A study of the effects of ageing on the characteristics of handwriting and signatures

The work presented in this thesis is focused on the understanding of factors that are unique to the elderly and their use of biometric systems. In particular, an investigation is carried out with a focus on the handwritten signature as the biometric modality of choice. This followed on from an in-depth analysis of various biometric modalities such as voice, fingerprint and face. This analysis aimed at investigating the inclusivity of and the policy guiding the use of biometrics by the elderly. Knowledge gained from extracted features of the handwritten signatures of the elderly shed more light on and exposed the uniqueness of some of these features in their ability to separate the elderly from the young. Consideration is also given to a comparative analysis of another handwriting task, that of copying text both in cursive and block capitals. It was discovered that there are features that are unique to each task. Insight into the human perceptual capability in inspecting signatures, in assessing complexity and in judging imitations was gained by analysing responses to practical scenarios that applied human perceptual judgement. Features extracted from a newly created database containing handwritten signatures donated by elderly subjects allowed the possibility of analysing the intra-class variations that exist within the elderly population

Utvrđivanje starosti potpisa: primjer iz prakse

The most common question that a handwriting expert is confronted with is to determine whether or not the signature or handwriting in question is authentic or forged. Moreover, in many cases, the request is to determine if the date on the document is the actual date the document was created or if the document has been backdated. Two methods of examination can be applied for the latter: the ink dating method as a destructive method or the signatures and handwriting dating method as a non-destructive method. This case study aims to show the changes that occur in a person\u27s signature over time. During the secret investigation phase, the Croatian State Prosecutor\u27s Office for the Suppression of Organized Crime and Corruption sent the Forensic Science Centre two Annexes to professional playing contracts containing two signatures in the name of Luka Modric. The experts were asked to determine if the questioned signatures were authentic and other facts relevant to the investigation (backdating etc.). The results obtained have shown clear variations/developments in known signatures over time without applying any destructive method.Najčešće pitanje s kojim se u svojem svakodnevnom radu susreću vještaci za rukopise je mogu li utvrditi je li sporni potpis ili rukopis autentičan ili krivotvoren. Štoviše, u mnogim slučajevima moraju i utvrditi je li datum na dokumentu stvarni datum kada je dokument izrađen ili je dokument antedatiran. Za ovu vrstu ispitivanja mogu se primijeniti dvije metode: metoda utvrđivanja starosti tinte kao destruktivna te metoda utvrđivanja starosti potpisa i rukopisa kao nedestruktivna metoda Cilj ovog primjera iz prakse jest pokazati promjene koje se događaju u potpisu osobe tijekom vremena. Ured za suzbijanje korupcije i organiziranog kriminaliteta u fazi tajne istrage dostavio je na vještačenja Centru za forenzična ispitivanja, istraživanja i vještačenja “Ivan Vučetić” dva ankesa ugovora o profesionalnom igranju s dva sporna potpisa Luke Modrića. Zadatak vještačenja bilo je utvrditi jesu li sporni potpisi autentični potpisi te ostale činjenice koje mogu biti bitne za samu istragu (jesu li potpisi možda antedatirani i sl.). Dobiveni rezultati pokazali su vidljive varijacije/razvoj u nespornim potpisima tijekom vremena i to bez primjene bilo kakve destruktivne metode

Predictive biometrics: A review and analysis of predicting personal characteristics from biometric data

Interest in the exploitation of soft biometrics information has continued to develop over the last decade or so. In comparison with traditional biometrics, which focuses principally on person identification, the idea of soft biometrics processing is to study the utilisation of more general information regarding a system user, which is not necessarily unique. There are increasing indications that this type of data will have great value in providing complementary information for user authentication. However, the authors have also seen a growing interest in broadening the predictive capabilities of biometric data, encompassing both easily definable characteristics such as subject age and, most recently, `higher level' characteristics such as emotional or mental states. This study will present a selective review of the predictive capabilities, in the widest sense, of biometric data processing, providing an analysis of the key issues still adequately to be addressed if this concept of predictive biometrics is to be fully exploited in the future

