Computerized kinematic analysis of the clock drawing task in elderly people with mild major depressive disorder: an exploratory study

Discriminative Power of Handwriting and Drawing Features in Depression

This study contributes knowledge on the detection of depression through handwriting/drawing features, to identify quantitative and noninvasive indicators of the disorder for implementing algorithms for its automatic detection. For this purpose, an original online approach was adopted to provide a dynamic evaluation of handwriting/drawing performance of healthy participants with no history of any psychiatric disorders ([Formula: see text]), and patients with a clinical diagnosis of depression ([Formula: see text]). Both groups were asked to complete seven tasks requiring either the writing or drawing on a paper while five handwriting/drawing features' categories (i.e. pressure on the paper, time, ductus, space among characters, and pen inclination) were recorded by using a digitalized tablet. The collected records were statistically analyzed. Results showed that, except for pressure, all the considered features, successfully discriminate between depressed and nondepressed subjects. In addition, it was observed that depression affects different writing/drawing functionalities. These findings suggest the adoption of writing/drawing tasks in the clinical practice as tools to support the current depression detection methods. This would have important repercussions on reducing the diagnostic times and treatment formulation.

Discovering individual-specific gait signatures from data-driven models of neuromechanical dynamics

Locomotion results from the interactions of highly nonlinear neural and biomechanical dynamics. Accordingly, understanding gait dynamics across behavioral conditions and individuals based on detailed modeling of the underlying neuromechanical system has proven difficult. Here, we develop a data-driven and generative modeling approach that recapitulates the dynamical features of gait behaviors to enable more holistic and interpretable characterizations and comparisons of gait dynamics. Specifically, gait dynamics of multiple individuals are predicted by a dynamical model that defines a common, low-dimensional, latent space to compare group and individual differences. We find that highly individualized dynamics-i.e., gait signatures-for healthy older adults and stroke survivors during treadmill walking are conserved across gait speed. Gait signatures further reveal individual differences in gait dynamics, even in individuals with similar functional deficits. Moreover, components of gait signatures can be biomechanically interpreted and manipulated to reveal their relationships to observed spatiotemporal joint coordination patterns. Lastly, the gait dynamics model can predict the time evolution of joint coordination based on an initial static posture. Our gait signatures framework thus provides a generalizable, holistic method for characterizing and predicting cyclic, dynamical motor behavior that may generalize across species, pathologies, and gait perturbations.

Achieving trust in health-behavior-change artificial intelligence apps (HBC-AIApp) development: a multi-perspective guide

OBJECTIVE

Trust determines the success of Health-Behavior-Change Artificial Intelligence Apps (HBC-AIApp). Developers of such apps need theory-based practical methods that can guide them in achieving such trust. Our study aimed to develop a comprehensive conceptual model and development process that can guide developers how to build HBC-AIApp in order to support trust creation among the app's users.

METHODS

We apply a multi-disciplinary approach where medical informatics, human-centered design, and holistic health methods are integrated to address the trust challenge in HBC-AIApps. The integration extends a conceptual model of trust in AI developed by Jermutus et al., whose properties guide the extension of the IDEAS (integrate, design, assess, and share) HBC-App development process.

RESULTS

The HBC-AIApp framework consists of three main blocks: (1) system development methods that study the users' complex reality, hence, their perceptions, needs, goals and environment; (2) mediators and other stakeholders who are important for developing and operating the HBC-AIApp, boundary objects that examine users' activities via the HBC-AIApp; and (3) the HBC-AIApp's structural components, AI logic, and physical implementation. These blocks come together to provide the extended conceptual model of trust in HBC-AIApps and the extended IDEAS process.

DISCUSSION

The developed HBC-AIApp framework drew from our own experience in developing trust in HBC-AIApp. Further research will focus on studying the application of the proposed comprehensive HBC-AIApp development framework and whether applying it supports trust creation in such apps.

