Providing service guarantees in 802.11e EDCA WLANs with legacy stations

Although the EDCA access mechanism of the 802.11e standard supports legacy DCF stations, the presence of DCF stations in the WLAN jeopardizes the provisioning of the service guarantees committed to the EDCA stations. The reason is that DCF stations compete with Contention Windows (CWs) that are predefined and cannot be modified, and as a result, the impact of the DCF stations on the service received by the EDCA stations cannot be controlled. In this paper, we address the problem of providing throughput guarantees to EDCA stations in a WLAN in which EDCA and DCF stations coexist. To this aim, we propose a technique that, implemented at the Access Point (AP), mitigates the impact of DCF stations on EDCA by skipping with a certain probability the Ack reply to a frame from a DCF station. When missing the Ack, the DCF station increases its CW, and thus, our technique allows us to have some control over the CWs of the legacy DCF stations. In our approach, the probability of skipping an Ack frame is dynamically adjusted by means of an adaptive algorithm. This algorithm is based on a widely used controller from classical control theory, namely a Proportional Controller. In order to find an adequate configuration of the controller, we conduct a control-theoretic analysis of the system. Simulation results show that the proposed approach is effective in providing throughput guarantees to EDCA stations in presence of DCF stations.European Community's Seventh Framework ProgramPartly funded by the Ministry of Science and Innovation of Spain, under the QUARTET project (TIN2009-13992-C02-01)Publicad

A modular telerehabilitation architecture for upper limb robotic therapy

Several factors may prevent post-stroke subjects from participating in rehabilitation protocols, for example, geographical location of rehabilitation centres, socioeconomic status, economic burden and lack of logistics surrounding transportation. Early supported discharge from hospitals with continued rehabilitation at home represents a well-defined regimen of post-stroke treatment. Information-based technologies coupled with robotics have promoted the development of new technologies for telerehabilitation. In this article, the design and development of a modular architecture for delivering upper limb robotic telerehabilitation with the CBM-Motus, a planar unilateral robotic machine that allows performing state-of-the-art rehabilitation tasks, have been presented. The proposed architecture allows a therapist to set a therapy session on his or her side and send it to the patient's side with a standardized communication protocol; the user interacts with the robot that provides an adaptive assistance during the rehabilitation tasks. Patient's performance is evaluated by means of performance indicators, which are also used to update robot behaviour during assistance. The implementation of the architecture is described and a set of validation tests on seven healthy subjects are presented. Results show the reliability of the novel architecture and the capability to be easily tailored to the user's needs with the chosen robotic device

Adaptive Streaming On Heterogeneous Networks”,

ABSTRACT Specific network protocols, like MobileIP, offer seamless connectivity to mobile systems. However, the QoS requirements of streaming applications and video conferencing systems require an approach that spans across different layers of the network stack. In this paper we study how to integrate an efficient method for vertical handoff and adaptation support for multimedia streaming through heterogeneous networks. We also present experimental results obtained with our prototype on IEEE 802.11 and UMTS networks

TMS-EEG biomarkers of amnestic mild cognitive impairment due to Alzheimer\u27s disease: A proof-of-concept six years prospective study

Background: Early and affordable identification of subjects with amnestic mild cognitive impairment (aMCI) who will convert to Alzheimer’s disease (AD) is a major scientific challenge. Objective: To investigate the neurophysiological hallmarks of sensorimotor cortex function in aMCI under the hypothesis that some may represent the plastic rearrangements induced by neurodegeneration, hence predictors of future conversion to AD. We sought to determine (1) whether the sensorimotor network shows peculiar alterations in patients with aMCI and (2) if sensorimotor network alterations predict long-term disease progression at the individual level. Methods: We studied several transcranial magnetic stimulation (TMS)-electroencephalogram (EEG) parameters of the sensorimotor cortex in a group of patients with aMCI and followed them for 6 years. We then identified aMCI who clinically converted to AD [prodromal to AD-MCI (pAD-MCI)] and those who remained cognitively stable [non-prodromal to AD-MCI (npAD-MCI)]. Results: Patients with aMCI showed reduced motor cortex (M1) excitability and disrupted EEG synchronization [decreased intertrial coherence (ITC)] in alpha, beta and gamma frequency bands compared to the control subjects. The degree of alteration in M1 excitability and alpha ITC was comparable between pAD-MCI and npAD-MCI. Importantly, beta and gamma ITC impairment in the stimulated M1 was greater in pAD-MCI than npAD-MCI. Furthermore, an additional parameter related to the waveform shape of scalp signals, reflecting time-specific alterations in global TMS-induced activity [stability of the dipolar activity (sDA)], discriminated npAD-MCI from MCI who will convert to AD. Discussion: The above mentioned specific cortical changes, reflecting deficit of synchronization within the cortico-basal ganglia-thalamo-cortical loop in aMCI, may reflect the pathological processes underlying AD. These changes could be tested in larger cohorts as neurophysiological biomarkers of AD

GSP for Virtual Sensors in eHealth Applications

© 2020 IEEE.The Graph Signal Processing (GSP) is a mathematical framework that extends the Discrete Signal Processing (DSP) tools such as filtering and signals decomposition to graph data structures. In this paper, we explore the application of the GSP framework to distributed wireless sensor networks to reduce the measured noise and/or estimate the signal of missing sensors. The context is that of distributed monitoring applications, such as the monitoring of large buildings, such as hospitals, public areas and farmlands. Using simulation tools, we analysed the ability of GSP in reducing the noise and in estimating sensor's data in different WSN scenarios. We modelled the sensor networks as Graph structures and apply Graph Shift and Graph Laplacian operations on such graph signals. The analysis of obtained results shows that GSP may represent a valuable tool in the considered scenarios with outstanding performance

Fast ECG baseline wander removal preserving the ST segment

Baseline wander removal is an unavoidable preprocessing step in ECG signal analysis. Unfortunately, the in-band nature of this kind of noise makes its removal difficult without affecting ECG waveform, in particular the ST segment. This is a portion of the ECG with high clinical relevance, as it is related to the diagnosis of acute coronary syndromes. The ST segment is highly susceptible to distortion when baseline removal is performed affecting the low-frequency region of ECG spectrum, where are concentrated the harmonic components that mainly contribute to the shape of the ST segment. In this paper, we propose to tackle the problem of baseline removal from a different perspective, considering the quadratic variation as an alternative measure of variability not directly related to the frequency domain. In this regard, we recently proposed a novel baseline removal algorithm based on quadratic variation reduction. In this paper, we assess its performance with respect to the distortion of the ST segment comparing it to state-of-the-art algorithms. Simulation results confirm the effectiveness of the approach based on quadratic variation reduction. Our algorithm outperforms state-of-the-art algorithms tailored to minimize distortion of the ST segment. Moreover, it compares favorably also in terms of computational complexity, which is linear in the size of the vector to detrend. This makes it suitable also for real-time applications. © 2011 ACM