AI enhanced collaborative human-machine interactions for home-based telerehabilitation

The use of robots in a telerehabilitation paradigm could facilitate the delivery of rehabilitation on demand while reducing transportation time and cost. As a result, it helps to motivate patients to exercise frequently in a more comfortable home environment. However, for such a paradigm to work, it is essential that the robustness of the system is not compromised due to network latency, jitter, and delay of the internet. This paper proposes a solution to data loss compensation to maintain the quality of the interaction between the user and the system. Data collected from a well-defined collaborative task using a virtual reality (VR) environment was used to train a robotic system to adapt to the users' behaviour. The proposed approach uses nonlinear autoregressive models with exogenous input (NARX) and long-short term memory (LSTM) neural networks to smooth out the interaction between the user and the predicted movements generated from the system. LSTM neural networks are shown to learn to act like an actual human. The results from this paper have shown that, with an appropriate training method, the artificial predictor can perform very well by allowing the predictor to complete the task within 25 s versus 23 s when executed by the human

Uteroplacental bleeding disorders during pregnancy: do missing paternal characteristics influence risk?

BACKGROUND: Several studies have assessed the risks of uteroplacental bleeding disorders in relation to maternal characteristics. The association between uteroplacental bleeding disorders and paternal characteristics, however, has received considerably less attention. Data on paternal demographics, notably race and age, from birth certificate data are becoming increasingly incomplete in recent years. This pattern of increasingly underreporting of paternal demographic data led us to speculate that pregnancies for which paternal characteristics are partially or completely missing may be associated with increased risk for uteroplacental bleeding disorders. The objective of this study is to examine the association between placenta previa and placental abruption and missing paternal age and race. METHODS: A retrospective cohort study using U.S. linked birth/infant death data from 1995 through 2001 (n = 26,336,549) was performed. Risks of placenta previa and placental abruption among: (i) pregnancies with complete paternal age and race data; (ii) paternal age only missing; (iii) paternal race only missing; and (iv) both paternal age and race missing, were evaluated. Relative risk (RR) with 95% confidence interval (CI) for placenta previa and placental abruption by missing paternal characteristics were derived after adjusting for confounders. RESULTS: Adjusted RR for placental abruption were 1.30 (95% CI 1.24, 1.37), 1.00 (95% CI 0.95, 1.05), and 1.08 (95% CI 1.06, 1.10) among pregnancies with "paternal age only", "paternal race only", and "both paternal age and race" missing, respectively. The increased risk of placental abruption among the "paternal age only missing" category is partly explained by increased risks among whites aged 20–29 years, and among blacks aged ≥30 years. However, no clear patterns in the associations between missing paternal characteristics and placenta previa were evident. CONCLUSION: Missing paternal characteristics are associated with increased risk of placental abruption, likely mediated through low socio-economic conditions

Participants' uptake of clinical trial results: a randomised experiment

BJC OPENInternational audienceBACKGROUND: Participants are showing great interest these days in obtaining the results of clinical trials. The aim of this study was to assess patients' uptake and understanding of the results of the trial in which they have participated and the impact of a letter offering patients the possibility of consulting the trial results on a specific website. METHODS: Breast cancer patients participating in a trial on the efficacy of Trastuzumab were randomly subdivided into an Internet group (who received the letter of invitation) and a control group (who did not receive it). Among 115 HER2-positive women from 21 centres, 107 (93%) answered a self-administered questionnaire. RESULTS: Most of the patients in both groups had access to the Internet (72.0%). The majority (97.2%) stated that receiving information about the trial results would be useful, and the oncologist was the most frequently preferred information provider. The Internet group's declared uptake of the trial results was only slightly higher (47.1% vs 33.9%; P=0.166); however, they understood the results significantly more accurately (18.8% vs 5.6%; P=0.039). INTERPRETATION: Although Internet was not the respondents' preferred source of information, the possibility of using this source slightly increased the uptake and understanding of the results

Maximum-Reward Motion in a Stochastic Environment: The Nonequilibrium Statistical Mechanics Perspective

We consider the problem of computing the maximum-reward motion in a reward field in an online setting. We assume that the robot has a limited perception range, and it discovers the reward field on the fly. We analyze the performance of a simple, practical lattice-based algorithm with respect to the perception range. Our main result is that, with very little perception range, the robot can collect as much reward as if it could see the whole reward field, under certain assumptions. Along the way, we establish novel connections between this class of problems and certain fundamental problems of nonequilibrium statistical mechanics . We demonstrate our results in simulation examples

A methodology for automated feature engineering in training of shallow neural networks for prediction of multi-linear growth failures (“Nova Algorithm”)

