH | (0.5977, 0.0573, 0.0172) | M | M | RH | (0.5419, 0.0452, 0.0136) |
X5 | RL | RL | L | (0.3082, 0.0593, 0.0178) | M | RL | M | (0.4477, 0.0477, 0.0143) | M | M | RL | (0.4582, 0.0452, 0.0136) |
X6 | RL | RL | L | (0.3082, 0.0593, 0.0178) | M | M | RL | (0.4582, 0.0452, 0.0136) | RH | M | RH | (0.5977, 0.0573, 0.0172) |
X7 | RL | RL | L | (0.3082, 0.0593, 0.0178) | RH | M | RH | (0.5977, 0.0573, 0.0172) | RH | RH | H | (0.6919, 0.0593, 0.0178) |
X8 | RL | RL | M | (0.3919, 0.0593, 0.0178) | H | RH | RH | (0.7058, 0.0566, 0.0170) | H | RH | RH | (0.7058, 0.0566, 0.0170) |
X9 | RL | RL | M | (0.3919, 0.0593, 0.0178) | RH | M | M | (0.5558, 0.0485, 0.0145) | RH | RH | H | (0.6919, 0.0593, 0.0178) |
X10 | RL | RL | M | (0.3919, 0.0593, 0.0178) | RH | M | M | (0.5558, 0.0485, 0.0145) | RL | M | RL | (0.4024, 0.0573, 0.0172) |
X11 | RH | M | M | (0.5558, 0.0485, 0.0145) | M | M | RH | (0.5419, 0.0452, 0.0136) | RL | L | RL | (0.2977, 0.0573, 0.0172) |
X12 | RH | M | M | (0.5558, 0.0485, 0.0145) | RH | RH | H | (0.6919, 0.0593, 0.0178) | RH | RH | M | (0.6082, 0.0593, 0.0178) |
X13 | RH | M | M | (0.5558, 0.0485, 0.0145) | RH | RH | RH | (0.6500, 0.0667, 0.0200) | M | RL | RL | (0.4058, 0.0566, 0.0170) |
X14 | RH | M | M | (0.5558, 0.0485, 0.0145) | M | RH | RH | (0.5942, 0.0566, 0.0170) | RH | M | M | (0.5558, 0.0485, 0.0145) |
X15 | M | RL | RL | (0.4058, 0.0566, 0.0170) | H | RH | RH | (0.7058, 0.0566, 0.0170) | RH | RH | H | (0.6919, 0.0593, 0.0178) |
X16 | M | RL | RL | (0.4058, 0.0566, 0.0170) | RH | H | RH | (0.7024, 0.0573, 0.0172) | RH | M | M | (0.5558, 0.0452, 0.0136) |
Parameter | \({C}_{\mathrm{wa}}\) | \({D}^{+}\left({y}_{i} ,{y}^{+}\right)\) | \({\mathrm{D}}^{-}\left({y}_{i} ,{y}^{-}\right)\) | \({D}_{ij}^{*}\) | Ranking | ||
---|---|---|---|---|---|---|---|
X1 | (0.7264, 0.0735, 0.0139) | \({D}^{+}\left({y}_{1} ,{y}^{+}\right)\) | 0.0893 | \({D}^{-}\left({y}_{1} ,{y}^{-}\right)\) | 0.2853 | 0.7616 | 1 |
X2 | (0.6732, 0.0721, 0.0138) | \({D}^{+}\left({y}_{2} ,{y}^{+}\right)\) | 0.1315 | \({D}^{-}\left({y}_{2} ,{y}^{-}\right)\) | 0.2422 | 0.6482 | 2 |
X3 | (0.6271, 0.0700, 0.0141) | \({D}^{+}\left({y}_{3} ,{y}^{+}\right)\) | 0.2041 | \({D}^{-}\left({y}_{3} ,{y}^{-}\right)\) | 0.1737 | 0.4597 | 11 |