The motor prodromes of parkinson's disease: from bedside observation to large-scale application

There is sufficient evidence that the pathological process that causes Parkinson's disease begins years before the clinical diagnosis is made. Over the last 15 years, there has been much interest in the existence of a prodrome in some patients, with a particular focus on non-motor symptoms such as reduced sense of smell, REM-sleep disorder, depression, and constipation. Given that the diagnostic criteria for Parkinson's disease depends on the presence of bradykinesia, it is somewhat surprising that there has been much less research into the possibility of subtle motor dysfunction as a pre-diagnostic pointer. This review will focus on early motor features and provide some advice on how to detect and measure them

Graphonomics and your Brain on Art, Creativity and Innovation : Proceedings of the 19th International Graphonomics Conference (IGS 2019 – Your Brain on Art)

[Italiano]: “Grafonomia e cervello su arte, creatività e innovazione”. Un forum internazionale per discutere sui recenti progressi nell'interazione tra arti creative, neuroscienze, ingegneria, comunicazione, tecnologia, industria, istruzione, design, applicazioni forensi e mediche. I contributi hanno esaminato lo stato dell'arte, identificando sfide e opportunità, e hanno delineato le possibili linee di sviluppo di questo settore di ricerca. I temi affrontati includono: strategie integrate per la comprensione dei sistemi neurali, affettivi e cognitivi in ambienti realistici e complessi; individualità e differenziazione dal punto di vista neurale e comportamentale; neuroaesthetics (uso delle neuroscienze per spiegare e comprendere le esperienze estetiche a livello neurologico); creatività e innovazione; neuro-ingegneria e arte ispirata dal cervello, creatività e uso di dispositivi di mobile brain-body imaging (MoBI) indossabili; terapia basata su arte creativa; apprendimento informale; formazione; applicazioni forensi. / [English]: “Graphonomics and your brain on art, creativity and innovation”. A single track, international forum for discussion on recent advances at the intersection of the creative arts, neuroscience, engineering, media, technology, industry, education, design, forensics, and medicine. The contributions reviewed the state of the art, identified challenges and opportunities and created a roadmap for the field of graphonomics and your brain on art. The topics addressed include: integrative strategies for understanding neural, affective and cognitive systems in realistic, complex environments; neural and behavioral individuality and variation; neuroaesthetics (the use of neuroscience to explain and understand the aesthetic experiences at the neurological level); creativity and innovation; neuroengineering and brain-inspired art, creative concepts and wearable mobile brain-body imaging (MoBI) designs; creative art therapy; informal learning; education; forensics

Designing a comprehensive system for analysis of handwriting biomechanics in relation to neuromotor control of handwriting