A survey of visual and procedural handwriting analysis for neuropsychological assessment

To date, Artificial Intelligence systems for handwriting and drawing analysis have primarily targeted domains such as writer identification and sketch recognition. Conversely, the automatic characterization of graphomotor patterns as biomarkers of brain health is a relatively less explored research area. Despite its importance, the work done in this direction is limited and sporadic. This paper aims to provide a survey of related work to provide guidance to novice researchers and highlight relevant study contributions. The literature has been grouped into “visual analysis techniques” and “procedural analysis techniques”. Visual analysis techniques evaluate offline samples of a graphomotor response after completion. On the other hand, procedural analysis techniques focus on the dynamic processes involved in producing a graphomotor reaction. Since the primary goal of both families of strategies is to represent domain knowledge effectively, the paper also outlines the commonly employed handwriting representation and estimation methods presented in the literature and discusses their strengths and weaknesses. It also highlights the limitations of existing processes and the challenges commonly faced when designing such systems. High-level directions for further research conclude the paper.

Patients' Self-Report and Handwriting Performance Features as Indicators for Suspected Mild Cognitive Impairment in Parkinson's Disease

Early identification of mild cognitive impairment (MCI) in Parkinson's disease (PD) patients can lessen emotional and physical complications. In this study, a cognitive functional (CF) feature using cognitive and daily living items of the Unified Parkinson's Disease Rating Scale served to define PD patients as suspected or not for MCI. The study aimed to compare objective handwriting performance measures with the perceived general functional abilities (PGF) of both groups, analyze correlations between handwriting performance measures and PGF for each group, and find out whether participants' general functional abilities, depression levels, and digitized handwriting measures predicted this CF feature. Seventy-eight participants diagnosed with PD by a neurologist (25 suspected for MCI based on the CF feature) completed the PGF as part of the Daily Living Questionnaire and wrote on a digitizer-affixed paper in the Computerized Penmanship Handwriting Evaluation Test. Results indicated significant group differences in PGF scores and handwriting stroke width, and significant medium correlations between PGF score, pen-stroke width, and the CF feature. Regression analyses indicated that PGF scores and mean stroke width accounted for 28% of the CF feature variance above age. Nuances of perceived daily functional abilities validated by objective measures may contribute to the early identification of suspected PD-MCI.

Trail Making Test Performance Using a Touch-Sensitive Tablet: Behavioral Kinematics and Electroencephalography

The Trail Making Test (TMT) is widely used to probe brain function and is performed with pen and paper, involving Parts A (linking numbers) and B (alternating between linking numbers and letters). The relationship between TMT performance and the underlying brain activity remains to be characterized in detail. Accordingly, sixteen healthy young adults performed the TMT using a touch-sensitive tablet to capture enhanced performance metrics, such as the speed of linking movements, during simultaneous electroencephalography (EEG). Linking and non-linking periods were derived as estimates of the time spent executing and preparing movements, respectively. The seconds per link (SPL) was also used to quantify TMT performance. A strong effect of TMT Part A and B was observed on the SPL value as expected (Part B showing increased SPL value); whereas the EEG results indicated robust effects of linking and non-linking periods in multiple frequency bands, and effects consistent with the underlying cognitive demands of the test.

Kinematic and Pressure Features of Handwriting and Drawing: Preliminary Results Between Patients with Mild Cognitive Impairment, Alzheimer Disease and Healthy Controls

Background:

Alzheimer’s disease (AD) is the most common neurodegenerative dementia of old age, and the leading chronic disease contributor to disability and dependence among older people worldwide. Clinically, AD is characterized by a progressive cognitive decline that interferes with the abil-ity to perform the activities of daily living. Handwriting and drawing are complex human activities that entail an intricate blend of cognitive, kinesthetic, and perceptual-motor features.

Objective:

To compare the kinematic characteristics of handwriting and drawing between patients with AD, patients with mild cognitive impairment (MCI) and healthy controls.

Methods:

We used a cross-sectional and observational design to assess the kinematic and pressure fea-tures of handwriting and drawing using a computerized system. Participants were asked to copy one sen-tence, write a dictated sentence and an own sentence, copy two and-three dimensions drawings, and to execute the clock drawing test. By means of discriminant analyses, we explored the value of several kin-ematic features in order to classify participants depending on their degree of cognitive functioning.

Results:

The sample consisted of 52 participants (23 AD, 12 MCI, and 17 healthy controls) with a mean age of 69.7 years (SD=8.11). The degree of correct classification was largely dependent on the nature of the groups to be classified and the specific task, and ranged between 63.5% and 100%. Diagnostic accu-racy based on kinematic measures showed higher specificity values for distinguishing between normal and impaired cognition (MCI and AD), and higher sensitivity was obtained when distinguishing between impaired cognition levels (MCI vs. AD).