X4 | (0.5431, 0.0584, 0.0116) | \({D}^{+}\left({y}_{4} ,{y}^{+}\right)\) | 0.1394 | \({D}^{-}\left({y}_{4} ,{y}^{-}\right)\) | 0.1967 | 0.5852 | 3 |
X5 | (0.4306, 0.0501, 0.0106) | \({D}^{+}\left({y}_{5} ,{y}^{+}\right)\) | 0.1769 | \({D}^{-}\left({y}_{5} ,{y}^{-}\right)\) | 0.1403 | 0.4423 | 12 |
X6 | (0.5090, 0.0607, 0.0127) | \({D}^{+}\left({y}_{6} ,{y}^{+}\right)\) | 0.2099 | \({D}^{-}\left({y}_{6} ,{y}^{-}\right)\) | 0.1896 | 0.4746 | 8 |
X7 | (0.6012, 0.0695, 0.0140) | \({D}^{+}\left({y}_{7} ,{y}^{+}\right)\) | 0.2287 | \({D}^{-}\left({y}_{7} ,{y}^{-}\right)\) | 0.2010 | 0.4678 | 10 |
X8 | (0.6545, 0.0719, 0.0140) | \({D}^{+}\left({y}_{8} , {y}^{+}\right)\) | 0.1890 | \({D}^{-}\left({y}_{8} , {y}^{-}\right)\) | 0.2310 | 0.5500 | 4 |
X9 | (0.6025, 0.0684, 0.0137) | \({D}^{+}\left({y}_{9} ,{y}^{+}\right)\) | 0.1963 | \({D}^{-}\left({y}_{9} ,{y}^{-}\right)\) | 0.2105 | 0.5175 | 7 |
X10 | (0.4462, 0.0536, 0.0120) | \({D}^{+}\left({y}_{10} ,{y}^{+}\right)\) | 0.2441 | \({D}^{-}\left({y}_{10} ,{y}^{-}\right)\) | 0.1389 | 0.3626 | 14 |
X11 | (0.4124, 0.0496, 0.0115) | \({D}^{+}\left({y}_{11} ,{y}^{+}\right)\) | 0.2226 | \({D}^{-}\left({y}_{11} ,{y}^{-}\right)\) | 0.1082 | 0.3270 | 15 |
X12 | (0.6245, 0.0678, 0.0138) | \({D}^{+}\left({y}_{12} ,{y}^{+}\right)\) | 0.2045 | \({D}^{-}\left({y}_{12} ,{y}^{-}\right)\) | 0.1475 | 0.4190 | 13 |
X13 | (0.5028, 0.0578, 0.0123) | \({D}^{+}\left({y}_{13} ,{y}^{+}\right)\) | 0.3699 | \({D}^{-}\left({y}_{13} ,{y}^{-}\right)\) | 0.1466 | 0.2838 | 16 |
X14 | (0.5672, 0.0602, 0.0120) | \({D}^{+}\left({y}_{14} ,{y}^{+}\right)\) | 0.1504 | \({D}^{-}\left({y}_{14} ,{y}^{-}\right)\) | 0.1700 | 0.5305 | 6 |
X15 | (0.6493, 0.0718, 0.0142) | \({D}^{+}\left({y}_{15} ,{y}^{+}\right)\) | 0.2034 | \({D}^{-}\left({y}_{15} ,{y}^{-}\right)\) | 0.1832 | 0.4739 | 9 |
X16 | (0.5748, 0.0623, 0.0123) | \({D}^{+}\left({y}_{16} ,{y}^{+}\right)\) | 0.1710 | \({D}^{-}\left({y}_{16} ,{y}^{-}\right)\) | 0.1935 | 0.5308 | 5 |
Determination of index weight clouds at all levels based on cloud-AHP
Second-level indices | F1 | F2 | F3 | Cloud |
---|---|---|---|---|
