Neuromorphic Tactile Sensing System for Textural Features Classification

Artificial tactile sensing systems have gained significant attention in recent years due to their potential to enhance human-machine interaction. Numerous initiatives have been introduced to shift the computational paradigms of these systems towards a more biologically inspired approach, by incorporating neuromorphic computing methods. Despite the significant advances made by these systems, dependence on complex offline methods for classification (i.e. hand-crafted encoding features), remains a limitation for their real-time deployment. In this work, we present a neuromorphic tactile PVDF-based sensing system for textural features classification, that employs raw signals directly for classification. We first converted raw signals into spikes and then trained recurrent spiking neural networks (RSNNs) using Backpropagation Through Time (BPTT) with surrogate gradients to perform classification. We proposed an optimization method based on tuning the refractory period of the encoding neurons, to explore a potential trade-off between the computational cost and classification accuracy of the RSNN. The proposed method effectively identified two RSNNs with refractory period configurations that achieved a trade-off between the two evaluation metrics. Following this, we reduced the inference time steps of the selected RSNN during inference using a rate-coding based method. This method succeeded in saving around 26.6% out of the total original time steps. In summary, the proposed system paves the way for establishing an end-to-end neuromorphic approach for tactile textural features classification, through deploying the selected RSNNs on a dedicated neuromorphic hardware device for real-time inferences

Convalescent plasma in patients admitted to hospital with COVID-19 (RECOVERY): a randomised controlled, open-label, platform trial

Background: Many patients with COVID-19 have been treated with plasma containing anti-SARS-CoV-2 antibodies. We aimed to evaluate the safety and efficacy of convalescent plasma therapy in patients admitted to hospital with COVID-19. Methods: This randomised, controlled, open-label, platform trial (Randomised Evaluation of COVID-19 Therapy [RECOVERY]) is assessing several possible treatments in patients hospitalised with COVID-19 in the UK. The trial is underway at 177 NHS hospitals from across the UK. Eligible and consenting patients were randomly assigned (1:1) to receive either usual care alone (usual care group) or usual care plus high-titre convalescent plasma (convalescent plasma group). The primary outcome was 28-day mortality, analysed on an intention-to-treat basis. The trial is registered with ISRCTN, 50189673, and ClinicalTrials.gov, NCT04381936. Findings: Between May 28, 2020, and Jan 15, 2021, 11558 (71%) of 16287 patients enrolled in RECOVERY were eligible to receive convalescent plasma and were assigned to either the convalescent plasma group or the usual care group. There was no significant difference in 28-day mortality between the two groups: 1399 (24%) of 5795 patients in the convalescent plasma group and 1408 (24%) of 5763 patients in the usual care group died within 28 days (rate ratio 1·00, 95% CI 0·93–1·07; p=0·95). The 28-day mortality rate ratio was similar in all prespecified subgroups of patients, including in those patients without detectable SARS-CoV-2 antibodies at randomisation. Allocation to convalescent plasma had no significant effect on the proportion of patients discharged from hospital within 28 days (3832 [66%] patients in the convalescent plasma group vs 3822 [66%] patients in the usual care group; rate ratio 0·99, 95% CI 0·94–1·03; p=0·57). Among those not on invasive mechanical ventilation at randomisation, there was no significant difference in the proportion of patients meeting the composite endpoint of progression to invasive mechanical ventilation or death (1568 [29%] of 5493 patients in the convalescent plasma group vs 1568 [29%] of 5448 patients in the usual care group; rate ratio 0·99, 95% CI 0·93–1·05; p=0·79). Interpretation: In patients hospitalised with COVID-19, high-titre convalescent plasma did not improve survival or other prespecified clinical outcomes. Funding: UK Research and Innovation (Medical Research Council) and National Institute of Health Research

Tocilizumab in patients admitted to hospital with COVID-19 (RECOVERY): a randomised, controlled, open-label, platform trial