Conclusion:

The kinematic features of writing and drawing procedures, rather than the final product, may be a useful and objective complement to the clinical assessment of patients with cognitive impairment.

Kinematic measures of brain drawings are associated with illness perceptions in people with stroke

BACKGROUND

Previous research has shown that measuring the size and content of patients' drawings of their illness can reveal their perceptions and predict recovery. This study aimed to assess the usefulness of analyzing kinematic features of drawings.

METHODS

A pilot observational study was conducted with 15 patients who had been hospitalized with a stroke 8 to 11 months previously. They were asked to draw a picture of what they thought had happened to their brain and describe the drawing using an electronic inking pen and digitizing tablet. Analysis of kinematic data (time to draw/write, drawing/writing speed, and pen pressure) was conducted using MovAlyzeR® software. Evaluations of physical functioning, quality of life, illness perceptions, and emotional well-being were administered, and correlations with kinematic measures assessed.

RESULTS

Stronger pen pressure was associated with perceptions of greater control over the stroke. Faster drawing was correlated with greater worry about a recurrent stroke and the perception that the effects of the stroke would last longer. Needing more time to write was associated with perceptions of fewer consequences of the stroke. No associations between kinematic measures and indicators of stroke severity, physical, or emotional well-being were shown.

CONCLUSIONS

Kinematic measures of stroke patients' drawings of their brain and comments were associated with illness perceptions and not measures of physical or emotional health status. The addition of kinematic analysis may add further utility to the assessment of patients' drawings of their illness. More studies need to be performed with larger sample sizes and other patient groups.

Fine motor movements while drawing during the encoding phase of a serial verbal recall task reduce working memory performance

The time-based resource-sharing (TBRS) model of working memory indicates that secondary tasks that capture attention for relatively long periods can result in the interference of working memory processing and maintenance. The current study investigates if discrete and continuous movements have differing effects on a concurrent, verbal serial recall task. In the listening condition, participants were asked to recall spoken words presented in lists of six. In the drawing conditions, participants performed the same task while producing discrete (star) or continuous (circle) movements. As hypothesised, participants recalled more words overall in the listening condition compared to the combined drawing conditions. The prediction that the continuous movement condition would reduce recall compared to listening was also supported. Fine-grained analysis at each serial position revealed significantly more words were recalled at mid serial positions in the listening condition, with worst recall for the continuous condition at position 5 compared to the listening and discrete conditions. Kinematic analysis showed that participants increased the size and speed of the continuous movements resulting in a similar duration and number of strokes for each condition. The duration of brief pauses in the discrete condition was associated with the number of words recalled. The results indicate that fine motor movements reduced working memory performance; however, it was not merely performing a movement but the type of the movement that determined how resources were diverted. In the context of the TBRS, continuous movements could be capturing attention for longer periods relative to discrete movements, reducing verbal serial recall.

Short term oxygen therapy effects in hypoxemic patients measured by drawing analysis

BACKGROUND

Chronic hypoxemia has deleterious effects on psychomotor function that can affect daily life. There are no clear results regarding short term therapy with low concentrations of O2 in hypoxemic patients. We seek to demonstrate, by measuring the characteristics of drawing, these effects on psychomotor function of hypoxemic patients treated with O2.

METHODS

Eight patients (7/1) M/F, age 69.5 (9.9) yr, mean (SD) with hypoxemia (Pa O2 62.2 (6.9) mmHg) performed two drawings of pictures. Tests were performed before and after 30 min breathing with O2.

RESULTS

Stroke velocity increased after O2 for the house drawing (i.e. velocity 27.6 (5.5) mm/s basal, 30.9 (7.1) mm/s with O2, mean (SD), p<0.025, Wilcoxon test). The drawing time 'down' or fraction time the pen is touching the paper during the drawing phase decreased (i.e. time down 20.7 (6.6) s basal, 17.4 (6.3) s with O2, p<0.017, Wilcoxon test).

CONCLUSIONS

This study shows that in patients with chronic hypoxemia, a short period of oxygen therapy produces changes in psychomotor function that can be measured by means of drawing analysis.