Unreliable Feedback Research Articles

Calibration and Modeling of the Semmes-Weinstein Monofilament for Diabetic Foot Management.

Diabetic foot is a serious complication that poses significant risks for diabetic patients. The resulting reduction in protective sensitivity in the plantar region requires early detection to prevent ulceration and ultimately amputation. The primary method employed for evaluating this sensitivity loss is the 10 gf Semmes-Weinstein monofilament test, commonly used as a first-line procedure. However, the lack of calibration in existing devices often introduces decision errors due to unreliable feedback. In this article, the mechanical behavior of a monofilament was analytically modeled, seeking to promote awareness of the impact of different factors on clinical decisions. Furthermore, a new device for the automation of the metrological evaluation of the monofilament is described. Specific testing methodologies, used for the proposed equipment, are also described, creating a solid base for the establishment of future calibration guidelines. The obtained results showed that the tested monofilaments had a very high error compared to the 10 gf declared by the manufacturers. To improve the precision and reliability of assessing the sensitivity loss, the frequent metrological calibration of the monofilament is crucial. The integration of automated verification, simulation capabilities, and precise measurements shows great promise for diabetic patients, reducing the likelihood of adverse outcomes.

Energy and Delay Efficient Fountain-Coded File Transfer Assisted by Unreliable Feedback

Energy and Delay Efficient Fountain-Coded File Transfer Assisted by Unreliable Feedback

Use of variable online visual feedback to optimize sensorimotor coding and learning of a motor sequence.

The present study characterized the impact of reliable and/or unreliable online visual feedback and their order of presentation on the coding and learning of a motor sequence. Participants practiced a 12-element motor sequence 200 times. During this acquisition phase, two groups received a single type (i.e., either reliable or unreliable) of online visual feedback, two other groups encountered both types of feedback: either reliable first then unreliable, or unreliable first then reliable. Delayed retention tests and intermanual transfer tests (visuospatial and motor) were administered 24 hours later. Results showed that varying the reliability of online visual information during the acquisition phase allowed participants to use different task coding modalities without damaging their long-term sequence learning. Moreover, starting with reliable visual feedback, replaced halfway through with unreliable feedback promoted motor coding, which is seldom observed. This optimization of motor coding opens up interesting perspectives, as it is known to promote better learning of motor sequences.

Effects of feedback reliability on event-related potentials in an arrow flanker task.

The processing of feedback is essential for learning, error detection, and correction. However, the underlying mechanisms of the feedback's characteristics, such as its reliability, valence, and expectations in the processing of error information, are not completely clear. The two degrees of feedback reliability, reliable feedback and unreliable feedback, respectively, were established by manipulating the feedback valence. The time course of event-related potentials (ERP) during the arrow flanker tasks was used to investigate the effects of feedback reliability and responses on brain activity. Three ERP components, the error-related negativity (ERN), feedback-related negativity (FRN), and P3, respectively, were measured. The impacts of feedback reliability and responses on ERN, FRN, and P3 had a different profile. Specifically, ERN and P3 are associated with the responses but not the feedback reliability, while FRN is associated with feedback reliability and feedback expectations but not the responses. The ERN, FRN, and P3 reflect distinct cognitive processes in the processing of error information.

Sincere praise and flattery: reward value and association with the praise-seeking trait.

Sincere praise reliably conveys positive or negative feedback, while flattery always conveys positive but unreliable feedback. These two praise types have not been compared in terms of communication effectiveness and individual preferences using neuroimaging. Through functional magnetic resonance imaging, we measured brain activity when healthy young participants received sincere praise or flattery after performing a visual search task. Higher activation was observed in the right nucleus accumbens during sincere praise than during flattery, and praise reliability correlated with posterior cingulate cortex activity, implying a rewarding effect of sincere praise. In line with this, sincere praise uniquely activated several cortical areas potentially involved in concern regarding others' evaluations. A high praise-seeking tendency was associated with lower activation of the inferior parietal sulcus during sincere praise compared to flattery after poor task performance, potentially reflecting suppression of negative feedback to maintain self-esteem. In summary, the neural dynamics of the rewarding and socio-emotional effects of praise differed.

The Way of the DAO: Toward Decentralizing the Tactile Internet

There has been a growing interest in adapting blockchain technologies to the specific needs of the Internet of Things (IoT) in order to develop a variety of blockchain-based IoT (BIoT) applications such as smart cities and Industry 4.0, where smart contracts play an important role. After briefly reviewing recent progress on BIoT, we explore the symbiosis of blockchain with other key technologies such as artificial intelligence (AI) and robots, while putting our focus on the emerging Tactile Internet for advanced human-to-machine interaction. Our interest is in exploiting the concept of the decentralized autonomous organization (DAO), which executes smart contracts and requires the involvement from humans to perform certain tasks that autonomous AI based software agents and robots themselves cannot do. In our search for synergies between human-agent-robot teamwork (HART) and the complementary strengths of the DAO, AI, and robots, we decentralize the Tactile Internet by leveraging mobile end-user equipment via partially or fully decentralized multi-access edge computing, and crowdsourcing of human expertise to decrease the completion time of physical tasks in the event of unreliable feedback forecasting of teleoperated robots. Finally, we aim at enhancing the human capabilities of unskilled crowd members by using our proposed nudge contract.

