Single-digit fingerprint analysis for hand determination: A study of twinned loops

Abstract

In fingerprint analysis, the determination of hand (right or left) is one of the keys to resolving questions regarding the identity of the donor of the print. It is rare to encounter a complete set of 10-digit fingerprints from the scene of a crime. Although vital and imperative, except for a few studies on whorl patterns, the use of single-digit prints and patterns to ascertain the hand of the donor is scarcely reported in the literature. This research describes a novel approach whereby an analysis of twinned loops was carried out to identify the various parameters that may be helpful in ascertaining the hand of the donor. Bilateral rolled fingerprints from 180 healthy consenting adults belonging to a heterogeneous population of central India were collected. Out of the total of 1800 prints taken, 100 twinned loops (50 on the right hand and 50 on the left hand) were analysed. The following six parameters were considered: the slope of the flow of the apex ridges, the distance between the left delta and the ascending core, the distance between the right delta and the ascending core, mid-core position, the position of the loop and ridge tracing. On applying the chi-square test, the results were found to be statistically significant. Therefore, these parameters were found suitable for the determination of the hand from a single twinned-loop print.

Keywords

Single-digit print twinned loop right hand left hand fingerprint analysis crime

Introduction

Fingerprints are the impressions of friction ridges on the distal phalanges of the fingers and thumb. They are often the most important means of identification found at various crime scenes, such as murder, theft, dacoity (i.e. banditry), rape, burglary, property dispute cases and questioned documents.^1–7 Fingerprints provide crucial evidence that can disseminate essential information using various dermatoglyphic features, including pattern types, ridge count, ridge density and fingertip features.^8–21

At crime scenes, fingerprints are often not found in a logical sequence. So, it can be challenging to determine whether the print is from the right or left hand.^22–26 Determination of the hand (left or right) of a print allows an investigator to reduce the pool of suspects.^23,24,26 It may not assist with individualisation per se, but it can offer new avenues for investigation. Fingerprints contain ridges and furrows that form various ridge characteristics that permit the development of different parameters and features that may help to establish the hand of the donor. The use of fingerprint-matching algorithms helps to reduce the time of fingerprint identification once the hand of the donor is established.²⁷

Literature dealing with the study of parameters for the determination of the hand of a single-digit fingerprint is scarce. While there are studies that deal with whorl patterns,^22–26,28 only a few include twinned-loop patterns^22,25,28 and study limited parameters. Therefore, this work aimed to study the various parameters in twinned-loop fingerprint patterns to ascertain the hand (left or right).

Methodology

Sample collection

The study was carried out on a heterogeneous population of central India. A total of 180 healthy adults aged between 18 and 60 years who were free from any deformities and disease (such as leprosy, scars or lacerations) affecting the fingers were included in the study.

The subjects were randomly selected. The purpose of the study was explained to them, and they were given the opportunity to ask questions and to clarify any doubts they may have had. Informed written consent was taken from subjects before they were enrolled in the study in accordance with the Declaration of Helsinki. Prints were then collected in an anonymised format.

As per the established procedure, rolled prints were taken.²⁶ The prints were taken in duplicate in order to avoid any uncertainty at any later point. In this study, twinned loops are considered to study the following parameter to verify the usefulness in the identification of hand. Henry’s Classification system was used. Out of the total of 1800 fingerprints (900 on the right hand and 900 on the left hand) collected, six parameters were studied in 100 twinned loops (50 on the right hand and 50 on the left hand).

The study was approved by the University Research Committee and was conducted in compliance with their ethical standards.

Parameters of analysis

Slope of apex ridge

The slope of the apex ridges in terms of their inclination towards the right side of the print is termed as right slopping, while their propensity towards the left side of the print is termed as left slopping.^22,26

Distance between left delta and ascending core

The distance between the core of the ascending loop and the left delta was measured.

Distance between right delta and ascending core

The distance between the core of the ascending loop and the right delta was measured.

Mid-core position

The position of the midpoint of the line drawn between the cores of both the loops relative to the vertical line that crosses the delta line was noted (i.e. right, middle or left).²⁵

Position of the ascending loop

The location of the ascending loop with the perpendicular bi-sector drawn on the delta line (right side, left side or middle) was noted.

Ridge tracing

Ridge tracing beginning from the left delta to the right delta was done, and the result was noted (i.e. inner, meeting or outer).^6,7,24,26

Statistical analysis

Statistical analyses were undertaken by applying chi-square tests (at p < 0.01 significance level).

Result and discussion

In this study, 100 samples (i.e. 50 samples belonging to the right hand and 50 belonging to the left hand) with twinned-loop patterns were analysed with the following parameters: the direction of flow of the apex ridge, the distance between the left delta and the ascending core, the distance between the right delta and the ascending core, the mid-core position, the position of the ascending loop and ridge tracing. The results, as observed, are described in Table 1.

Table 1.

Showing the parameters used for the determination of hand from fingerprints with a twinned-loop pattern.