F1 | (1,0,0) | (2, 0.33, 0.05) | (2, 0.33, 0.05) | (0.4934, 0.0780, 0.0118) |
F2 | (1/2, 0.33/4, 0.05/4) | (1, 0, 0) | (2, 0.33, 0.05) | (0.1958, 0.0310, 0.0047) |
F3 | (1/2, 0.33/4, 0.05/4) | (1/2, 0.33/4, 0.05/5) | (1, 0, 0) | (0.3108, 0.0492, 0.0074) |
X1 | X2 | X3 | X4 | X5 | X6 | X7 | X8 | X9 | X10 | X11 | X12 | X13 | X14 | X15 | X16 | |
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
Multiply the rows | ||||||||||||||||
\({E}_{{x}_{i}}\) | 0.7264 | 0.6732 | 0.6271 | 0.5431 | 0.4306 | 0.5090 | 0.6012 | 0.6545 | 0.6025 | 0.4462 | 0.4124 | 0.6245 | 0.5028 | 0.5672 | 0.6493 | 0.5748 |
\({E}_{{n}_{i}}\) | 0.0735 | 0.0721 | 0.0700 | 0.0584 | 0.0501 | 0.0607 | 0.0695 | 0.0719 | 0.0684 | 0.0536 | 0.0496 | 0.0678 | 0.0578 | 0.0602 | 0.0718 | 0.0623 |
\({H}_{{e}_{i}}\) | 0.0139 | 0.0138 | 0.0141 | 0.0116 | 0.0106 | 0.0127 | 0.0140 | 0.0140 | 0.0137 | 0.0120 | 0.0115 | 0.0138 | 0.0605 | 0.0120 | 0.0142 | 0.0123 |
Square roots | ||||||||||||||||
\(E^{\prime}_{{x_{i} }}\) | 0.9685 | 0.9612 | 0.9544 | 0.9408 | 0.9192 | 0.9347 | 0.9504 | 0.9585 | 0.9506 | 0.9225 | 0.8014 | 0.8890 | 0.8421 | 0.8678 | 0.8058 | 0.7582 |
\(E^{\prime}_{{n_{i} }}\) | 0.0310 | 0.0326 | 0.0337 | 0.0320 | 0.0338 | 0.0352 | 0.0348 | 0.0333 | 0.0341 | 0.0351 | 0.0482 | 0.0482 | 0.0484 | 0.0461 | 0.0630 | 0.0581 |
\(H^{\prime}_{{e_{i} }}\) | 0.0058 | 0.0062 | 0.0068 | 0.0064 | 0.0072 | 0.0074 | 0.0070 | 0.0065 | 0.0069 | 0.0079 | 0.0115 | 0.0098 | 0.0506 | 0.0092 | 0.0125 | 0.0114 |
Normalization | ||||||||||||||||
\(\omega \left({E}_{{x}_{i}}\right)\) | 0.1024 | 0.1016 | 0.1009 | 0.0994 | 0.0972 | 0.0988 | 0.1005 | 0.1013 | 0.1005 | 0.0975 | 0.2357 | 0.2614 | 0.2477 | 0.2552 | 0.5152 | 0.4848 |
\(\omega \left({E}_{{n}_{i}}\right)\) | 0.0035 | 0.0036 | 0.0037 | 0.0036 | 0.0037 | 0.0039 | 0.0038 | 0.0037 | 0.0038 | 0.0039 | 0.0156 | 0.0160 | 0.0158 | 0.0153 | 0.0492 | 0.0457 |
\(\omega \left({H}_{{e}_{i}}\right)\) | 0.0007 | 0.0007 | 0.0008 | 0.0007 | 0.0008 | 0.0008 | 0.0008 | 0.0007 | 0.0008 | 0.0009 | 0.0036 | 0.0033 | 0.0034 | 0.0031 | 0.0097 | 0.0090 |
\(\mathrm{C}.\mathrm{R}.\) | 0.0008 < 0.1 | 0.0101 < 0.1 | 0.0187 < 0.1 |
Index | Cloud | Weight | Index | Cloud | Weight |
---|---|---|---|---|---|
