A Handwriting-Based Protocol for Assessing Neurodegenerative Dementia (original) (raw)
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Handwriting Process Variables Discriminating Mild Alzheimer's Disease and Mild Cognitive Impairment
The Journals of Gerontology Series B: Psychological Sciences and Social Sciences, 2006
This study's aims were (a) to examine kinematically the handwriting process of persons with mild cognitive impairment (MCI), compared with those with mild Alzheimer's disease and healthy controls; (b) to assess the importance of these measures for the differentiation of the groups; and (c) to assess characteristics of the handwriting process across different functional tasks. Thirty-one persons with MCI, 22 with mild Alzheimer's disease, and 41 healthy controls performed functional tasks while using a computerized system. We found significant differences between the groups in almost all measures, with the MCI group assuming a position between the other groups. Temporal measures were higher and pressure was lower in more cognitively deteriorated groups. Information gathered about kinematic measures, together with cognitive functioning, allowed us to classify 69% to 72% of the participants correctly, although the classification for the MCI group was relatively poor. A LZHEIMER'S disease (AD) is a degenerative disease that attacks the brain, causing memory loss, cognitive impairment, and, in late stages, deterioration of motor skills and withdrawal from social contacts. AD is characterized by a gradual onset of symptoms and irreversible decline to a near vegetative state (Small et al., 1997). Recently, there has been an increase in research focusing on evidence that the onset of AD is preceded by a phase of loss in cognitive functioning in general and in memory functioning in particular (Goldman & Morris, 2001). This phase has been termed mild cognitive impairment (MCI; Petersen et al., 1999), and it has been defined as ''a transitional but progressively degenerative cognitive phase that precedes the onset of AD'' (Shah, Tangalos, & Petersen, 2000, p. 65), although naturalistic studies show that not all persons with MCI progress and some even recover. Handwriting is a complex human activity that entails an intricate blend of cognitive, kinesthetic, and perceptual-motor components (Reisman, 1993), including visual and kinesthetic perception, motor planning, eye-hand coordination, visualmotor integration, dexterity, and manual skills (Tseng & Cermak, 1993). These characteristics of the handwriting process suggest that it might be sensitive to age-related impairments in cognitive functioning, and thus assessments of handwriting might facilitate the diagnosis of such impairments. We designed the present research to address this possibility. Significant handwriting difficulties were already reported by Alois Alzheimer when describing the first patient with AD in 1907: ''when writing, she reduplicated the same syllable and forgot some others, in general, finished very rapidly by stopping'' (p. 226, Croislie, 1999). The evolution of agraphic impairments in AD was described in 1989 (Platel et al., 1993) and included lexicosemantic disturbances at the beginning of the disease, with impairments becoming more and more phonological as the dementia becomes more severe.
An Experimental Protocol to Support Cognitive Impairment Diagnosis by using Handwriting Analysis
procedia Computer science, 2018
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. However, few studies have been conducted on the use of classification systems, e.g. neural networks or decision trees, as tools for detecting the handwriting of people affected by cognitive impairments. 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 proposed protocol has been developed taking into account the results reported in the literature. 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.
Using Handwriting Features to Characterize Cognitive Impairment
Lecture Note in Computer Science, 2019
Cognitive impairments affect skills such as communication, understanding or memory and they may be a short-term problem or a permanent condition. Among the diseases involving cognitive impairments , neurodegenerative ones are the most common and affect millions of people worldwide. Handwriting is one of the daily activities affected by these kinds of impairments, and its anomalies are already used as diagnosis sign, e.g. micrographia in Parkinson's patients. Nowadays, many studies have been conducted to investigate how cognitive impairments affect handwriting, but few of them have used classification algorithms as a tool to support the diagnosis of these diseases. Moreover, almost all of these studies have involved a few dozens of subjects. In this paper, we present a study in which the handwriting of more than one hundred subjects has been recorded while they were performing some elementary tasks, such as the copy of simple words or the drawing of elementary forms. As for the features, we considered kinematic ones. The results seem to confirm that handwriting analysis can be used to develop machine learning tools to support the diagnosis of cognitive impairments.
