Cognitive Human Factors and Forensic Document Examiner Methods and Procedures

Mara L. Merlino; Veronica B. Dahir; Charles P. Edwards; Derek L. Hammond; Tierra Freeman-Taylor; Adrian Dyer; Bryan J. Found

doi:10.69525/jasqde.262

Cognitive Human Factors and Forensic Document Examiner Methods and Procedures

Journal of the American Society of Questioned Document Examiners

Volume 23 (2020): Issue 1

By: Mara L. Merlino, Veronica B. Dahir, Charles P. Edwards, Derek L. Hammond, Tierra Freeman-Taylor, Adrian Dyer and Bryan J. Found

Open Access

|Jun 2020

Figures & Tables

This “gaze plot” of a recorded comparison shows an example of a visual context effect. Note that the position of the two known signatures beneath the first name (top and bottom left [AGD1]) shows that this FDE fixated to a greater extent on those two known signatures, while the positioning of the other two known signatures under “LaBarbera” (top and bottom right) attracted a greater number of fixations on those known signatures.

Genuine Terry Lu signature with “eyelet” in the T, which appeared only in this genuine questioned signature. The T in the specimen on the right is a two-stroke letter form in which the staff and the crossbar are not connected.

An example of the stimulus sequence displayed on the eye-tracking system. Each of the four images in the figure were displayed on separate screen. Stimulus 1 is a “fixation cross” where FDEs were instructed to center their gaze so that each comparison began in the same location. After being displayed for 3 seconds, the screen changed to Stimulus 2, the known signatures. FDEs viewed this screen for as long as they chose. When they were ready to complete the comparison, they indicated so verbally to the research assistant, who then changed the screen to Stimulus 3, a second fixation cross. After 3 seconds, the screen automatically changed to Stimulus 4, the questioned/known comparison. FDEs again viewed this screen for as long as they chose. When they completed each comparison they verbally indicated this to the research assistant, who exited the comparison screen. Fixations were recorded from the time the screen changed to the signatures until the research assistant exited that screen.

The participant is seated 57 cm away from the eye tracking unit. The operator, seated to the participant’s right, controls the presentation of stimuli and records the participant’s verbal responses. The eye-tracking protocols were conducted in low lighting for maximum pupil dilation, which improves the quality of the gaze data. In this image a gaze plot, or map of the fixation locations and the scan path, is displayed. The image displayed on the operator’s screen is a gaze plot created from filtered fixation data.

Image 1 (upper left) is an example of a signature comparison stimulus displayed on the eye-tracking screen. Image 2 (upper right) is a “gaze plot” visualization of the visual behavior of the FDE. Each dot represents a “fixation” recorded by the system when the FDE’s eye movement drops below the threshold described above. The lines represent visual “saccades,” or eye movement between fixations. The fixations are sequentially numbered by the eye-tracker to enable researchers to track the deployment of cognitive attention resources. Image 3 (lower left) is a “heat map” visualization of the areas that received to most attention from the FDE. Image 4 (lower right) demonstrates the areas of interest (AOIs) developed from the heat map.

Configuration 1 includes all four known signatures. In configuration 2 the fixation counts and for known signatures 1 and 2 are combined in AOI Top, and 3 and 4 are combined in AOI Bottom. In configuration 3, fixation counts for signatures 1 and 3 are combined in AOI Left, 2 and 4 are combined in AOI Right.

The statistically significant difference in the mean number of fixations demonstrated in this figure are consistent with a top-to-bottom and left-to-right viewing pattern. Fixations are highest in the upper left known signature (Known 1) then in the upper right signature (Known 2). Fixation count in Known 3 is significantly lower than Known 2, but significantly higher than in Known 4. Fixation count is significantly higher in the combined areas of Known 1 and 2 (Top), than in Known 3 and 4 (Bottom). Fixation count is also significantly higher in the combined areas of Known 1 and 3 (Left) than in Known 2 and 4 (Bottom). It is important to note that fixation counts are filtered data that identify where the FDE’s gaze has slowed enough to meet the 50-pixel/100 ms threshold requirement. It should not be inferred from these data that FDEs failed to look at other areas where fixations were not indicated by the filter.

