The Feeling of Color: A Haptic Feedback Device for the Visually Disabled

Tapson J, Gurari N, Diaz J, et al. The Feeling of Color: A Haptic Feedback Device for the Visually Disabled. Presented at the Biomedical Circuits and Systems Conference (BIOCAS), Baltimore, MD.We describe a sensory augmentation system designed to provide the visually disabled with a sense of color. Our system consists of a glove with short-range optical color sensors mounted on its fingertips, and a torso-worn belt on which tactors (haptic feedback actuators) are mounted. Each fingertip sensor detects the observed objectpsilas color. This information is encoded to the tactor through vibrations in respective locations and varying modulations. Early results suggest that detection of primary colors is possible with near 100% accuracy and moderate latency, with a minimum amount of training

The effect of backing material on the transmitting response level and bandwidth of a wideband underwater transmitting transducer using 1-3 piezocomposite material

AbstractIncreasing operating depths of autonomous underwater vehicles have necessitated the development of underwater transducers that can operate at a greater depth. This paper investigates the possibility of incorporating rigid backing material into the transducer design to increase its stiffness and depth capability without adversely affecting its wide bandwidth and high transmitting levels. The transducer design under consideration uses 1-3 piezocomposite material, matching layer, coupling layer, stiff backing material (backing plates) and operates at 300 kHz with 200 kHz 6dB bandwidth

Synthesis of neural networks for spatio-temporal spike pattern recognition and processing

The advent of large scale neural computational platforms has highlighted the lack of algorithms for synthesis of neural structures to perform predefined cognitive tasks. The Neural Engineering Framework offers one such synthesis, but it is most effective for a spike rate representation of neural information, and it requires a large number of neurons to implement simple functions. We describe a neural network synthesis method that generates synaptic connectivity for neurons which process time-encoded neural signals, and which makes very sparse use of neurons. The method allows the user to specify, arbitrarily, neuronal characteristics such as axonal and dendritic delays, and synaptic transfer functions, and then solves for the optimal input-output relationship using computed dendritic weights. The method may be used for batch or online learning and has an extremely fast optimization process. We demonstrate its use in generating a network to recognize speech which is sparsely encoded as spike times.Comment: In submission to Frontiers in Neuromorphic Engineerin

Governing body nurses' experiences of clinical commissioning groups: an observational study of two clinical commissioning groups (CCGs) in England

Clinical commissioning groups (CCGs) were set up under the Health & Social Care Act (2012) in England to commission healthcare services for local communities. Governing body nurses (GBNs) provide nursing leadership to commissioning services on CCGs. Little is known about how nurses function on clinical commissioning groups. We conducted observations of seven formal meetings, three informal observation sessions, and seven interviews from January 2015 to July 2015 in two CCGs in the South of England. Implicit in the GBN role is the enduring and contested assumption that nurses embody the values of caring, perception and compassion. This assumption undermines the authority of nurses in multidisciplinary teams where authority is traditionally clinically based. Emerging roles within CCGs are not based on clinical expertise but on well-established new public management concepts which promote governance over clinically based authority. While GBNS claim an authority located in clinical and managerial expertise, this is contested by members of the CCG and external stakeholders irrespective of whether it is aligned with clinical knowledge and practice or with new forms of management, as both disregard the type of expertise nurses in commissioning embody. Key words: case study; clinical commissioning groups; governing body nurses; leadership; authority; observation

Do governing body and CSU nurses on clinical commissioning groups really lead a nursing agenda? Findings from a 2015 Survey of the Commissioning Nurse Leaders’ Network Membership

Aims This paper presents findings from a 2015 survey of the Commissioning Nurse Leaders’ Network (CNLN) aiming to understand how governing body nurses (GBNs), perceive their influence and leadership on clinical commissioning groups (CCGs). Methods An online survey method was used with a census sample of 238 GBNs and nurses working in CSUs, who were members of the CNLN. The response rate was 40.7% (n=97). Results While most GBNs felt confident in their leadership role, this was less so for non-executive GBNs and nurses in CSUs were much less positive than GBNs about their influence on CCGs. Conclusions Despite GBNs’ satisfaction with their impact on CCGs, there is no reliable evidence of this impact. The purpose of such roles to "represent nursing, and ensure the patient voice is heard” (NHSCC 2016:9) may be a flawed aspiration, conflating nursing leadership and patient voice. Implications for Nursing Management This is the first study to explicitly explore differences between executive and non-executive GBNs and CSUs. Achieving CCG goals, including developing and embedding nursing leadership roles in CCGs, may be threatened if the contributions of GBNs, and other nurses supporting, CCGS, go unrecognised or if GPs or other CCG executive members dominate decision-making

Are senior nurses on clinical commissioning groups in England inadvertently supporting the devaluation of their profession?: A critical integrative review of the literature