A comprehensive system for investigation of biomechanical and neuromuscular processes involved with producing handwriting and drawing was developed. The system included a pen-like grip measuring device that enabled the variations of finger grip force associated with writing and drawing to be measured while holding the pen in tripod grip. The pen was integrated with a digitiser tablet for recording x,ycoordinates and pressure of the nib and a motion analysis system for recording the limb and hand kinematics. It was observed that for line drawing in the y-direction of the tablet, finger forces were directly related to pen tip movement and finger forces were modulated in a repeatable and predictable fashion, while this was not the case for line drawing in the x-direction. This was evidence for longstanding assumptions. Wrist rotation was required for production of lines in the x-direction without excessive deviation. For writing tasks, it was observed that no two tasks performed by one subject share an identical writing process, not even when the writing results are (nearly) identical. The neuromuscular control apparatus is highly flexible and works in a coordinated fashion that allows production of nearly equal end-results by means of different mechanical and therefore neuromuscular processes. For spiral drawing, tremor that originates from the fingers, hand and arm was quantified with the transducer pen. Limb joint kinematics were displayed in three dimensions with colour coding of coordinate sample numbers. This method can reveal the origin of some forms of limb tremor. Pen grip force patterns during signature writing were found to be characteristic for subjects, which relate to their individual pen-hand interaction, resulting from fine control of distal joints. Variation between trials of the same subject was observed, revealing adaptations of the computational processes during writing. The potential for signature verification by means of finger force recording was explored.A comprehensive system for investigation of biomechanical and neuromuscular processes involved with producing handwriting and drawing was developed. The system included a pen-like grip measuring device that enabled the variations of finger grip force associated with writing and drawing to be measured while holding the pen in tripod grip. The pen was integrated with a digitiser tablet for recording x,ycoordinates and pressure of the nib and a motion analysis system for recording the limb and hand kinematics. It was observed that for line drawing in the y-direction of the tablet, finger forces were directly related to pen tip movement and finger forces were modulated in a repeatable and predictable fashion, while this was not the case for line drawing in the x-direction. This was evidence for longstanding assumptions. Wrist rotation was required for production of lines in the x-direction without excessive deviation. For writing tasks, it was observed that no two tasks performed by one subject share an identical writing process, not even when the writing results are (nearly) identical. The neuromuscular control apparatus is highly flexible and works in a coordinated fashion that allows production of nearly equal end-results by means of different mechanical and therefore neuromuscular processes. For spiral drawing, tremor that originates from the fingers, hand and arm was quantified with the transducer pen. Limb joint kinematics were displayed in three dimensions with colour coding of coordinate sample numbers. This method can reveal the origin of some forms of limb tremor. Pen grip force patterns during signature writing were found to be characteristic for subjects, which relate to their individual pen-hand interaction, resulting from fine control of distal joints. Variation between trials of the same subject was observed, revealing adaptations of the computational processes during writing. The potential for signature verification by means of finger force recording was explored

Active detection of age groups based on touch interaction

This paper studies user classification into children and adults according to their interaction with touchscreen devices. We analyse the performance of two sets of features derived from the Sigma-Lognormal theory of rapid human movements and global characterization of touchscreen interaction. We propose an active detection approach aimed to continuously monitorize the user patterns. The experimentation is conducted on a publicly available database with samples obtained from 89 children between 3 and 6 years old and 30 adults. We have used Support Vector Machines algorithm to classify the resulting features into age groups. The sets of features are fused at score level using data from smartphones and tablets. The results, with correct classification rates over 96%, show the discriminative ability of the proposed neuromotorinspired features to classify age groups according to the interaction with touch devices. In active detection setup, our method is able to identify a child using only 4 gestures in averageThis work was funded by the project CogniMetrics (TEC2015-70627-R) and Bio-Guard (Ayudas Fundación BBVA a Equipos de Investigación Científica 2017

Study and characterisation of the prodromal motor phase of Parkinson’s Disease

There is sufficient evidence that a neurodegenerative process in Parkinson’s Disease (PD) starts many years before the clinical diagnosis. The progression of PD is generally slow and, because it is diagnosed based on established motor features, it is probable that subtle motor manifestations appear in the pre-diagnostic phase of PD. Isolated rapid eye movement (REM) sleep behaviour disorder (iRBD) is a condition known to be part of the prodromal phase of PD. The PREDICT-PD study is a population-based cohort which aims to identify individuals at risk of PD based on the presence and absence of risk factors. The first project of this thesis investigated the association between first presentation of motor symptoms (tremor, rigidity and balance difficulties) and subsequent PD in a large primary care dataset in East London, including almost 3 decades of clinical information from over a million individuals. People who went on to develop PD reported motor symptoms up to 10 years before PD diagnosis. Tremor had the highest association with future PD followed by balance difficulties and rigidity. The second project aimed to identify the range of motor features in the elderly population participating in the PREDICT-PD cohort study and document their rate of progression over time. People classified as having a higher risk of future PD (using the PREDICT-PD algorithm) were more likely to have early parkinsonian signs than the lower risk group. Six years later, they also showed a bigger motor decline compared with people in the lower risk group. The third project was focused on developing two new objective motor tools, the Distal Finger Tapping test and the Slow-Motion Analysis of Repetitive Tapping. Both tests were able to detect abnormal patterns of movement amongst people with early PD. Finally, a motor battery was created and implemented in a group of patients with iRBD. A higher proportion of patients with iRBD had early parkinsonian signs compared with controls. The motor battery was able to detect early patterns of motor dysfunction not captured by standardised clinical scales. The work presented in this thesis demonstrates that motor features start in the pre-diagnostic phase of PD and describes new motor signatures in the prodromal phase of PD