F1 | (0.4934, 0.0780, 0.0118) | 0.4934 | X1 | (0.1024, 0.0035, 0.0007) | 0.1024 |
X2 | (0.1016, 0.0036, 0.0007) | 0.1016 | |||
X3 | (0.1009, 0.0037, 0.0008) | 0.1009 | |||
X4 | (0.0994, 0.0036, 0.0007) | 0.0994 | |||
X5 | (0.0972, 0.0037, 0.0008) | 0.0972 | |||
X6 | (0.0988, 0.0039, 0.0008) | 0.0988 | |||
X7 | (0.1005, 0.0038, 0.0008) | 0.1005 | |||
X8 | (0.1013, 0.0037, 0.0007) | 0.1013 | |||
X9 | (0.1005, 0.0038, 0.0008) | 0.1005 | |||
X10 | (0.0975, 0.0039, 0.0009) | 0.0975 | |||
F2 | (0.1958, 0.0310, 0.0047) | 0.1958 | X11 | (0.2357, 0.0156, 0.0036) | 0.2357 |
X12 | (0.2614, 0.0160, 0.0033) | 0.2614 | |||
X13 | (0.2477, 0.0158, 0.0034) | 0.2477 | |||
X14 | (0.2552, 0.0153, 0.0031) | 0.2552 | |||
F3 | (0.3108, 0.0492, 0.0074) | 0.3108 | X15 | (0.5152, 0.0492, 0.0097) | 0.5152 |
X16 | (0.4848, 0.0457, 0.0090) | 0.4848 |
Evaluation of mental load state based on CM
Index | Unit | First-level mental load | Second-level mental load | Third-level mental load | Fourth-level mental load |
---|---|---|---|---|---|
X1 | bpm | < 86 | 86–96 | 97–108 | > 109 |
X2 | ms | > 0.811 | 0.661–0.811 | 0.565–0.660 | < 0.565 |
X3 | ms | > 0.265 | 0.164–0.265 | 0.057–0.163 | < 0.057 |
X4 | – | < 2.86 | 2.86–12.49 | 12.50–40.14 | > 40.14 |
X5 | Hz | < 49.97 | 49.97–68.25 | 68.26–83.06 | > 83.06 |
X6 | Hz | < 36.82 | 36.82–82.30 | 82.31–173.34 | > 173.34 |
X7 | Hz | < 47.02 | 47.02–60.32 | 60.33–69.48 | > 69.48 |
X8 | mm | < 3.682 | 3.682–4.681 | 4.682–5.783 | > 5.783 |
X9 | ms | > 820 | 419.7–820 | 255.6–419.6 | < 255.6 |
X10 | Count/s | > 570 | 274.6–570 | 103–274.5 | < 103 |
X11 | Point | 1 | 2 | 3 | 4 |
X12 | Point | 1 | 2 | 3 | 4 |
X13 | Point | 1 | 2 | 3 | 4 |
X14 | Point | 1 | 2 | 3 | 4 |
X15 | s | < − 0.311 | − 0.311–0.499 | 0.500–1.383 | > 1.383 |
X16 | % | < − 0.007 | − 0.007–0.288 | 0.289–1.489 | > 1.489 |
Participants | X1 | X2 | X3 | X4 | X5 | X6 | X7 | X8 | X9 | X10 | X11 |
---|---|---|---|---|---|---|---|---|---|---|---|
P1 | 4 | 4 | 4 | 2 | 3 | 2 | 2 | 3 | 4 | 1 | 2 |
P2 | 4 | 4 | 4 | 2 | 2 | 2 | 3 | 4 | 4 | 2 | 3 |
P3 | 2 | 3 | 3 | 2 | 4 | 4 | 3 | 3 | 3 | 2 | 3 |
P4 | 3 | 3 | 3 | 3 | 3 | 3 | 2 | 2 | 4 | 2 | 3 |
P5 | 1 | 2 | 4 | 2 | 2 | 2 | 3 | 2 | 3 | 3 | 2 |