Unreliable feedback deteriorates information processing in primary visual cortex

It is well-established that increased sensory uncertainty impairs perceptual decision-making and leads to degraded neural stimulus representations. Recently, we also showed that providing unreliable feedback to choices leads to changes in perceptual decision-making similar to those of increased stimulus noise: A deterioration in objective task performance, a decrease in subjective confidence and a lower reliance on sensory information for perceptual inference. To investigate the neural basis of such feedback-based changes in perceptual decision-making, in the present study, two groups of healthy human participants (n = 15 each) performed a challenging visual orientation discrimination task while undergoing functional magnetic resonance imaging (fMRI). Critically, one group received reliable feedback regarding their task performance in an intervention phase, whereas the other group correspondingly received unreliable feedback - thereby keeping stimulus information constant. The effects of feedback reliability on performance and stimulus representation in the primary visual cortex (V1) were studied by comparing the pre- and post-intervention test phases between the groups. Compared to participants who received reliable feedback, those receiving unreliable feedback showed a decline in task performance that was paralleled by reduced distinctness of fMRI response patterns in V1. These results show that environmental uncertainty can affect perceptual inference at the earliest cortical processing stages.

Novel hybrid brain-computer interface system based on motor imagery and P300.

Motor imagery (MI) is a mental representation of motor behavior and has been widely used in electroencephalogram based brain-computer interfaces (BCIs). Several studies have demonstrated the efficacy of MI-based BCI-feedback training in post-stroke rehabilitation. However, in the earliest stage of the training, calibration data typically contain insufficient discriminability, resulting in unreliable feedback, which may decrease subjects' motivation and even hinder their training. To improve the performance in the early stages of MI training, a novel hybrid BCI paradigm based on MI and P300 is proposed in this study. In this paradigm, subjects are instructed to imagine writing the Chinese character following the flash order of the desired Chinese character displayed on the screen. The event-related desynchronization/synchronization (ERD/ERS) phenomenon is produced with writing based on one's imagination. Simultaneously, the P300 potential is evoked by the flash of each stroke. Moreover, a fusion method of P300 and MI classification is proposed, in which unreliable P300 classifications are corrected by reliable MI classifications. Twelve healthy naïve MI subjects participated in this study. Results demonstrated that the proposed hybrid BCI paradigm yielded significantly better performance than the single-modality BCI paradigm. The recognition accuracy of the fusion method is significantly higher than that of P300 (p < 0.05) and MI (p < 0.01). Moreover, the training data size can be reduced through fusion of these two modalities.

Differential effects of instructed and objective feedback reliability on feedback-related brain activity.

Feedback reliability refers to the probability that the same decision leads to the same positive or negative feedback in the future. Previous research has shown that unreliable feedback is associated with attenuated feedback-related brain activity in ERPs, represented by a reduced fronto-central valence effect (feedback-related negativity or reward positivity) and a reduced feedback-related P3. Here, we asked whether these effects reflect top-down mechanisms or whether they can be explained by implicit feedback-outcome contingency learning. In two experiments, participants performed a trial-and-error learning task while subjective or objective feedback reliability was varied across blocks. In Experiment 1, we manipulated instructed feedback reliability while holding objective feedback reliability constant. Low instructed feedback reliability led to an attenuation of the fronto-central valence effect and the P3. In Experiment 2, we manipulated objective feedback reliability while holding instructed feedback reliability constant. Here, no modulation of feedback-related brain activity was observed. These results suggest that effects of feedback reliability are driven by top-down mechanisms based on explicit knowledge. Specifically, effects on the fronto-central valence effect could indicate a devaluation of unreliable feedback or a bias on the generation or utilization of reward prediction errors.

Electrophysiological measures reveal the role of anterior cingulate cortex in learning from unreliable feedback.

Although a growing number of studies have investigated the neural mechanisms of reinforcement learning, it remains unclear how the brain responds to feedback that is unreliable. A recent theory proposes that the reward positivity (RewP) component of the event-related brain potential (ERP) and frontal midline theta (FMT) power reflect separate feedback-related processing functions of anterior cingulate cortex (ACC). In the present study, the electroencephalogram (EEG) was recorded from participants as they engaged in a time estimation task in which feedback reliability was manipulated across conditions. After each response, they received a cue that indicated that the following feedback stimulus was 100%, 75%, or 50% reliable. The results showed that participants' time estimates adjusted linearly according to the feedback reliability. Moreover, presentation of the cue indicating 100% reliability elicited a larger RewP-like ERP component than the other cues did, and feedback presentation elicited a RewP of approximately equal amplitude for all of the three reliability conditions. By contrast, FMT power elicited by negative feedback decreased linearly from the 100% condition to 75% and 50% condition, and only FMT power predicted behavioral adjustments on the following trials. In addition, an analysis of Beta power and cross-frequency coupling (CFC) of Beta power with FMT phase suggested that Beta-FMT communication modulated motor areas for the purpose of adjusting behavior. We interpreted these findings in terms of the hierarchical reinforcement learning account of ACC, in which the RewP and FMT are proposed to reflect reward processing and control functions of ACC, respectively.