Table 1

Mean Fixation Count by Area of Interest

							95% Confidence Interval
Fixation Count AOIs	N	M	SD	t	df	P	Lower CI	Upper CI
FC Knowns 1, 2 (top)	1650	24.47	22.95	26.92	1649	< .001	9.54	11.04
FC Knowns 3, 4 (bottom)	1650	14.18	19.07
FC Knowns 1, 3 (left)	1650	20.1	21.5	4.4	1649	< .001	0.86	2.24
FC Knowns 2, 4 (right)	1650	18.55	20.25
Fixation Count AOIs	N	M	SD	χ²	df	p	Mean Rank
FC Known 1	1652	13.29	13.05	1713.73	3	< .001	3.28
FC Known 2	1650	11.16	11.23				2.95
FC Known 3	1650	6.8	10.51				1.85
FC Known 4	1650	7.39	11.33				1.92

AOIs in which the highest mean fixation counts are highlighted. Areas of darker shading indicate AOIs with the higher fixation counts. All mean differences are statistically significant, as indicated in Table 1.

Table 2

Mean Fixation Count by Signature Type

Signature Type
								95% Confidence Interval
	Sig Type	N	M	SD	t	df	p	Lower CI	Upper CI
FC Knowns 1, 2 (top)	Text	1008	25.64	24.33	2.701	1526	0.007	0.824	5.195
	Stylized	642	22.63	20.49
FC Knowns 3, 4 (bottom)	Text	1008	15.03	20.98	2.429	1612	0.015	0.421	3.957
	Stylized	642	12.85	15.53
FC Knowns 1, 3 (left)	Text	1008	21.08	22.88	2.416	1535	0.016	0.474	4.559
	Stylized	642	18.56	19.05
FC Knowns 2, 4 (right)	Text	1008	19.60	22.11	2.788	1597	0.005	0.795	4.568
	Stylized	642	16.91	16.81
FC Known 1	Text	1010	14.14	13.87	3.467	1538	0.001	0.948	3.419
	Stylized	642	11.95	11.51
FC Known 2	Text	1008	11.48	11.84	1.454	1508	0.146	-0.278	1.874
	Stylized	642	10.68	10.19
FC Known 3	Text	1008	6.91	11.36	0.574	1648	0.566	-0.737	1.346
	Stylized	642	6.61	9.02
FC Known 4	Text	1008	8.12	12.99	3.654	1646	< .001	0.873	2.896
	Stylized	642	6.24	7.96

Table 3

Regression Coefficients for Predictors of Signature Type

						95% Confidence Interval
Analysis 1: Top/Bottom	B	Wald	df	p	Odds	Lower CI	Upper CI
FC Knowns 1, 2 (top)	-0.005	1.79	1	0.181	0.995	0.989	1.002
FC Knowns 3, 4 (bottom)	-0.002	0.275	1	0.6	0.998	0.99	1.006

Table 4

Regression Coefficients for Predictors of Signature Type

						95% Confidence Interval
Analysis 2: Left/Right	B	Wald	df	p	Odds	Lower CI	Upper CI
FC Knowns 1, 3 (left)	-0.002	0.212	1	0.646	0.998	0.991	1.006
FC Knowns 2, 4 (right)	-0.005	1.749	1	0.186	0.995	0.986	1.003

Table 5

Regression Coefficients for Predictors of Signature Type

						95% Confidence Interval
Analysis 3: All Knowns	B	Wald	df	p	Odds	Lower CI	Upper CI
FC Known 1	-0.028	13.564	1	< .001	0.973	0.959	0.987
FC Known 2	0.021	6.774	1	0.009	1.021	1.005	1.038
FC Known 3	0.018	6.258	1	0.012	1.018	1.004	1.033
FC Known 4	-0.022	7.865	1	0.005	0.978	0.963	0.993

Table 6

Mean Fixation Count by Signature Complexity

								95% Confidence Interval
	Comp	N	M	SD	t	df	p	Lower CI	Upper CI
FC Knowns 1, 2 (top)	High	690	24.22	22.69	-0.376	1648	0.707	-2.678	1.817
	Low	960	24.65	23.15
FC Knowns 3, 4 (bottom)	High	690	15.79	22.67	2.750	1158	0.006	0.791	4.732
	Low	960	13.03	15.90
FC Knowns 1, 3 (left)	High	690	20.33	22.75	0.362	1648	0.717	-1.716	2.494
	Low	960	19.94	20.56
FC Knowns 2,4 (right)	High	690	19.68	22.36	1.866	1309	0.062	-0.100	3.984
	Low	960	17.74	18.55
FC Known 1	High	690	13.35	13.16	0.168	1650	0.867	-1.168	1.386
	Low	962	13.24	12.97
FC Known 2	High	690	10.87	10.95	-0.914	1648	0.361	- 1.612	0.587
	Low	960	11.38	11.43
FC Known 3	High	690	6.97	12.24	0.586	1648	0.558	-0.722	1.336
	Low	960	6.67	9.07
FC Known 4	High	690	8.82	14.48	4.012	1007	< .001	1.254	3.655
	Low	960	6.36	8.23