P6 | 2 | 3 | 1 | 4 | 1 | 2 | 2 | 1 | 3 | 3 | 3 |
P7 | 3 | 3 | 4 | 2 | 1 | 1 | 2 | 2 | 3 | 2 | 3 |
P8 | 2 | 3 | 2 | 4 | 2 | 2 | 4 | 2 | 3 | 2 | 2 |
P9 | 3 | 3 | 4 | 1 | 4 | 3 | 4 | 3 | 3 | 2 | 3 |
P10 | 4 | 4 | 3 | 1 | 1 | 1 | 1 | 4 | 4 | 2 | 3 |
P11 | 2 | 2 | 4 | 1 | 2 | 2 | 2 | 2 | 3 | 3 | 2 |
P12 | 1 | 1 | 3 | 2 | 3 | 3 | 3 | 3 | 2 | 3 | 3 |
P13 | 3 | 4 | 3 | 1 | 3 | 3 | 2 | 4 | 3 | 3 | 3 |
P14 | 4 | 4 | 4 | 2 | 2 | 2 | 2 | 3 | 3 | 2 | 2 |
P15 | 2 | 2 | 3 | 4 | 2 | 2 | 3 | 3 | 3 | 3 | 2 |
P16 | 1 | 2 | 4 | 1 | 2 | 2 | 3 | 3 | 3 | 2 | 2 |
P17 | 3 | 4 | 4 | 2 | 1 | 1 | 1 | 2 | 1 | 2 | 4 |
P18 | 2 | 3 | 4 | 3 | 2 | 2 | 3 | 3 | 3 | 1 | 2 |
P19 | 2 | 2 | 3 | 2 | 3 | 3 | 3 | 3 | 4 | 2 | 2 |
P20 | 3 | 3 | 3 | 1 | 2 | 2 | 2 | 3 | 2 | 3 | 3 |
X12 | X13 | X14 | X15 | X16 | F1- grate cloud | F2- grate cloud | F3-grate cloud | ML-grate cloud | \({X}_{\mathrm{max}}\) | EC | FC | SQ |
---|---|---|---|---|---|---|---|---|---|---|---|---|
2 | 2 | 1 | 4 | 4 | (0.2924, 0.0062, 0.0013) | (0.4356, 0.0205, 0.0044) | (2.0019, 0.0951, 0.0111) | (1.6867, 0.1099, 0.0095) | 2.0164 | IV | IV | III |
1 | 2 | 2 | 2 | 1 | (0.3128, 0.0065, 0.0013) | (0.4879, 0.0215, 0.0046) | (1.0009, 0.0672, 0.0077) | (0.8468, 0.0849, 0.0062) | 1.1015 | III | III | III |
3 | 4 | 3 | 2 | 2 | (0.2894, 0.0063, 0.0013) | (0.8124, 0.0282, 0.0060) | (1.0009, 0.0672, 0.0077) | (0.8908, 0.0886, 0.0067) | 1.1565 | III | III | IV |
4 | 3 | 3 | 2 | 2 | (0.2803, 0.0062, 0.0013) | (0.8195, 0.0284, 0.0060) | (1.0009, 0.0672, 0.0077) | (0.8922, 0.0885, 0.0081) | 1.1577 | III | III | IV |
2 | 1 | 2 | 2 | 1 | (0.2396, 0.0057, 0.0012) | (0.4394, 0.0206, 0.0044) | (0.7659, 0.0583, 0.0075) | (0.6540, 0.0749, 0.0063) | 0.8788 | II | II | II |
3 | 3 | 3 | 1 | 2 | (0.2199, 0.0054, 0.0011) | (0.7511, 0.0272, 0.0058) | (0.7355, 0.0564, 0.0055) | (0.6853, 0.0765, 0.0051) | 0.9148 | II | III | III |
4 | 3 | 3 | 3 | 2 | (0.2321, 0.0055, 0.0011) | (0.8195, 0.0284, 0.0060) | (1.2664, 0.0755, 0.0093) | (1.0993, 0.0953, 0.0080) | 1.3851 | III | III | III |
3 | 1 | 2 | 2 | 1 | (0.2604, 0.0059, 0.0012) | (0.5078, 0.0220, 0.0047) | (0.7659, 0.0583, 0.0075) | (0.6638, 0.0761, 0.0063) | 0.8920 | II | III | II |