Deep learning requires a large data set. When working with smaller data sets we need an automated approach for feature learning as a pre-processing step to create the training set for a shallow neural network with one hidden layer. The outcome of the neural net classifier is filtered using post-processing rules over a defined wait and quiet period to create an ensemble prediction with higher quality. This gives us the benefits of deep learning, but with a smaller data set. A partial implementation of this methodology was used for a pilot release for prediction of Common Previsioning Group (CPG) growth failures in 3PAR storage devices, using a trained neural net model with additional derived attributes, pre-processing rules and post-processing steps, applied to 90 days history of logical disk free space for each CPG on the storage device

How does reviewing the evidence change veterinary surgeons' beliefs regarding the treatment of ovine footrot? A quantitative and qualitative study

Footrot is a widespread, infectious cause of lameness in sheep, with major economic and welfare costs. The aims of this research were: (i) to quantify how veterinary surgeons’ beliefs regarding the efficacy of two treatments for footrot changed following a review of the evidence (ii) to obtain a consensus opinion following group discussions (iii) to capture complementary qualitative data to place their beliefs within a broader clinical context. Grounded in a Bayesian statistical framework, probabilistic elicitation (roulette method) was used to quantify the beliefs of eleven veterinary surgeons during two one-day workshops. There was considerable heterogeneity in veterinary surgeons’ beliefs before they listened to a review of the evidence. After hearing the evidence, seven participants quantifiably changed their beliefs. In particular, two participants who initially believed that foot trimming with topical oxytetracycline was the better treatment, changed to entirely favour systemic and topical oxytetracycline instead. The results suggest that a substantial amount of the variation in beliefs related to differences in veterinary surgeons’ knowledge of the evidence. Although considerable differences in opinion still remained after the evidence review, with several participants having non-overlapping 95% credible intervals, both groups did achieve a consensus opinion. Two key findings from the qualitative data were: (i) veterinary surgeons believed that farmers are unlikely to actively seek advice on lameness, suggesting a proactive veterinary approach is required (ii) more attention could be given to improving the way in which veterinary advice is delivered to farmers. In summary this study has: (i) demonstrated a practical method for probabilistically quantifying how veterinary surgeons’ beliefs change (ii) revealed that the evidence that currently exists is capable of changing veterinary opinion (iii) suggested that improved transfer of research knowledge into veterinary practice is needed (iv) identified some potential obstacles to the implementation of veterinary advice by farmers

Feedback control architecture and the bacterial chemotaxis network.

PMCID: PMC3088647This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.Bacteria move towards favourable and away from toxic environments by changing their swimming pattern. This response is regulated by the chemotaxis signalling pathway, which has an important feature: it uses feedback to 'reset' (adapt) the bacterial sensing ability, which allows the bacteria to sense a range of background environmental changes. The role of this feedback has been studied extensively in the simple chemotaxis pathway of Escherichia coli. However it has been recently found that the majority of bacteria have multiple chemotaxis homologues of the E. coli proteins, resulting in more complex pathways. In this paper we investigate the configuration and role of feedback in Rhodobacter sphaeroides, a bacterium containing multiple homologues of the chemotaxis proteins found in E. coli. Multiple proteins could produce different possible feedback configurations, each having different chemotactic performance qualities and levels of robustness to variations and uncertainties in biological parameters and to intracellular noise. We develop four models corresponding to different feedback configurations. Using a series of carefully designed experiments we discriminate between these models and invalidate three of them. When these models are examined in terms of robustness to noise and parametric uncertainties, we find that the non-invalidated model is superior to the others. Moreover, it has a 'cascade control' feedback architecture which is used extensively in engineering to improve system performance, including robustness. Given that the majority of bacteria are known to have multiple chemotaxis pathways, in this paper we show that some feedback architectures allow them to have better performance than others. In particular, cascade control may be an important feature in achieving robust functionality in more complex signalling pathways and in improving their performance

INGA 3D - creative transfer of competence in 3D footwear CAD to VET professionals

INGA 3D project - Creative Transfer of Competence in 3D Footwear CAD to VET Professionals aims to transfer and extend innovative software solutions and 3D technologies for Footwear Computer Aided Design. The project brings together universities, research and training centres, adult education providers and IT companies from Romania, Spain, Portugal, and UK. The project products introduce innovative solutions for e-learning in order to test and to validate new teaching methodologies and approaches suitable for vocational training. The INGA 3D training content, its supportive guide as well as the online learning platform was designed, developed, tested and evaluated in line with the best practices identified by partners in their institutions, countries and elsewhere in Europe. INGA 3D project contributes to developing skills and competencies of VET teachers, trainers, tutors, in order to face the future challenges raised by the necessity of adding to the current curricula in VET institutions ICT skill sets that will enable their graduates to work with highly specialized footwear CAD technologies