Abnormal Infant Movements Classification With Deep Learning on Pose-Based Features

The pursuit of early diagnosis of cerebral palsy has been an active research area with some very promising results using tools such as the General Movements Assessment (GMA). In our previous work, we explored the feasibility of extracting pose-based features from video sequences to automatically classify infant body movement into two categories, normal and abnormal. The classification was based upon the GMA, which was carried out on the video data by an independent expert reviewer. In this paper we extend our previous work by extracting the normalised pose-based feature sets, Histograms of Joint Orientation 2D (HOJO2D) and Histograms of Joint Displacement 2D (HOJD2D), for use in new deep learning architectures. We explore the viability of using these pose-based feature sets for automated classification within a deep learning framework by carrying out extensive experiments on five new deep learning architectures. Experimental results show that the proposed fully connected neural network FCNet performed robustly across different feature sets. Furthermore, the proposed convolutional neural network architectures demonstrated excellent performance in handling features in higher dimensionality. We make the code, extracted features and associated GMA labels publicly available

Establishing Pose Based Features Using Histograms for the Detection of Abnormal Infant Movements

The pursuit of early diagnosis of cerebral palsy has been an active research area with some very promising results using tools such as the General Movements Assessment (GMA). In this paper, we conducted a pilot study on extracting important information from video sequences to classify the body movement into two categories, normal and abnormal, and compared the results provided by an independent expert reviewer based on GMA. We present two new pose-based features, Histograms of Joint Orientation 2D (HOJO2D) and Histograms of Joint Displacement 2D (HOJD2D), for the pose-based analysis and classification of infant body movement from video footage. We extract the 2D skeletal joint locations from 2D RGB images using Cao et al.’s method 1. Using the MINI-RGBD dataset 2, we further segment the body into local regions to extract part specific features. As a result, the pose and the degree of displacement are represented by histograms of normalised data. To demonstrate the effectiveness of the proposed features, we trained several classifiers using combinations of HOJO2D and HOJD2D features and conducted a series of experiments to classify the body movement into categories. The classification algorithms used included k-Nearest Neighbour (kNN, k=1 and k=3), Linear Discriminant Analysis (LDA) and the Ensemble classifier. Encouraging results were attained, with high accuracy (91.67{\%}) obtained using the Ensemble classifier

Blueberry Pancakes

The train is 1000 feet away, but I hear it run through my ears and tear through my bedsheets. I plead with it, “Take me with you.

Can ‘healing’ architectural elements be incorporated into current and future hospitals to create environments that aid recovery and improve patient experience?

The modern day hospital: institutions experienced by the majority, yet, arguably, often have a palpable absence of positive, meaningful and health-encouraging environments. This research project investigates the extent to which architecture and interiors can directly impact a hospital patient’s recovery, in conjunction with considering the factors prohibiting relevant healing architectural features from being consistently implemented in the hospital design process. When considering places devoted to healing the sick have a recorded historical presence dating back to ancient Greece, there is relative early exploration into ‘healing’ architectural features and the legitimate effectiveness of a health-enhancing built environment. Project research into the historical progression and cultural interpretations of hospitals in addition to an exploration of scientific architectural studies aided an understanding of the societal role of hospitals and analysis of recovery associated designs. Primary findings were collated from visiting three contrasting healthcare sites, hospital patient interviews and a public hospital experience survey. With 48% of survey participants, as the majority, stating they felt worse within an environment that is intended to have the opposite effect, it highlights a concern for hospitals and patient experience. Largely, hospitals can provide healing spaces if they offer an environment that finds a balance between avoiding stress inducing features, such as poor wayfinding and lack of natural light, alongside the provision of spaces that are both rejuvenating and engaging. Despite the conjunction between the fields of neuroscience and architecture continuing to prove the impact of architectural features on the mind and body, the expense and potential impracticality of healing architecture often prevents them from being retrofitted in existing hospitals or involved in new builds. Notably, the understanding of the human perception of space and the power of patient experience are the neglected elements that need to be reintroduced during the concept phase of hospital projects

Genome-wide Association Study Identifies New Loci for Resistance to Leptosphaeria maculans in Canola

Blackleg, caused by Leptosphaeria maculans, is a significant disease which affects the sustainable production of canola. This study reports a genome-wide association study based on 18,804 polymorphic SNPs to identify loci associated with qualitative and quantitative resistance to L. maculans. Genomic regions delimited with 503 significant SNP markers, that are associated with resistance evaluated using 12 single spore isolates and pathotypes from four canola stubble were identified. Several significant associations were detected at known disease resistance loci including in the vicinity of recently cloned Rlm2/LepR3 genes, and at new loci on chromosomes A01/C01, A02/C02, A03/C03, A05/C05, A06, A08, and A09. In addition, we validated statistically significant associations on A01, A07 and A10 in four genetic mapping populations, demonstrating that GWAS marker loci are indeed associated with resistance to L. maculans. One of the novel loci identified for the first time, Rlm12, conveys adult plant resistance and mapped within 13.2 kb from Arabidopsis R gene of TIR-NBS class. We showed that resistance loci are located in the vicinity of R genes of A. thaliana and B. napus on the sequenced genome of B. napus cv. Darmor-bzh. Significantly associated SNP markers provide a valuable tool to enrich germplasm for favorable alleles in order to improve the level of resistance to L. maculans in canola

