an experimental protocol to support cognitive impairment diagnosis by using handwriting analysis

Abstract Nowadays diseases involving cognitive impairments affect millions of people worldwide, with Alzheimer's and Parkinson's diseases being the most common ones. Because of the worldwide average lifespan increment, it is expected that their incidence will increase in the next few decades. Among the daily activities, handwriting is one of the first affected by cognitive impairments. For this reasons, researchers have also been investigating the analysis of handwriting alterations as diagnostic signs for this kind of diseases. In this paper we present an experimental protocol that we developed for the analysis of the handwriting dynamics of patients affected by cognitive impairments. The aim of this protocol is to build a large database that would allow to effectively train different classifier systems. We also detail the most common and effective features previously used in the literature to represent handwriting dynamics of the subjects affected by cognitive impairments

Premature thoughts on writing disorders

Three papers appeared in the 19th century describing the dissociation between speech and writing: Marce (1856), Ogle (1867) and Pitres (1884). An account of the convincing evidence of dissociations put forward in these papers is presented. Three explanations are proposed as to the reason why the observations reported by these authors were overlooked or rejected by their contemporaries, namely: (a) in the first half of the century it seems that very little knowledge of the processes underlying writing (as opposed to speech) was available, (b) the debates focussed on the independence of speech versus motor control and language versus the intellect, (c) parallelisms between phylogeny, ontogeny and aphasia impeded the application of the principle of double dissociations, including the dissociations between speech and writing. It is argued that this phenomenon in the history of aphasia is best captured by the concept of prematurity in scientific discovery proposed by Stent (1972, 2003)

Artificial intelligence approaches to predicting and detecting cognitive decline in older adults: A conceptual review.

Preserving cognition and mental capacity is critical to aging with autonomy. Early detection of pathological cognitive decline facilitates the greatest impact of restorative or preventative treatments. Artificial Intelligence (AI) in healthcare is the use of computational algorithms that mimic human cognitive functions to analyze complex medical data. AI technologies like machine learning (ML) support the integration of biological, psychological, and social factors when approaching diagnosis, prognosis, and treatment of disease. This paper serves to acquaint clinicians and other stakeholders with the use, benefits, and limitations of AI for predicting, diagnosing, and classifying mild and major neurocognitive impairments, by providing a conceptual overview of this topic with emphasis on the features explored and AI techniques employed. We present studies that fell into six categories of features used for these purposes: (1) sociodemographics; (2) clinical and psychometric assessments; (3) neuroimaging and neurophysiology; (4) electronic health records and claims; (5) novel assessments (e.g., sensors for digital data); and (6) genomics/other omics. For each category we provide examples of AI approaches, including supervised and unsupervised ML, deep learning, and natural language processing. AI technology, still nascent in healthcare, has great potential to transform the way we diagnose and treat patients with neurocognitive disorders

Use of technological tools to evaluate handwriting production of the alphabet and pseudocharacters by Brazilian students

OBJECTIVE: This study aimed to characterize and compare the handwriting performance of Brazilian students from the 3rd to the 5th grade level of elementary school I with a computerized instrument that allowed the real performance to be observed during the execution of the handwriting. METHODS: Ninety-five students, aged 8 years to 11 years and 11 months, were assigned the production tasks of handwriting letters and pseudocharacters to assess the variables of latency, letter duration production and movement fluency. The stimulus presentation and the analysis of the movements were analyzed by Ductus software. RESULTS: In relation to the writing duration, latency and fluency of the alphabet letters, there was a diminution of values from the 3rd to 5th grade. For the comparison between alphabet and pseudocharacter latency, the results indicated a difference between the alphabet letter and its corresponding pseudocharacter, with greater latency for the pseudocharacter. This finding suggests that a motor sequence has not been established, so it cannot be assumed that the production of the alphabet letters was automatic. CONCLUSION: The results of this study make it possible to verify the interaction failures between the central and peripheral processes, with progression between the 3rd and 5th grade. It also highlights the influence of the lack of systematized teaching of the tracing of letters for Brazilian students since proficiency in calligraphy is critically linked to academic performance. These findings provide a great contribution to Brazilian educational psychology and reflect both educational and clinical practices

A Preliminary Review of Behavioural Biometrics for Health Monitoring in the Elderly

This article explores the potential of ICT-based biometrics for monitoring the health status of the elderly people. It departs from specific ageing and biometric traits to then focus on behavioural biometric traits like handwriting, speech and gait to finally explore their practical application in health monitoring of elderly

Investigating The Relationship between Event-Related Potentials and Response Kinematics

Movement is one of the most important functions of our nervous system. Recent research has shown that cognitive and perceptual functions ranging from our perception of others’ emotions to the planning of goal-directed behaviors depends critically on brain areas once thought to be primarily motor in nature. Given the important role our motor system plays in understanding and interacting with the world around us, it is surprising that the majority of cognitive neuroscience research using electroencephalogram (EEG) has focused primarily on perception and cognition irrespective of its relationship(s) to the execution of movement. One possible explanation for this is that EEG and event-related potential (ERP) studies typically rely on simplistic motor responses and ERP averaging techniques that do not afford an analysis of these dynamic relationships. Combining a novel method for tracking dynamic cursor movement and single-trial EEG analysis, the current study addressed this limitation in the field via assessment of younger and older adults’ goal-directed movements during a task-set switching procedure. Our results demonstrate that ERPs conventionally interpreted with respect to cognition and perception are in fact related to the kinematics of motor responses

Drawing, Handwriting Processing Analysis: New Advances and Challenges

International audienceDrawing and handwriting are communicational skills that are fundamental in geopolitical, ideological and technological evolutions of all time. drawingand handwriting are still useful in defining innovative applications in numerous fields. In this regard, researchers have to solve new problems like those related to the manner in which drawing and handwriting become an efficient way to command various connected objects; or to validate graphomotor skills as evident and objective sources of data useful in the study of human beings, their capabilities and their limits from birth to decline