Neurology assessment by objective structured video examination (OSVE)

Summary
Background
The ability to carry out a neurological examination and make an appropriate differential diagnosis is one of the mainstays of our final Bachelor of Medicine (MB) exam; however, with the introduction of objective structured clinical examinations (OSCEs) it has become impossible to arrange for adequate numbers of suitable real patients to participate in the exam.

Context
It is vital that newly qualified doctors can perform a basic neurological examination, interpret the physical signs and formulate a differential diagnosis.

It is vital that newly qualified doctors can perform a basic neurological examination

Innovation
Since 2010 we have introduced an objective structured video examination (OSVE) of a neurological examination of a real patient as part of our final MB OSCE exam. The students view clips of parts of the examination process. They answer questions on the signs that are demonstrated and formulate a differential diagnosis.

Implications
This type of station is logistically a lot easier to organise than a large number of real patients at different examination sites. The featured patients have clearly demonstrated signs and, as every student sees the same patient, are perfectly standardised. It is highly acceptable to examiners and performed well as an assessment tool. There are, however, certain drawbacks in that we are not examining the student's examination technique or their interaction with the patient. Also, certain signs, in particular the assessment of muscle tone and power, are more difficult for a student to estimate in this situation

‘At First I Saw It as a Toy’: Life Stories, Social Consciousness and Music Ethnography

This article examines the role of life narratives as discursive spaces for the performance of individual resistance. Through the inspection of three interviews with professional musicians in Athens, the essay will illustrate how the recounting of nodal events in their lives and careers facilitates an assertion of their current social ideology and their disillusionment with the popular music industry in which they operate. Ultimately, what follows will suggest a mode of listening to individual utterances and narratives as discursive forms of resistance that need to be appreciated as social acts as opposed to mere ethnographic data.

Recurrent Convolutional Network for Video-based Person Re-Identification

In this paper we propose a novel recurrent neural networkarchitecture for video-based person re-identification.Given the video sequence of a person, features are extracted from each frame using a convolutional neural network that incorporates a recurrent final layer, which allows information to flow between time-steps. The features from all time steps are then combined using temporal pooling to give an overall appearance feature for the complete sequence. The convolutional network, recurrent layer, and temporal pooling layer, are jointly trained to act as a feature extractor for video-based re-identification using a Siamese network architecture.Our approach makes use of colour and optical flow information in order to capture appearance and motion information which is useful for video re-identification. Experiments are conduced on the iLIDS-VID and PRID-2011 datasets to show that this approach outperforms existing methods of video-based re-identification.

https://github.com/niallmcl/Recurrent-Convolutional-Video-ReID
Project Source Code

Music therapy for end-of-life care: an updated systematic review

Background: Music therapy during palliative and end-of-life care is well established and positive benefits for patients have been reported.
Aim: Assess the effectiveness of music therapy versus standard care alone or standard care in combination with other therapies for improving psychological, physiological and social outcomes among adult patients in any palliative care setting.
Data sources: In order to update an existing Cochrane systematic review, we searched MEDLINE, CINAHL, EMBASE, PsycINFO, CENTRAL, ClinicalTrials.gov register, and Current Controlled Trials register to identify randomised or quasi-randomised controlled trails published between 2009 and April 2015. Nine electronic music therapy journals were searched from 2009 until April 2015, along with reference lists and contact was made with key experts in music therapy. Only studies published in English were eligible for inclusion. Two reviewers independently screened titles, abstracts, assessed relevant studies for eligibility, extracted data and judged risk of bias for included studies. Disagreements were resolved through discussion with a third reviewer. Data were synthesised in Revman using the random effects model. Heterogeneity was assessed using l2.
Results: Three studies were included in the review. Findings suggest music therapy may be effective for helping to reduce pain in palliative care patients (standard mean deviation (SMD) = -0.42, 95% CI -0.68 to -0.17, P = 0.001).
Conclusions: Available evidence did not support the use of music therapy to improve overall quality-of-life in palliative care. While this review suggests music therapy may be effective for reducing pain, this is based on studies with a high risk of bias. Further high quality research is required.

Spatio-temporal Rich Model Based Video Steganalysis on Cross Sections of Motion Vector Planes

A rich model based motion vector steganalysis benefiting from both temporal and spatial correlations of motion vectors is proposed in this work. The proposed steganalysis method has a substantially superior detection accuracy than the previous methods, even the targeted ones. The improvement in detection accuracy lies in several novel approaches introduced in this work. Firstly, it is shown that there is a strong correlation, not only spatially but also temporally, among neighbouring motion vectors for longer distances. Therefore, temporal motion vector dependency along side the spatial dependency is utilized for rigorous motion vector steganalysis. Secondly, unlike the filters previously used, which were heuristically designed against a specific motion vector steganography, a diverse set of many filters which can capture aberrations introduced by various motion vector steganography methods is used. The variety and also the number of the filter kernels are substantially more than that of used in previous ones. Besides that, filters up to fifth order are employed whereas the previous methods use at most second order filters. As a result of these, the proposed system captures various decorrelations in a wide spatio-temporal range and provides a better cover model. The proposed method is tested against the most prominent motion vector steganalysis and steganography methods. To the best knowledge of the authors, the experiments section has the most comprehensive tests in motion vector steganalysis field including five stego and seven steganalysis methods. Test results show that the proposed method yields around 20% detection accuracy increase in low payloads and 5% in higher payloads.