Comparison of CNN-Learned vs. Handcrafted Features for Detection of Parkinson's Disease Dysgraphia in a Multilingual Dataset

Parkinson's disease dysgraphia (PDYS), one of the earliest signs of Parkinson's disease (PD), has been researched as a promising biomarker of PD and as the target of a noninvasive and inexpensive approach to monitoring the progress of the disease. However, although several approaches to supportive PDYS diagnosis have been proposed (mainly based on handcrafted features (HF) extracted from online handwriting or the utilization of deep neural networks), it remains unclear which approach provides the highest discrimination power and how these approaches can be transferred between different datasets and languages. This study aims to compare classification performance based on two types of features: features automatically extracted by a pretrained convolutional neural network (CNN) and HF designed by human experts. Both approaches are evaluated on a multilingual dataset collected from 143 PD patients and 151 healthy controls in the Czech Republic, United States, Colombia, and Hungary. The subjects performed the spiral drawing task (SDT; a language-independent task) and the sentence writing task (SWT; a language-dependent task). Models based on logistic regression and gradient boosting were trained in several scenarios, specifically single language (SL), leave one language out (LOLO), and all languages combined (ALC). We found that the HF slightly outperformed the CNN-extracted features in all considered evaluation scenarios for the SWT. In detail, the following balanced accuracy (BACC) scores were achieved: SL—0.65 (HF), 0.58 (CNN); LOLO—0.65 (HF), 0.57 (CNN); and ALC—0.69 (HF), 0.66 (CNN). However, in the case of the SDT, features extracted by a CNN provided competitive results: SL—0.66 (HF), 0.62 (CNN); LOLO—0.56 (HF), 0.54 (CNN); and ALC—0.60 (HF), 0.60 (CNN). In summary, regarding the SWT, the HF outperformed the CNN-extracted features over 6% (mean BACC of 0.66 for HF, and 0.60 for CNN). In the case of the SDT, both feature sets provided almost identical classification performance (mean BACC of 0.60 for HF, and 0.58 for CNN). Copyright © 2022 Galaz, Drotar, Mekyska, Gazda, Mucha, Zvoncak, Smekal, Faundez-Zanuy, Castrillon, Orozco-Arroyave, Rapcsak, Kincses, Brabenec and Rektorova

Dynamic Biometric Signature - an Effective Alternative for Electronic Authentication

The use of dynamic biometric methods for the authentication of people provides significantly greater security than the use of the static ones. The variance of individual dynamic properties of a person, which protects biometric methods against attacks, can be the weak point of these methods at the same time.This paper summarizes the results of a long-term research, which shows that a DBS demonstrates practically absolute resistance to forging and that the stability of signatures provided by test subjects in various situations is high. Factors such as alcohol and stress have no influence on signature stability, either. The results of the experiments showed that the handwritten signature obtained through long practice and the consolidation of the dynamic stereotype, is so automated and stored so deep in the human brain, that its involuntary performance also allows other processes to take place in the cerebral cortex. The dynamic stereotype is composed of psychological, anatomical and motor characteristics of each person. It was also proven to be true that the use of different devices did not have a major impact on the stability of signatures, which is of importance in the case of a blanket deployment.The carried out experiments conclusively showed that the aspects that could have an impact on the stability of a signature did not manifest themselves in such a way that we could not trust these methods even used on commercially available devices. In the conclusion of the paper, the possible directions of research are suggested