Background: In this study, we aimed to evaluate the effects of tocilizumab in adult patients admitted to hospital with COVID-19 with both hypoxia and systemic inflammation. Methods: This randomised, controlled, open-label, platform trial (Randomised Evaluation of COVID-19 Therapy [RECOVERY]), is assessing several possible treatments in patients hospitalised with COVID-19 in the UK. Those trial participants with hypoxia (oxygen saturation <92% on air or requiring oxygen therapy) and evidence of systemic inflammation (C-reactive protein ≥75 mg/L) were eligible for random assignment in a 1:1 ratio to usual standard of care alone versus usual standard of care plus tocilizumab at a dose of 400 mg–800 mg (depending on weight) given intravenously. A second dose could be given 12–24 h later if the patient's condition had not improved. The primary outcome was 28-day mortality, assessed in the intention-to-treat population. The trial is registered with ISRCTN (50189673) and ClinicalTrials.gov (NCT04381936). Findings: Between April 23, 2020, and Jan 24, 2021, 4116 adults of 21 550 patients enrolled into the RECOVERY trial were included in the assessment of tocilizumab, including 3385 (82%) patients receiving systemic corticosteroids. Overall, 621 (31%) of the 2022 patients allocated tocilizumab and 729 (35%) of the 2094 patients allocated to usual care died within 28 days (rate ratio 0·85; 95% CI 0·76–0·94; p=0·0028). Consistent results were seen in all prespecified subgroups of patients, including those receiving systemic corticosteroids. Patients allocated to tocilizumab were more likely to be discharged from hospital within 28 days (57% vs 50%; rate ratio 1·22; 1·12–1·33; p<0·0001). Among those not receiving invasive mechanical ventilation at baseline, patients allocated tocilizumab were less likely to reach the composite endpoint of invasive mechanical ventilation or death (35% vs 42%; risk ratio 0·84; 95% CI 0·77–0·92; p<0·0001). Interpretation: In hospitalised COVID-19 patients with hypoxia and systemic inflammation, tocilizumab improved survival and other clinical outcomes. These benefits were seen regardless of the amount of respiratory support and were additional to the benefits of systemic corticosteroids. Funding: UK Research and Innovation (Medical Research Council) and National Institute of Health Research

Convalescent plasma in patients admitted to hospital with COVID-19 (RECOVERY): a randomised controlled, open-label, platform trial

SummaryBackground Azithromycin has been proposed as a treatment for COVID-19 on the basis of its immunomodulatoryactions. We aimed to evaluate the safety and efficacy of azithromycin in patients admitted to hospital with COVID-19.Methods In this randomised, controlled, open-label, adaptive platform trial (Randomised Evaluation of COVID-19Therapy [RECOVERY]), several possible treatments were compared with usual care in patients admitted to hospitalwith COVID-19 in the UK. The trial is underway at 176 hospitals in the UK. Eligible and consenting patients wererandomly allocated to either usual standard of care alone or usual standard of care plus azithromycin 500 mg once perday by mouth or intravenously for 10 days or until discharge (or allocation to one of the other RECOVERY treatmentgroups). Patients were assigned via web-based simple (unstratified) randomisation with allocation concealment andwere twice as likely to be randomly assigned to usual care than to any of the active treatment groups. Participants andlocal study staff were not masked to the allocated treatment, but all others involved in the trial were masked to theoutcome data during the trial. The primary outcome was 28-day all-cause mortality, assessed in the intention-to-treatpopulation. The trial is registered with ISRCTN, 50189673, and ClinicalTrials.gov, NCT04381936.Findings Between April 7 and Nov 27, 2020, of 16 442 patients enrolled in the RECOVERY trial, 9433 (57%) wereeligible and 7763 were included in the assessment of azithromycin. The mean age of these study participants was65·3 years (SD 15·7) and approximately a third were women (2944 [38%] of 7763). 2582 patients were randomlyallocated to receive azithromycin and 5181 patients were randomly allocated to usual care alone. Overall,561 (22%) patients allocated to azithromycin and 1162 (22%) patients allocated to usual care died within 28 days(rate ratio 0·97, 95% CI 0·87–1·07; p=0·50). No significant difference was seen in duration of hospital stay (median10 days [IQR 5 to >28] vs 11 days [5 to >28]) or the proportion of patients discharged from hospital alive within 28 days(rate ratio 1·04, 95% CI 0·98–1·10; p=0·19). Among those not on invasive mechanical ventilation at baseline, nosignificant difference was seen in the proportion meeting the composite endpoint of invasive mechanical ventilationor death (risk ratio 0·95, 95% CI 0·87–1·03; p=0·24).Interpretation In patients admitted to hospital with COVID-19, azithromycin did not improve survival or otherprespecified clinical outcomes. Azithromycin use in patients admitted to hospital with COVID-19 should be restrictedto patients in whom there is a clear antimicrobial indication

Building a trust model for generating and validating assurance keys between consumers in E-commerce

This study investigates trust building among members of virtual communities (VC) as an effective way in E-Commerce from the consumer-to-consumer (C2C) perspective. So it reviews studies in E-Commerce, which focus on trust building in the other party. It also reviews websites operating in the same area, the most common of which is eBay; it relies on trust in the other party in the payment method of PayPal, which accepts credit cards. However, this method has a number of limitations, including that fact that online registration does not verify if the user is the owner of the card; thus, it renders the consumer entirely untrustworthy. As a result, this paper attempts to provide a more trusted method that ensures to identity the other party by building a database of trusted third parties (TTP), based a new algorithm for generating and validating assurance keys (AK's) to all consumers in the world. The AK is saved as the name of the image of the consumer in the database image-DB file of the TTP, and using the AK in the verification of the consumer when making a sale or purchase