Handwriting analysis to support Alzheimer Disease diagnosis: a preliminary study
Lecture Notes in Computer Science, 2019
Alzheimers disease (AD) is the most common neurodegener-ative dementia of old age and the leading chronic disease contributor to disability and dependence among older people worldwide. Handwriting is among the motor activities compromised by AD, which is the result of a complex network of cognitive, kinaesthetic and perceptive-motor skills. Indeed, researchers have shown that the patients affected by these diseases exhibit alterations in the spatial organization and poor control of movement. In this paper, we present the preliminary results of a study in which an experimental protocol (including the copy of words, letters and sentence task) has been used to assess assess the kinematic properties of the movements involved in the handwriting. The obtained results are very encouraging and seem to confirm the hypothesis that machine learning-based analysis of handwriting can be profitably used to support AD diagnosis.
A Brief Overview on Handwriting Analysis for Neurodegenerative Disease Diagnosis
2017
Degenerative nerve diseases affect many of your body's activities, such as balance, movement, talking, breathing, and heart function. These disease cannot be cured, nonetheless an early diagnosis can help to better manage the symptoms and the evolution of these diseases. Since handwriting involves several cognitive abilities, clinicians started to consider handwriting analysis as an effective tool for early diagnoses for this kind of diseases. Moreover, as they show different handwriting impairments as they evolve, handwriting analysis can be also used for monitoring them along the clinical course. This paper provides a brief overview on the use of handwriting analysis for early diagnosis, monitoring and tracking of neurodegenerative diseases. In particular, we taken into account Alzheimer and Parkinson diseases.
Journal of the International Neuropsychological Society, 1999
Patients with dementia of the Alzheimer's type (DAT) and their matched controls wrote, on a computer graphics tablet, 4 consecutive, cursive letter 'l's, with varying levels of visual feedback: noninking pen and blank paper so that only the hand movements could be seen, noninking pen and lined paper to constrain their writing, goggles to occlude the lower visual field and eliminate all relevant visual feedback, and inking pen with full vision. The kinematic measures of stroke length, duration, and peak velocity were expressed in terms of consistency via a signal-to-noise ratio (M value of each parameter divided by its SD). Irrespective of medication or severity, DAT patients had writing strokes of significantly less consistent lengths than controls', and were disproportionately impaired by reduced visual feedback. Again irrespective of medication or severity, patients' strokes were of significantly less consistent duration, and significantly less consistent peak velocity than controls', independent of feedback conditions. Patients, unlike controls, frequently perseverated, producing more than 4 'l's, or multiple sets of responses, which was not differentially affected by level of visual feedback. The more variable performance of patients supports a degradation of the base motor program, and resembles that of Huntington's rather than Parkinson's disease patients. It may indeed reflect frontal rather than basal ganglia dysfunction. (JINS, 1999, 5, 20-25.)
Acta Neuropsychologica, 2022
Handwriting is a component of the complex language that came about late in the history of mankind and which develops late in human beings. Numerous works have raised changes in both the graphic and kinematic characteristics of writing. Although, age does not modify the lexical and syntactic parameters of language, it can however modify its spatial structure, especially pressure and speed. Many neurodegenerative pathologies, especially Alzheimer's disease, are characterized by a progressive disorganization of writing. Depending on the cognitive stage of the dementia, the graphic gesture deteriorates as does the spatial construction. Our study aims at assessing the characteristics of Arabic writing in a healthy Moroccan population and to compare it to people with mild to moderate Alzheimer's disease. Our objective is to help health professionals detect early cognitive deterioration in neurodegenerative diseases by analyzing the graphic gesture. Handwriting is captured on a graphic tablet (WACOM) and is analyzed "online" as a sequence of acquired signals (position, pressure, speed and pen inclination) in Moroccan patients with mild to moderate Alzheimer's disease and these were compared to those of normal volunteers. We performed a first analysis of the results from 18 Alzheimer's patients compared to 18 control subjects. The results reveal differences between the control and Alzheimer's groups. AD subjects had lower speeds and accelerations compared to the control subjects. The time spent on paper and in the air was significantly greater in the AD subjects. This preliminary analysis of the results allowed us to identify distinguishing characteristics through the analysis of different handwriting parameters in order to identify the two groups studied.
Handwriting Characterization of Neurodegenerative diseases
2012
There is no definite relationship between handwriting patterns of a patient suffering from a neurodegenerative disease and the disease itself. It is a known fact that handwriting of a patient can depict the intensity of this disease and can be taken as a symptom or detection tool, yet no standard theory or tool exists. This paper tries to find that definite relation between handwriting and the associated diseases.