WRR4, a broad-spectrum TIR-NB-LRR gene from Arabidopsis thaliana that confers white rust resistance in transgenic oilseed brassica crops

White blister rust caused by Albugo candida (Pers.) Kuntze is a common and often devastating disease of oilseed and vegetable brassica crops worldwide. Physiological races of the parasite have been described, including races 2, 7 and 9 from Brassica juncea, B. rapa and B. oleracea, respectively, and race 4 from Capsella bursa-pastoris (the type host). A gene named WRR4 has been characterized recently from polygenic resistance in the wild brassica relative Arabidopsis thaliana (accession Columbia) that confers broad-spectrum white rust resistance (WRR) to all four of the above Al. candida races. This gene encodes a TIR-NB-LRR (Toll-like/interleukin-1 receptor-nucleotide binding-leucine-rich repeat) protein which, as with other known functional members in this subclass of intracellular receptor-like proteins, requires the expression of the lipase-like defence regulator, enhanced disease susceptibility 1 (EDS1). Thus, we used RNA interference-mediated suppression of EDS1 in a white rust-resistant breeding line of B. napus (transformed with a construct designed from the A. thaliana EDS1 gene) to determine whether defence signalling via EDS1 is functionally intact in this oilseed brassica. The eds1-suppressed lines were fully susceptible following inoculation with either race 2 or 7 isolates of Al. candida. We then transformed white rust-susceptible cultivars of B. juncea (susceptible to race 2) and B. napus (susceptible to race 7) with the WRR4 gene from A. thaliana. The WRR4-transformed lines were resistant to the corresponding Al. candida race for each host species. The combined data indicate that WRR4 could potentially provide a novel source of white rust resistance in oilseed and vegetable brassica crops

It’s all about balance: Graduate Teaching Assistant reflections on finding balance between teaching, learning, and research.

Expected to demonstrate merit in teaching, research, or in many cases both, academics are under increasing pressure to meet institutional expectations of excellence, requiring an ability to balance the myriad of ever-growing responsibilities placed upon them. This excellence, no longer only expected of seasoned academics, has resulted in increased pressures for those at all levels of academia. Positioned in university departments across the UK, Graduate Teaching Assistants (GTAs) are experiencing first-hand the complexities of this balancing act, in some cases stretched further due to their student positions. As a GTA there is an expectation that alongside PhD studies students will perform a range of teaching and assessment-based duties across undergraduate programmes. In theory the responsibilities of a GTA should be both limited and manageable, without compromising their ability to focus on their own studies; however, the reality of the role is often misaligned with the projected ideal. For many GTAs the experience of teaching, including the related responsibilities, results in significant time pressures, where time allocation trade-offs between PhD study and the tasks associated with their teaching roles become commonplace. Using reflections of former and current GTAs at a UK business school, this paper seeks to explore the realities of balancing teaching, learning and research; critically assessing the concept of balance using the contrasting perspectives of Inter-Role Conflict Theory (Greenhaus & Beutell, 1985) and Interrole Facilitation (Frone, 2003) to provide insights into how these sometimes conflicting responsibilities are shaping our future academics

Structural design with Accoya wood

The benefits from acetylation of wood to enhance resistance against fungal decay and dimensional stability have been known for many years. Since 2007 Accsys Technologies has been commercially producing Accoya wood that is based on acetylation of Radiata pine. Accoya has shown its potential for many applications, even for structural use. However, due to limited engineering data each project had to be evaluated on a case-by-case basis. Based on research at various universities and institutes, Accsys Technologies has in combination with TimberSolve and ARUP, developed a handbook to assist designers and structural engineers produce reliable, durable and consistent designs utilising Accoya wood in structural applications

PCPP: A MATLAB application for abnormal infant movement detection from video

PCPP is an application developed in MATLAB, for the detection of abnormal infant movements associated with cerebral palsy. This system uses 2D skeletal data extracted from videos, and consists of a full pipeline providing data pre-processing, data normalization, feature extraction and classification. Evaluation metrics, such as accuracy, sensitivity, specificity, F1 score and Matthews Correlation Coefficient (MCC), are computed to facilitate full assessment of performance and allow for comparison with other methods from the literature. These evaluations are conducted on the MINI-RGBD and RVI-38 datasets using the code and data provided