Computerised analysis of writing and drawing by essential tremor phenotype

We investigated whether computerised analysis of writing and drawing could discriminate essential tremor (ET) phenotypes according to the 2018 Consensus Statement on the Classification of Tremors. The Consensus scheme emphasises soft additional findings, mainly motor, that do not suffice to diagnose another tremor syndrome. Ten men and nine women were classified by blinded assessors according to Consensus Axis 1 definitions of ET and ET plus. Blinded scoring of tremor severity and alternating limb movement was also conducted. Twenty healthy participants acted as controls. Four writing and three drawing tasks were performed on a Wacom Intuos Pro Large digital tablet with a pressure-sensor mounted ink pen. Sixty-seven computerised measurements were obtained, comprising static (dimensional and temporal), kinematic and pen pressure features. The mean age of ET participants was 67.2±13.0 years and mean tremor duration was 21.7±19.0 years. Six were classified as ET, five had one plus feature and eight had two plus features. The computerised analysis could predict the presence and number of ET plus features. Measures of acceleration and variation of pen pressure performed strongly to separate ET phenotypes (p<0.05). Plus features were associated with higher scores on the Fahn-Tolosa-Marin Tremor Rating Scale (p=0.001) and it appeared that ET groups were mainly being separated according to severity of tremor and by compensatory manoeuvres used by participants with more severe tremor. There were, in addition, a small number of negative kinematic correlations suggesting some slowness with ET plus. Abnormal repetitive limb movement was also correlated with tremor severity (R=0.57) by clinical grading. Critics of the Consensus Statement have drawn attention to weaknesses of the ET plus concept in relation to duration and severity of ET. This classification of ET may be too biased towards tremor severity to assist in distinguishing underlying biological differences by clinical measurement.

Recognising Fetal Compromise in the Cardiograph during the Antenatal Period: Pearls and Pitfalls

There are several national and international guidelines to aid the interpretation of the cardiotocograph (CTG) trace during labour. These guidelines are based on assessing changes in the fetal heart rate (i.e. cardiograph) in response to mechanical and hypoxic stresses during labour secondary to ongoing frequency, duration and strength of uterine contractions (i.e. tocograph). However, during the antenatal period, uterine contractions are absent, and therefore, these intrapartum CTG guidelines cannot be used to reliably identify fetuses at risk of compromise. Computerised analysis of CTG using the Dawes-Redman Criteria could be used to detect fetal compromise. However, clinicians should be aware of the multiple pathways of fetal damage (i.e. inflammation, infection, intrauterine fetal stroke, chronic fetal anaemia, acute feto-maternal haemorrhage and fetal cardiac or neurological disorders) which can cause changes on the CTG trace which may not be recognised by using CTG guidelines.

How Does Nationalist Selfishness Creep into Cosmopolitan Protection?

This article investigates how selfish justifications enter cosmopolitan rationales in the political plane of the discourse. It makes sense of the ways in which selfish ideas are allowed to meddle in and merge with morally-based cosmopolitan norms. The article commits to the ontological and epistemological premises of critical discourse analysis, and focuses on us presidential papers since 1989. It substantiates the claims it makes by using computer-assisted discursive process tracing method as a supporting tool for qualitative analysis of texts. The computerised analysis of discursive entanglements reveals that cosmopolitan protective operations are in fact mainly framed nationalistically. The roots of such selfish nationalistic arguments for international protective military operations can be traced in the realist and hegemonic fallacies that emphasise the naturality of national selfishness and the need for global hegemony. Furthermore, the article shows how the entanglement of discourse strands about ‘protection’ and ‘innocent victimhood’ as well as the entanglement between ‘crime prevention’ and ‘terrorism prevention’ legitimate selfish internationalist arguments in the us political debate.

Developing an intelligent virtual agent to stratify people with cognitive complaints: A comparison of human–patient and intelligent virtual agent–patient interaction

Previous work on interactions in the memory clinic has shown that conversation analysis can be used to differentiate neurodegenerative dementia from functional memory disorder. Based on this work, a screening system was developed that uses a computerised ‘talking head’ (intelligent virtual agent) and a combination of automatic speech recognition and conversation analysis-informed programming. This system can reliably differentiate patients with functional memory disorder from those with neurodegenerative dementia by analysing the way they respond to questions from either a human doctor or the intelligent virtual agent. However, much of this computerised analysis has relied on simplistic, nonlinguistic phonetic features such as the length of pauses between talk by the two parties. To gain confidence in automation of the stratification procedure, this paper investigates whether the patients’ responses to questions asked by the intelligent virtual agent are qualitatively similar to those given in response to a doctor. All the participants in this study have a clear functional memory disorder or neurodegenerative dementia diagnosis. Analyses of patients’ responses to the intelligent virtual agent showed similar, diagnostically relevant sequential features to those found in responses to doctors’ questions. However, since the intelligent virtual agent’s questions are invariant, its use results in more consistent responses across people – regardless of diagnosis – which facilitates automatic speech recognition and makes it easier for a machine to learn patterns. Our analysis also shows why doctors do not always ask the same question in the exact same way to different patients. This sensitivity and adaptation to nuances of conversation may be interactionally helpful; for instance, altering a question may make it easier for patients to understand. While we demonstrate that some of what is said in such interactions is bound to be constructed collaboratively between doctor and patient, doctors could consider ensuring that certain, particularly important and/or relevant questions are asked in as invariant a form as possible to be better able to identify diagnostically relevant differences in patients’ responses.