Table 7

Regression Coefficients for Predictors of Signature Complexity

						95% Confidence Interval
Analysis 1: Top/Bottom	B	Wald	df	p	Odds	Lower CI	Upper CI
FC Knowns 1, 2 (top)	0.014	14.281	1	< .001	1.014	1.007	1.021
FC Knowns 3, 4 (bottom)	-0.021	20.298	1	< .001	0.979	0.971	0.988

Table 8

Regression Coefficients for Predictors of Signature Complexity

						95% Confidence Interval
Analysis 2: Left/Right	B	Wald	df	p	Odds	Lower CI	Upper CI
FC Knowns 1, 3 (left)	0.006	2.913	1	0.088	1.006	0.999	1.014
FC Knowns 2, 4 (right)	-0.01	6.325	1	0.012	0.99	0.983	0.998

Table 9

Regression Coefficients for Predictors of Signature Complexity

						95% Confidence Interval
Analysis 3: All Knowns	B	Wald	df	p	Odds	Lower CI	Upper CI
FC Known 1	< .001	< .001	1	0.990	1.000	0.986	1.014
FC Known 2	0.031	13.870	1	< .001	1.031	1.015	1.048
FC Known 3	0.003	0.189	1	0.664	1.003	0.990	1.016
FC Known 4	-0.046	31.831	1	< .001	0.955	0.939	0.970

Table 10

Mean Fixation Count by Ground Truth

Ground Truth
								95% Confidence Interval
	Truth	N	M	SD	t	df	p	Lower CI	Upper CI
FC Knowns 1, 2 (top)	Genuine	686	28.64	25.18	6.100	1291	< .001	4.844	9.437
	Non	964	21.50	20.73
FC Knowns 3, 4 (bottom)	Genuine	686	17.67	20.65	6.172	1316	< .001	4.077	7.876
	Non	964	11.70	17.45
FC Knowns 1, 3 (left)	Genuine	686	24.32	24.49	6.504	1214	< .001	5.038	9.391
	Non	964	17.10	18.53
FC Knowns 2,4 (right)	Genuine	686	22.00	21.04	5.811	1396	< .001	3.910	7.896
	Non	964	16.10	19.31
FC Known 1	Genuine	688	15.17	14.11	4.852	1331	< .001	1.918	4.521
	Non	964	11.95	12.06
FC Known 2	Genuine	686	13.43	12.55	6.740	1250	< .001	2.749	5.006
	Non	964	9.55	9.89
FC Known 3	Genuine	686	9.10	12.90	7.103	1056	< .001	2.860	5.042
	Non	964	5.15	8.01
FC Known 4	Genuine	686	8.57	9.96	3.592	1648	< .001	0.920	3.132
	Non	964	6.55	12.15

Table 11

Regression Coefficients for Predictors of Ground Truth

						95% Confidence Interval
Analysis 1: Top/Bottom	B	Wald	df	p	Odds	Lower CI	Upper CI
FC Knowns 1, 2 (top)	-0.007	4.432	1	0.035	0.993	0.986	0.999
FC Knowns 3, 4 (bottom)	-0.011	5.998	1	0.014	0.989	0.981	0.998

Table 12

Regression Coefficients for Predictors of Ground Truth

						95% Confidence Interval
Analysis 2: Left/Right	B	Wald	df	p	Odds	Lower CI	Upper CI
FC Knowns 1, 3 (left)	-0.014	12.289	1	< .001	0.986	0.978	0.994
FC Knowns 2, 4 (right)	-0.004	0.824	1	0.364	0.996	0.989	1.004

Table 13

Regression Coefficients for Predictors of Ground Truth

						95% Confidence Interval
Analysis 3: All Knowns	B	Wald	df	p	Odds	Lower CI	Upper CI
FC Known 1 (top left)	0.021	8.341	1	0.004	1.022	1.007	1.036
FC Known 2 (top right)	-0.033	16.553	1	< .001	0.967	0.952	0.983
FC Known 3 (bottom left)	-0.050	30.359	1	< .001	0.951	0.934	0.968
FC Known 4 (bottom right)	0.012	3.550	1	0.060	1.012	1.000	1.024