Effect of weight around ankle on decreasing hip flexion excursion during gait in children with diplegia

Introduction Children with diplegia have considerably larger hip flexion excursion during the gait cycle than normal developing children. There have been few studies that look at the effect of ankle loading on gait in children with hemiparesis, but none that look at the effect of ankle loading on hip flexion angles during gait in children with diplegia, to our knowledge. The purpose of the study is to evaluate the effect of using a weight around the ankle on the degree of hip flexion excursion in children with diplegia. Methods Fifty children with spastic diplegia were assigned into 2 groups at random (A, B). Both groups received the same prescribed exercise program with gait training for group A and gait training while using a weight around the ankle for group B. Treatment was conducted for 1 hour 3 sessions/week for 3 successive months. Two-dimensional (2D) gait analysis was used to evaluate hip excursion throughout the gait cycle before and after the 3 months of therapy. Results Mixed design MANOVA was used to study the effect within each group and between the 2 groups. A comparison of both groups after treatment demonstrated a significant decrease in right and left hip flexion excursion in the initial swing, mid-swing, terminal swing, initial contact, mid-stance, and pre-swing ( p > 0.01). There was no significant difference in loading response between groups after treatment ( p = 0.3). Conclusions Using weight around the ankle during gait helped to decrease the degree of excessive hip flexion excursion during gait in children with diplegia

Embedded feedback system for upper limb prosthetics

This paper proposes an embedded tactile sensory feedback system for the upper-limb prosthesis. The feedback system delivers tactile information extracted from tactile sensors to the user through electrocutaneous stimulation. The proposed system has been tested experimentally on three healthy subjects. Results demonstrate the correct feedback of the tactile information when the subjects were able to identify the location and the contact pressure level applied to the sensor arrays with a recognition rate of 86%. The system can provide feedback with a delay of around 32 ms while consuming 300 mW opening up interesting perspectives for wearable feedback systems for prosthetics

Smart tactile sensing systems based on embedded CNN implementations

Embedding machine learning methods into the data decoding units may enable the extraction of complex information making the tactile sensing systems intelligent. This paper presents and compares the implementations of a convolutional neural network model for tactile data decoding on various hardware platforms. Experimental results show comparable classification accuracy of 90.88% for Model 3, overcoming similar state-of-the-art solutions in terms of time inference. The proposed implementation achieves a time inference of 1.2 ms while consuming around 900 \u3bcJ. Such an embedded implementation of intelligent tactile data decoding algorithms enables tactile sensing systems in different application domains such as robotics and prosthetic devices

Touch Modality Classification Using Recurrent Neural Networks

Recurrent Neural Networks (RNNs) are mainly designed to deal with sequence prediction problems and they show their effectiveness in processing data originally represented as time series. This paper investigates the time series characteristics of RNNs to classify touch modalities represented as spatio temporal 3D tensor data. Different approaches are followed in order to propose efficient RNN models aimed at tactile data classification. The main idea is to capture long-term dependence from data that can be used to deal with long sequences represented by employing Gated Recurrent Unit (GRU) and Long Short-Term Memory (LSTM) architectures. Moreover, a case specific approach to dataset organization of the 3D tensor data is presented. The target is to provide efficient hardware-friendly touch modality classification approaches suitable for embedded applications. To this end, the proposed work achieves effective performance in terms of hardware complexity by reducing the FLOPS by 99.98% and the memory storage by 98.34%, with respect to the state-of-art solutions on the same benchmark dataset. This directly affects the time latency and energy consumption of the embedded hardware. Besides, the implemented models shows a classification accuracy higher than those state-of-art solutions. Results demonstrate that the proposed computing architecture is scalable showing acceptable complexity when the system is scaled up in terms of input matrix size and number of classes to be recognized

Trends in Healthcare Resource Use Preceding Diagnosis of Alzheimer’s Disease Dementia

Introduction. An Alzheimer’s disease (AD) dementia diagnosis is often preceded by an extended period of cognitive decline. Few studies have examined healthcare resource use (HRU) during an extended period before AD dementia diagnosis. Methods. In a historical claims-based cohort study, propensity score-matched cohorts of patients with and without AD dementia were observed for a 5-year prediagnosis period and a 1-year postdiagnosis period. Demographics, clinical characteristics, and HRU were compared between groups. Results. Individuals in the AD dementia group displayed a greater level of medical complexity in the year before diagnosis of AD dementia relative to those in the matched cohort. Both all-cause and AD dementia complication-related HRU increased gradually, with a marked spike at the time of initial AD dementia diagnosis. Discussion. Further research into the natural history of patients with AD dementia is necessary to improve identification of early AD and to better understand its broader impact