BECA: A Blockchain-Based Edge Computing Architecture for Internet of Things Systems

The scale of Internet of Things (IoT) systems has expanded in recent times and, in tandem with this, IoT solutions have developed symbiotic relationships with technologies, such as edge Computing. IoT has leveraged edge computing capabilities to improve the capabilities of IoT solutions, such as facilitating quick data retrieval, low latency response, and advanced computation, among others. However, in contrast with the benefits offered by edge computing capabilities, there are several detractors, such as centralized data storage, data ownership, privacy, data auditability, and security, which concern the IoT community. This study leveraged blockchain’s inherent capabilities, including distributed storage system, non-repudiation, privacy, security, and immutability, to provide a novel, advanced edge computing architecture for IoT systems. Specifically, this blockchain-based edge computing architecture addressed centralized data storage, data auditability, privacy, data ownership, and security. Following implementation, the performance of this solution was evaluated to quantify performance in terms of response time and resource utilization. The results show the viability of the proposed and implemented architecture, characterized by improved privacy, device data ownership, security, and data auditability while implementing decentralized storage.

Motor Responses of Lumbar Erector Spinae Induced by Electrical Vestibular Stimulation in Seated Participants

Introduction: The study of motor responses induced by electrical vestibular stimulation (EVS) may help clarify the role of the vestibular system in postural control. Although back muscles have an important role in postural control, their EVS-induced motor responses were rarely studied. Moreover, the effects of EVS parameters, head position, and vision on EVS-induced back muscles responses remain little explored.Objectives: To explore the effects of EVS parameters, head position, and vision on lumbar erector spinae muscles EVS-induced responses.Design: Exploratory, cross-sectional study.Materials and Methods: Ten healthy participants were recruited. Three head positions (right, left and no head rotation), 4 intensities (2, 3, 4, 5 mA), and 4 EVS durations (5, 20, 100, 200 ms) were tested in sitting position with eyes open or closed. EVS usually induced a body sway toward the anode (placed on the right mastoid). EMG activity of the right lumbar erector spinae was recorded. Variables of interest were amplitude, occurrence, and latency of the EVS-induced modulation of the EMG activity.Results: The short-latency response was inhibitory and the medium-latency response was excitatory. Increased EVS current intensity augmented the occurrence and the amplitude of the short- and medium-latency responses (more inhibition and more excitation, respectively). EVS duration influenced the medium-latency response differently depending on the position of the head. Right head rotation produced larger responses amplitude and occurrence than left head rotation. Opposite head rotation (left vs. right) did not induce a reversal of the short- and medium-latency responses (i.e., the inhibition did not become an excitation), as typically reported in lower legs muscles. The eyes open condition did not modulate muscle responses.Conclusion: Modulation of EVS parameters (current intensity and duration of EVS) affects the amplitude and occurrence of the lumbar erector spinae responses. In contrast, vision did not influence the responses, suggesting its minimal contribution to vestibulomotor control in sitting. The lack of response reversal in sagittal plane may reflect the biomechanical role of lumbar erector spinae to fine-tune the lumbar lordosis during the induced body sway. This hypothesis remains to be further tested.