3 | 2 | 3 | 3 | 2 | (0.3005, 0.0064, 0.0013) | (0.6898, 0.0260, 0.0055) | (1.2664, 0.0755, 0.0093) | (1.0782, 0.0951, 0.0079) | 1.3634 | III | III | III |
4 | 3 | 3 | 2 | 2 | (0.2534, 0.0056, 0.0011) | (0.8195, 0.0284, 0.0060) | (1.0009, 0.0672, 0.0077) | (0.8952, 0.0877, 0.0067) | 1.1583 | III | III | IV |
2 | 3 | 2 | 3 | 3 | (0.2301, 0.0056, 0.0011) | (0.5621, 0.0234, 0.0050) | (1.5014, 0.0823, 0.0095) | (1.2643, 0.0988, 0.0082) | 1.5606 | III | III | III |
2 | 1 | 1 | 4 | 2 | (0.2385, 0.0057, 0.0012) | (0.4298, 0.0200, 0.0043) | (1.5318, 0.0825, 0.0107) | (1.2864, 0.0971, 0.0091) | 1.5777 | III | III | III |
3 | 4 | 2 | 1 | 1 | (0.2908, 0.0063, 0.0013) | (0.7473, 0.0270, 0.0058) | (0.5005, 0.0475, 0.0053) | (0.5288, 0.0694, 0.0049) | 0.7371 | II | III | IV |
2 | 2 | 2 | 1 | 1 | (0.2824, 0.0062, 0.0012) | (0.5007, 0.0222, 0.0047) | (0.5005, 0.0475, 0.0053) | (0.4706, 0.0665, 0.0047) | 0.6700 | II | II | II |
3 | 3 | 2 | 3 | 1 | (0.2700, 0.0061, 0.0012) | (0.6304, 0.0248, 0.0053) | (1.0314, 0.0666, 0.0091) | (0.8833, 0.0857, 0.0076) | 1.1404 | III | III | III |
2 | 3 | 2 | 3 | 3 | (0.2305, 0.0056, 0.0011) | (0.5621, 0.0234, 0.0050) | (1.5014, 0.0823, 0.0095) | (1.2647, 0.0987, 0.0082) | 1.5609 | III | III | III |
3 | 3 | 3 | 3 | 2 | (0.2121, 0.0052, 0.0010) | (0.8067, 0.0281, 0.0060) | (1.2664, 0.0755, 0.0093) | (1.1004, 0.0946, 0.0081) | 1.3843 | III | III | IV |
3 | 3 | 4 | 1 | 2 | (0.2616, 0.0059, 0.0012) | (0.7607, 0.0272, 0.0057) | (0.7355, 0.0564, 0.0055) | (0.6869, 0.0773, 0.0051) | 0.9189 | II | III | III |
2 | 1 | 2 | 3 | 2 | (0.2700, 0.0061, 0.0012) | (0.4394, 0.0206, 0.0044) | (1.2664, 0.0755, 0.0093) | (1.0591, 0.0915, 0.0079) | 1.3336 | III | III | II |
4 | 3 | 2 | 3 | 2 | (0.2409, 0.0057, 0.0012) | (0.7543, 0.0271, 0.0058) | (1.2664, 0.0755, 0.0093) | (1.0890, 0.0948, 0.0080) | 1.3733 | III | III | III |
Mental load level | ML-grate cloud | Value range | Linguistic term |
---|---|---|---|
I | (0.4241, 0.0590, 0.0046) | 0 ≤ Ψ ≤ 0.6012 | Very low load |
II | (0.8482, 0.0835, 0.0066) | 0.6012 < Ψ ≤ 1.0987 | Low load |
III | (1.2722, 0.1023, 0.0082) | 1.0987 < Ψ ≤ 1.5790 | Medium load |
IV | (1.6963, 0.1181, 0.0095) | 1.5790 < Ψ ≤ 2.0506 | High load |