	1		2			3			4			5			6
	Slope of the apex ridges		Distance						Position						Tracing
	Slope of the apex ridges		Left delta to ascending core			Right delta to ascending core			Mid-core position			Position of the ascending loop			Tracing
	LS	RS	G	E	L	G	E	L	LS	Mi	RS	LS	Mi	RS	I	M	O
Left hand
n (N=50)	44	6	4	1	45	45	1	4	43	2	5	46	1	3	48	1	1
%	88	12	8	2	90	90	2	8	86	4	10	92	2	6	96	2	2
Right Hand
n (N=50)	6	44	44	1	5	5	1	44	3	3	44	3	3	44	4	1	45
%	12	88	88	2	10	10	2	88	6	6	88	6	6	88	8	2	90
Chi-square	57.76		65.33			65.33			66.02			74.50			79.32
p-Value*	<0.00001		<0.00001			<0.00001			<0.00001			<0.00001			<0.00001

*p < 0.01.

LS: left side; RS: right side; G: greater; E: equal; L: lesser; Mi: middle; I: inner; M: meeting; O: outer.

All of the studied parameters of the left-hand and right-hand twinned loops showed asymmetry (Figure 1).

Figure 1.

Percentage of asymmetry in the parameters used for the determination of hand. LS: left side; RS: right side; G: greater; E: equal; L: lesser; Mi: middle; I: inner; M: meeting; O: outer.

For the twinned loops on the left hand, the slope of the apex ridges was found to be towards the left side in 88% of the samples, while on the right hand, the slope was found to be towards the right side in 88% of the samples. These results are in accordance with the findings of Singh and Chattopadhyay, which is probably the first such study for the determination of the hand from single-digit fingerprint that reported the downward slope of the apex ridges towards the left side in 84.61% of samples on the left hand and towards the right side in 78.57% of samples on the right hand in Punjabi Jat males.²²

The distance from the left delta to the ascending core was conclusively smaller in 90% of the samples for twinned loops on the left-hand, while it was greater in 88% of the samples on the right hand. The trend reversed when the distance from the right delta to the ascending core was measured, and it was found to be greater in 90% of the samples on the left hand and smaller in 88% of the samples on the right hand.

The mid-core position was towards the left side in 86% of the samples on the left hand and towards the right side in 88% of the samples on the right hand. On the left hand, the position of the ascending loop was towards the left side in 92% of samples and towards the right side in 88% of samples on the right hand.

A total of 96% of the samples on the left hand showed ‘inner’ ridge tracing, whereas 90% of samples on the right hand showed ‘outer’ ridge tracing. The side-specific differences in the ridge tracing of the twinned loops were in agreement with the results of the study conducted on Czechs, Slovaks and Lusatian Serbs by Kralik et al.²⁵ who found 84% inner tracing on the left hand and 84% outer tracing on the right hand. A few parameters under consideration in the present study could not be compared per se with other studies.

Applying the chi-square test showed that there was a significant association (p < 0.01) of these studied parameters of the twinned-loop pattern on the left hand and on the right hand (Table 1). Inter- and intra-observer variability rates were found to be insignificant (p > 0.01).

Ten blind (unknown) single-digit double-loop pattern fingerprint samples were assessed by two observers independently. From the parameters under consideration, they were able to identify the hand of the print correctly in all the samples.

All the parameters studied were found to show statistically significant radio-ulnar asymmetry and hence may be used for the determination of hand (left or right) from a single-digit fingerprint.

Conclusion

The sloping of the apex ridges towards the left side, smaller distance from the left delta to the ascending core, greater distance from the right delta to the ascending core, mid-core position on the left side, ascending loop on the left side and ‘inner’ ridge tracing would lead to the conclusion of left-handedness of the print (Figure 2).

Figure 2.

Parameters of the left-hand twinned loop.

The sloping of the apex ridges towards the right side, greater distance from the left delta to the ascending core, smaller distance from right delta to the ascending core, mid-core position on the right side, ascending loop on the right side and ‘outer’ ridge tracing would lead to the conclusion of right-handedness of the print (Figure 3).

Figure 3.

Parameters of the right-hand twinned loop.

The study confirms the findings of the only two similar studies in this specific area,^22,25 while also adding newer parameters, thereby aiding the determination of the hand from a single-digit fingerprint. Apart from the crime scene, single-digit prints may be encountered in cases involving burglary, idol theft, automobile theft, cheats, attendance sheets in competitive examinations, pension-related documents, insurance claim-related documents, property-related documents, wills, bank cheques and biometrics attendance. The determination of hand may be used as a criterion for elimination and may quicken the search in cases of criminal investigation and personal identification. In the future, there is a possibility of extending this study for palm prints in public databases such as the Latent Palmprint Identification Database (LPIDBv1.0).²⁹ The frequency of occurrence may be used to derive a ‘search sequence’ to search the database. Further studies with other pattern types and other discernible parameters are in progress. Population variability may be studied further to ensure the universal applicability of these parameters.

Footnotes

Acknowledgements

The authors wish to thank the participants of the study, who willingly donated their prints for the study, and the reviewers for their comments. N.K. and A.B. gratefully acknowledge the Director, Government Institute of Forensic Science, Nagpur, and Department of Higher Education, Government of Maharashtra, for their encouragement.

