The Relationship Between Impedance, Programming and Word Recognition in a Large Clinical Dataset of Cochlear Implant Recipients

Cochlear implant programming typically involves measuring electrode impedance, selecting a speech processing strategy and fitting the dynamic range of electrical stimulation. This study retrospectively analyzed a clinical dataset of adult cochlear implant recipients to understand how these variables relate to speech recognition. Data from 425 implanted post-lingually deafened ears with Advanced Bionics devices were analyzed. A linear mixed-effects model was used to infer how impedance, programming and patient factors were associated with monosyllabic word recognition scores measured in quiet. Additional analyses were conducted on subsets of data to examine the role of speech processing strategy on scores, and the time taken for the scores of unilaterally implanted patients to plateau. Variation in basal impedance was negatively associated with word score, suggesting importance in evaluating the profile of impedance. While there were small, negative bivariate correlations between programming level metrics and word scores, these relationships were not clearly supported by the model that accounted for other factors. Age at implantation was negatively associated with word score, and duration of implant experience was positively associated with word score, which could help to inform candidature and guide expectations. Electrode array type was also associated with word score. Word scores measured with traditional continuous interleaved sampling and current steering speech processing strategies were similar. The word scores of unilaterally implanted patients largely plateaued within 6-months of activation. However, there was individual variation which was not related to initially measured impedance and programming levels.

Sensory Percepts Elicited by Chronic Macro-Sieve Electrode Stimulation of the Rat Sciatic Nerve

Objective: Intuitive control of conventional prostheses is hampered by their inability to provide the real-time tactile and proprioceptive feedback of natural sensory pathways. The macro-sieve electrode (MSE) is a candidate interface to amputees’ truncated peripheral nerves for introducing sensory feedback from external sensors to facilitate prosthetic control. Its unique geometry enables selective control of the complete nerve cross-section by current steering. Unlike previously studied interfaces that target intact nerve, the MSE’s implantation requires transection and subsequent regeneration of the target nerve. Therefore, a key determinant of the MSE’s suitability for this task is whether it can elicit sensory percepts at low current levels in the face of altered morphology and caliber distribution inherent to axon regeneration. The present in vivo study describes a combined rat sciatic nerve and behavioral model developed to answer this question.Approach: Rats learned a go/no-go detection task using auditory stimuli and then underwent surgery to implant the MSE in the sciatic nerve. After healing, they were trained with monopolar electrical stimuli with one multi-channel and eight single-channel stimulus configurations. Psychometric curves derived by the method of constant stimuli (MCS) were used to calculate 50% detection thresholds and associated psychometric slopes. Thresholds and slopes were calculated at two time points 3 weeks apart.Main Results: For the multi-channel stimulus configuration, the average current required for stimulus detection was 19.37 μA (3.87 nC) per channel. Single-channel thresholds for leads located near the nerve’s center were, on average, half those of leads located near the periphery (54.92 μA vs. 110.71 μA, or 10.98 nC vs. 22.14 nC). Longitudinally, 3 of 5 leads’ thresholds decreased or remained stable over the 3-week span. The remaining two leads’ thresholds increased by 70–74%, possibly due to scarring or device failure.Significance: This work represents an important first step in establishing the MSE’s viability as a sensory feedback interface. It further lays the groundwork for future experiments that will extend this model to the study of other devices, stimulus parameters, and task paradigms.

Detection of Network Attacks Based on Multiprocessing and Trace Back Methods

The way of thinking of traffic observing for discovery of system assaults is predicated on a “gained information” viewpoint: current methods recognize either the notable assaults which they’re customized to alarm on, or those strange occasions that veer off from a known typical activity profile. These philosophies depend on an expert structure which gives the ideal data, either with respect to “marks” of the striking attacks or as anomaly free traffic datasets, adequately rich to make delegate profiles for commonplace movement traffic. The theory talks about the limitations of current information-based system to recognize organize assaults in an inexorably unpredictable and advancing Web, Described by ever-rising applications and an ever-expanding number of most recent system assaults. In an oppositely inverse viewpoint, we place the weight on the occasion of solo recognition strategies, fit for distinguishing obscure system assaults during a unique situation with none past information, neither on the attributes of the assault nor on the gauge traffic conduct. In view of the perception that an outsized portion of system assaults are contained during a little division of traffic flows, the proposition exhibits an approach to join basic bunching strategies to precisely distinguish and portray malignant flows. to bring up the practicality of such an information autonomous methodology, a solid multi-bunching-based location technique is created and assess its capacity to recognize and portray arrange assaults with none past information, utilizing bundle follows from two genuine operational systems. The methodology is acclimated identify and describe obscure vindictive flows, and spotlights on the identification and portrayal of ordinary and notable assaults, which encourages the translation of results. When contrasted with the predominant DDoS traceback techniques, the proposed system has assortment of favorable circumstances—it is memory no concentrated, proficiently adaptable, vigorous against parcel contamination, and free of assault traffic designs. The consequences of inside and out test and reenactment considers are introduced to exhibit the adequacy and effectiveness of the proposed strategy. It’s an uncommon test to traceback the wellspring of Circulated Disavowal of-Administration (DDoS) assaults inside the Web. In DDoS assaults, aggressors create a lot of solicitations to casualties through undermined PCs (zombies), with the point of keeping ordinary help or debasing from getting the norm of administrations. Because of this fundamental change, the proposed system conquers the acquired downsides of parcel stamping strategies, similar to weakness to bundle contaminations. The execution of the proposed strategy welcomes no changes on current steering programming. Moreover, this work builds up a hypothetical structure for assessing the insurance of IDS against mimicry assaults. It shows an approach to break the wellbeing of 1 distributed IDS with these strategies, and it tentatively affirms the capacity of various assaults by giving a worked model. The Project is intended by using Java 1.6 as face and MS SQL Server 2000 as backside. The IDE used is Net Beans 6.8.