Table 14

Mean Fixation Count by FDE Decision Accuracy

								95% Confidence Interval
	Accuracy	N	M	SD	t	df	p	Lower CI	Upper CI
FC Knowns 1, 2 (top)	Accurate	1413	22.90	22.26	-6.380	303	< .001	-14.315	- 7.566
	Mislead	237	33.84	24.78
FC Knowns 3, 4 (bottom)	Accurate	1413	13.21	19.06	-5.079	1648	< .001	-9.354	-4.142
	Mislead	237	19.96	18.15
FC Knowns 1, 3 (left)	Accurate	1413	18.71	21.07	-6.234	311	< .001	-12.699	-6.606
	Mislead	237	28.37	22.22
FC Knowns 2,4 (right)	Accurate	1413	17.40	19.96	-5.573	315	< .001	-10.874	- 5.199
	Mislead	237	25.43	20.64
FC Known 1	Accurate	1414	12.44	12.72	-6.135	308	< .001	-7.773	-3.998
	Mislead	238	18.33	13.85
FC Known 2	Accurate	1413	10.45	10.87	- 5.844	300	< .001	- 6.665	-3.307
	Mislead	237	15.43	12.36
FC Known 3	Accurate	1413	6.26	10.44	-5.057	321	< .001	-5.137	-2.259
	Mislead	237	9.96	10.41
FC Known 4	Accurate	1413	6.95	11.50	-4.284	352	< .001	-4.451	- 1.650
	Mislead	237	10.00	9.90

Table 15

Regression Coefficients for Predictors of Decision Accuracy

						95% Confidence Interval
Analysis 1: Top/Bottom	B	Wald	df	p	Odds	Lower CI	Upper CI
FC Knowns 1 and 2 (top)	0.017	18.015	1	< .001	1.017	1.009	1.024
FC Knowns 3 and 4 (bottom)	< .001	0.002	1	0.961	1.000	0.991	1.009

Table 16

Regression Coefficients for Predictors of Decision Accuracy

						95% Confidence Interval
Analysis 2: Left/Right	B	Wald	df	p	Odds	Lower CI	Upper CI
FC Knowns 1 and 3 (left)	0.013	8.101	1	0.004	1.013	1.004	1.022
FC Knowns 2 and 4 (right)	0.005	1.352	1	0.245	1.005	0.996	1.015

Table 17

Regression Coefficients for Predictors of Decision Accuracy

						95% Confidence Interval
Analysis 3: All Knowns	B	Wald	df	p	Odds	Lower CI	Upper CI
FC Known 1	0.016	3.776	1	0.052	1.016	1.000	1.033
FC Known 2	0.017	3.063	1	0.080	1.017	0.998	1.036
FC Known 3	0.005	0.374	1	0.541	1.005	0.99	1.019
FC Known 4	-0.004	0.272	1	0.602	0.996	0.981	1.011

Table 18

Regression Coefficients for Decision Accuracy Predictors

						95% Confidence Interval
Predictor Variables	B	Wald	df	p	Odds Ratio	Lower CI	Upper CI
Signature Type	-0.090	1.293	1	0.256	0.914	0.782	1.068
Complexity	0.229	1.878	1	0.171	1.258	0.906	1.746
Ground Truth	-2.699	153.035	1	< .001	0.067	0.044	0.103
FC Known 1	0.027	8.125	1	0.004	1.027	1.008	1.047
FC Known 2	< .001	< .001	1	0.989	1.000	0.980	1.021
FC Known 3	-0.010	1.281	1	0.258	0.990	0.973	1.007
FC Known 4	0.003	0.082	1	0.775	1.003	0.983	1.023

References

Authors

Metrics

Articles in this issue

DOI: https://doi.org/10.69525/jasqde.262 | Journal eISSN: 1524-7287

Journal RSS Feed

Language: English

Page range: 9 - 30

Published on: Jun 1, 2020

Published by: American Society of Questioned Document Examiners

In partnership with: Paradigm Publishing Services

© 2020 Mara L. Merlino, Veronica B. Dahir, Charles P. Edwards, Derek L. Hammond, Tierra Freeman-Taylor, Adrian Dyer, Bryan J. Found, published by American Society of Questioned Document Examiners
This work is licensed under the Creative Commons Attribution 4.0 License.

Volume 23 (2020): Issue 1

Cognitive Human Factors and Forensic Document Examiner Methods and Procedures

Figures & Tables

Figure 1

Figure 2

Figure 3

Figure 4

Figure 5

Figure 6

Figure 7

Table 1

Figure 8

Table 2

Table 3

Table 4

Table 5

Table 6

Table 7

Table 8

Table 9

Table 10

Table 11

Table 12

Table 13

Table 14

Table 15

Table 16

Table 17

Table 18

Paradigm

My account