Declaration of conflicting interests

The authors declared no potential conflicts of interest with respect to the research, authorship and/or publication of this article.

Funding

The authors received no financial support for the research, authorship, and/or publication of this article.

ORCID iDs

Neeti Kapoor

Ashish Badiye

References

Nath

Fingerprint Identification in crime detection. New Delhi: Reliance Publishing House, 1991.

Nabar

BS.

Forensic science in criminal investigation. 3rd ed. Hyderabad, India: Asia Law House, 2012.

Cummins

Midlo

Fingerprints, palms and soles. New York: Dover Publications, 1961.

Bridges

BC.

Practical fingerprinting. New York: Funk and Wagnalls, 1937.

Chatterjee

SK.

Finger, palm and sole prints. Calcutta, India: Kosa Publications, 1967.

Field

AJ.

Fingerprint handbook. Springfield, IL: Charles C Thomas, 1959.

Sehgal

Nath

Forensic science and related issues. New Delhi: Selective and Scientific Books, 2012

Arrieta

Martinez

Simon

, et al. Quantitative and qualitative finger dermatoglyphics in the Basque Valley of Urola, Spain. Anthropol Anz 1990; 48: 65–84.

Arrieta

Salazar

Lostao

CM.

Finger ridge count in Basque populations: univariate and multivariate comparison with other Spanish populations.

Ann Hum Biol 1987; 14: 507–516.

10.

Bansal

Badiye

Kapoor

Distribution of fingerprint patterns in an Indian population. Malay J Forensic Sci 2015; 5: 18–21.

11.

Eshak

Zaher

Hasan

, et al. Sex identification from fingertip features in Egyptian population. J Forensic Leg Med 2013; 20: 46–50.

12.

Floris

Sex and side differences and correlations between quantitative palmar characteristics in a sample Sardinian population.

Am J Phys Anthropol 1975; 42: 277–280.

13.

Gutiérrez-Redomero

Alonso

Romero

, et al. Variability of fingerprint ridge density in a sample of Spanish Caucasians and its application to sex determination. Forensic Sci Int 2008; 180: 17–22.

14.

Gutiérrez-Redomero

Galera

Martínez

, et al. Biological variability of the minutiae in the fingerprints of a sample of the Spanish population. Forensic Sci Int 2007; 172: 98–105.

15.

Kapoor

Badiye

Digital dermatoglyphics: a study on Muslim population from India. Egypt J Forensic Sci 2015; 5: 90–95.

16.

Kapoor

Badiye

Sex differences in thumbprint ridge density in a central Indian population. Egypt J Forensic Sci 2015; 5: 23–29.

17.

Martín

Portabales

Quantitative finger dermatoglyphics in a Spanish population (Tierra de Campos). Anthropol Anz 1986; 44: 227–238.

18.

Nayak

Rastogi

Kanchan

, et al. Sex differences from fingerprint ridge density in the Indian population. J Forensic Leg Med 2010; 17: 84–86.

19.

Nayak

Rastogi

Kanchan

, et al. Sex differences from fingerprint ridge density in Chinese and Malaysian population. Forensic Sci Int 2010; 197: 67–69.

20.

Nithin

Manjunatha

Preethi

, et al. Gender differentiation by finger ridge count among South Indian population. J Forensic Leg Med 2011; 18: 79–81.

21.

Soanboon

Nanakorn

Kutanan

Determination of sex difference from fingerprint ridge density in northeastern Thai teenagers. Egypt J Forensic Sci 2016; 6: 185–193.

22.

Singh

Chattopadhyay

PK.

Determination of the hand from single digit fingerprint. In: Current Topics in Forensic Science, Proceedings of the 14th Meeting of the International Association of Forensic Sciences, Tokyo, Japan, August 1996, Volume 4, pp.167–179. Ottawa, Canada: Shunderson Communications, 1997.

23.

Singh

Chattopadhyay

Garg

RK.

Determination of hand from single digit fingerprint: a study of whorls.

Forensic Sci Int 2005; 152: 205–208.

24.

Nagesh

Sahoo

Ashoka

Determination of hand from a fingerprint. J Punjab Acad Forensic Med Toxicol 2012; 12: 82–86.

25.

Kralik

Čiháková

Urbanová

, et al. Radio-ulnar asymmetry of fingerprint whorl patterns. In 20th World Meeting of the International Association of Forensic Sciences (IAFS 2014), Coex, Seoul, Korea, 12–18 October 2014.

26.

Kapoor

Badiye

An analysis of whorl patterns for determination of hand.

J Forensic Leg Med 2015; 32: 42–46.

27.

Medina-Pérez

Moreno

Ferrer Ballester

MÁ

, et al. Latent fingerprint identification using deformable minutiae clustering. Neurocomputing 2016; 175: 851–865.

28.

Brazella

Hand determination of whorl patterns using Axis slant. J Forensic Ident 2018; 68: 77–86.

29.

Morales-Moreno

Medina-Pérez

Ferrer-Ballester

, et al. LPIDB v1.0 – Latent Palmprint Identification Database. In: IEEE International Joint Conference on Biometrics (IJCB 2014), Clearwater, FL, USA, 29 September–2 October 2014, pp.1–6.