Auditory evoked potentials as yardstick for tinnitus

<p class="abstract"><strong>Background:</strong> Aiming to evaluate the recent theoretical postulates on tinnitus underscoring the role of thalamocortical neural tracts, the present study: explores middle latency response (MLR) as a possible physiological measure of tinnitus: thus investigates the predicted exaggeration of P_a-N_a, N_a-P_b interpeak amplitudes in tinnitus patients and; explores middle latency response (MLR) as a prognostic indicator of tinnitus retraining therapy (TRT), thus evaluates possible decrease in P_a-N_a and N_a-P_b amplitude after 2 weeks exposure to tinnitus retraining therapy.</p><p class="abstract"><strong>Methods:</strong> An experimental group was constructed by randomly assigning 30 patients with mean age 38.5 years and complaining of debilitating tinnitus but with normal hearing for the study. MLR was administered on patients with normal auditory brainstem response (ABR) and otoacoustic emission (OAE) both pre- and post-tinnitus retraining therapy. </p><p class="abstract"><strong>Results:</strong> Results demonstrated no significant effect on P_a, N_a and N_b absolute and interpeak latencies. However, significantly exaggerated P_a-N_a and N_a-P_b interpeak amplitudes between experimental and control groups as well as pre and post therapeutic groups were found.</p><p class="abstract"><strong>Conclusions:</strong> This proves that MLR may adequately reflect thalamocortical hyperactivity in cases with distressing tinnitus and demonstrable improvement post TRT warrants the use of MLR as its prognostic indicator.</p>

Effects of Perturbation Velocity, Direction, Background Muscle Activation, and Task Instruction on Long-Latency Responses Measured From Forearm Muscles

The central nervous system uses feedback processes that occur at multiple time scales to control interactions with the environment. The long-latency response (LLR) is the fastest process that directly involves cortical areas, with a motoneuron response measurable 50 ms following an imposed limb displacement. Several behavioral factors concerning perturbation mechanics and the active role of muscles prior or during the perturbation can modulate the long-latency response amplitude (LLRa) in the upper limbs, but the interactions among many of these factors had not been systematically studied before. We conducted a behavioral study on thirteen healthy individuals to determine the effect and interaction of four behavioral factors – background muscle torque, perturbation direction, perturbation velocity, and task instruction – on the LLRa evoked from the flexor carpi radialis (FCR) and extensor carpi ulnaris (ECU) muscles after velocity-controlled wrist displacements. The effects of the four factors were quantified using both a 0D statistical analysis on the average perturbation-evoked EMG signal in the period corresponding to an LLR, and using a timeseries analysis of EMG signals. All factors significantly modulated LLRa, and their combination nonlinearly contributed to modulating the LLRa. Specifically, all the three-way interaction terms that could be computed without including the interaction between instruction and velocity significantly modulated the LLR. Analysis of the three-way interaction terms of the 0D model indicated that for the ECU muscle, the LLRa evoked when subjects are asked to maintain their muscle activation in response to the perturbations was greater than the one observed when subjects yielded to the perturbations (p &lt; 0.001), but this effect was not measured for muscles undergoing shortening or in absence of background muscle activation. Moreover, higher perturbation velocity increased the LLRa evoked from the stretched muscle in presence of a background torque (p &lt; 0.001), but no effects of velocity were measured in absence of background torque. Also, our analysis identified significant modulations of LLRa in muscles shortened by the perturbation, including an interaction between torque and velocity, and an effect of both torque and velocity. The time-series analysis indicated the significance of additional transient effects in the LLR region for muscles undergoing shortening.

RDAMS: An Efficient Run-Time Approach for Memory Fault and Hardware Trojans Detection

Ensuring the security of IoT devices and chips at runtime has become an urgent task as they have been widely used in human life. Embedded memories are vital components of SoC (System on Chip) in these devices. If they are attacked or incur faults at runtime, it will bring huge losses. In this paper, we propose a run-time detection architecture for memory security (RDAMS) to detect memory threats (fault and Hardware Trojans attack). The architecture consists of a Security Detection Core (SDC) that controls and enforces the detection procedure as a “security brain”, and a memory wrapper (MEM_wrapper) which interacts with memory to assist the detection. We also design a low latency response mechanism to solve the SoC performance degradation caused by run-time detection. A block-based multi-granularity detection approach is proposed to render the design flexible and reduce the cost in implementation using the FPGA’s dynamic partial reconfigurable (DPR) technology, which enables online detection mode reconfiguration according to the requirements. Experimental results show that RDAMS can correctly detect and identify 10 modeled memory faults and two types of Hardware Trojans (HTs) attacks without leading a great performance degradation to the system.