This paper discusses the role of senior nurses who sit on clinical commissioning groups that now plan and procure most health services in England. These nurses are expected to bring a nursing view to all aspects of clinical commissioning group business (National Health Service England 2014a; Olphert 2014). The role is a senior level appointment and requires experience of strategic commissioning. However little is known about how nurses function in these roles. Following Barrientos’ methodology (1998), published policy and literature were analysed to investigate these roles and NHS England’s claim that nursing can influence and advance a nursing perspective in clinical commissioning groups. Drawing on work by Berg et al (2008, 2014) on ‘new public management’ we discuss how nurses on clinical commissioning groups work at the alignment of the interests of biomedicine and managerialism. We propose that the way this nursing role is being implemented might paradoxically offer further evidence of the devaluing of nursing (Latimer 2014) rather than the emergence of a strong professional nursing voice at the level of strategic commissioning

Explicit Computation of Input Weights in Extreme Learning Machines

We present a closed form expression for initializing the input weights in a multi-layer perceptron, which can be used as the first step in synthesis of an Extreme Learning Ma-chine. The expression is based on the standard function for a separating hyperplane as computed in multilayer perceptrons and linear Support Vector Machines; that is, as a linear combination of input data samples. In the absence of supervised training for the input weights, random linear combinations of training data samples are used to project the input data to a higher dimensional hidden layer. The hidden layer weights are solved in the standard ELM fashion by computing the pseudoinverse of the hidden layer outputs and multiplying by the desired output values. All weights for this method can be computed in a single pass, and the resulting networks are more accurate and more consistent on some standard problems than regular ELM networks of the same size.Comment: In submission for the ELM 2014 Conferenc

Fast, simple and accurate handwritten digit classification by training shallow neural network classifiers with the 'extreme learning machine' algorithm

Recent advances in training deep (multi-layer) architectures have inspired a renaissance in neural network use. For example, deep convolutional networks are becoming the default option for difficult tasks on large datasets, such as image and speech recognition. However, here we show that error rates below 1% on the MNIST handwritten digit benchmark can be replicated with shallow non-convolutional neural networks. This is achieved by training such networks using the 'Extreme Learning Machine' (ELM) approach, which also enables a very rapid training time (∼ 10 minutes). Adding distortions, as is common practise for MNIST, reduces error rates even further. Our methods are also shown to be capable of achieving less than 5.5% error rates on the NORB image database. To achieve these results, we introduce several enhancements to the standard ELM algorithm, which individually and in combination can significantly improve performance. The main innovation is to ensure each hidden-unit operates only on a randomly sized and positioned patch of each image. This form of random 'receptive field' sampling of the input ensures the input weight matrix is sparse, with about 90% of weights equal to zero. Furthermore, combining our methods with a small number of iterations of a single-batch backpropagation method can significantly reduce the number of hidden-units required to achieve a particular performance. Our close to state-of-the-art results for MNIST and NORB suggest that the ease of use and accuracy of the ELM algorithm for designing a single-hidden-layer neural network classifier should cause it to be given greater consideration either as a standalone method for simpler problems, or as the final classification stage in deep neural networks applied to more difficult problems.Mark D. McDonnell, Migel D. Tissera, Tony Vladusich, André van Schaik, Jonathan Tapso

Efficacy and safety outcomes of recanalization procedures in patients with acute symptomatic pulmonary embolism: systematic review and network meta-analysis.

Background We aimed to review the efficacy and safety of recanalisation procedures for the treatment of PE. Methods We searched PubMed, the Cochrane Library, EMBASE, EBSCO, Web of Science and CINAHL databases from inception through 31 July 2015 and included randomised clinical trials that compared the effect of a recanalisation procedure versus each other or anticoagulant therapy in patients diagnosed with PE. We used network meta-analysis and multivariate randomeffects meta-regression to estimate pooled differences between each intervention and meta-regression to assess the association between trial characteristics and the reported effects of recanalisation procedures versus anticoagulation. Results For all-cause mortality, there were no significant differences in event rates between any of the recanalisation procedures and anticoagulant treatment (full-dose thrombolysis: OR 0.60; 95% CI0.36 to 1.01; low-dose thrombolysis: 0.47; 95%CI 0.14 to 1.59; and catheter-associated thrombolysis: 0.31; 95%CI 0.01 to 7.96). Full-dose thrombolysis increased the risk of major bleeding (2.00; 95%CI 1.06 to 3.78) compared with anticoagulation. Catheter-directed thrombolysis was associated with the lowest probability of dying (surface under the cumulative ranking curve (SUCRA), 0.67), followed by low-dose thrombolysis (SUCRA, 0.66) and full-dose thrombolysis (SUCRA, 0.55). Similarly, low-dose thrombolysis was associated with the lowest probability of major bleeding (SUCRA, 0.61), followed by catheterdirected thrombolysis (SUCRA, 0.54) and full-dose thrombolysis (SUCRA, 0.17). The results were similar in sensitivity analyses based on restricting only to studies in haemodynamically stable patients with PE. Conclusions In the treatment of PE, recanalisation procedures do not seem to offer a clear advantage compared with standard anticoagulation. Low-dose thrombolysis was associated with the lowest probability of dying and bleedingpre-print549 K