Effects of feedback reliability on feedback-related brain activity: A feedback valuation account.

Adaptive decision making relies on learning from feedback. Because feedback sometimes can be misleading, optimal learning requires that knowledge about the feedback's reliability be utilized to adjust feedback processing. Although previous research has shown that feedback reliability indeed influences feedback processing, the underlying mechanisms through which this is accomplished remain unclear. Here we propose that feedback processing is adjusted by the adaptive, top-down valuation of feedback. We assume that unreliable feedback is devalued relative to reliable feedback, thus reducing the reward prediction errors that underlie feedback-related brain activity and learning. A crucial prediction of this account is that the effects of feedback reliability are susceptible to contrast effects. That is, the effects of feedback reliability should be enhanced when both reliable and unreliable feedback are experienced within the same context, as compared to when only one level of feedback reliability is experienced. To evaluate this prediction, we measured the event-related potentials elicited by feedback in two experiments in which feedback reliability was varied either within or between blocks. We found that the fronto-central valence effect, a correlate of reward prediction errors during reinforcement learning, was reduced for unreliable feedback. But this result was obtained only when feedback reliability was varied within blocks, thus indicating a contrast effect. This suggests that the adaptive valuation of feedback is one mechanism underlying the effects of feedback reliability on feedback processing.

FER Estimation in a Memoryless BSC With Variable Frame Length and Unreliable ACK/NAK Feedback

We consider the problem of estimating the frame error rate (FER) of a given memoryless binary symmetric channel by observing the success or failure of transmitted packets. Whereas FER estimation is relatively straightforward if all observations correspond to packets with equal length, the problem becomes considerably more complex when this is not the case. We develop FER estimators when transmissions of different lengths are observed, together with the Cramer–Rao lower bound (CRLB). Although the main focus is on maximum likelihood (ML) estimation, we also obtain low-complexity schemes performing close to optimal in some scenarios. In a second stage, we consider the case in which FER estimation is performed at a node different from the receiver, and incorporate the impairment of unreliable observations by considering noisy ACK/NAK feedback links. The impact of unreliable feedback is analyzed by means of the corresponding CRLB. In this setting, the ML estimator is obtained by applying the expectation–maximization algorithm to jointly estimate the error probabilities of the data and feedback links. Simulation results illustrate the benefits of the proposed estimators.

A repairable &lt;i&gt;M&lt;/i&gt;&lt;SUP align="right"&gt;[&lt;i&gt;X&lt;/i&gt;]&lt;/SUP&gt;/&lt;i&gt;G&lt;SUB align="right"&gt;k&lt;/i&gt;/1 feedback retrial &lt;i&gt;G&lt;/i&gt;-queue, balking and reneging, search of customers with vacation

This paper deals with the steady state analysis of unreliable batch arrival feedback retrial queue with k stages of service and Bernoulli vacation policy, where the busy server is subjected to breakdown due to the arrival of negative customers. After completion of the ith, (i = 1, 2, ..., k) stage of service, the customer may have the option to choose (i + 1)th stage with probability θi, with probability pi may join into orbit as feedback customer or may leave the system with probability 1 – θi – pi = qi, if the service is successful. The server takes Bernoulli vacation after the service completion. Arriving positive customers may balk (or renege) the system at particular times. After completion of the service, vacation or repair, the server searches for the customer in the orbit or remains idle. The system is solved by using the supplementary variable method and numerical illustrations are discussed.

Gaussian Interference Channel With Intermittent Feedback

We investigate how to exploit intermittent feedback for interference management by studying the two-user Gaussian interference channel (IC). We approximately characterize (within a universal constant) the capacity region for the Gaussian IC with intermittent feedback. We exactly characterize the capacity region of the linear deterministic version of the problem, which gives us insight into the Gaussian problem. We find that the characterization only depends on the forward channel parameters and the marginal probability distribution of each feedback link. The result shows that passive and unreliable feedback can be harnessed to provide multiplicative capacity gain in Gaussian ICs. We find that when the feedback links are active with sufficiently large probabilities, the perfect feedback sum-capacity is achieved to within a constant gap. In contrast to other schemes developed for IC with feedback, our achievable scheme makes use of quantize-map-and-forward to relay the information obtained through feedback, performs forward decoding, and does not use structured codes. We also develop new outer bounds enabling us to obtain the (approximate) characterization of the capacity region.

Reachback WSN Connectivity: Non-Coherent Zero-Feedback Distributed Beamforming or TDMA Energy Harvesting?

This work is motivated by the reachback connectivity scenario in resource-constrained wireless sensor networks (WSNs): a single terminal at maximum power cannot establish a reliable communication link with the intended destination. Thus, neighboring distributed transmitters should contribute their radios and transmission power, in order to achieve reliable transmission of a common message. This work is particularly interested in low-SNR scenarios with unreliable feedback channels, no channel state information (CSI), and commodity radios, where carrier phase/frequency synchronization is not possible. Concrete non-coherent maximum likelihood and energy detection receivers are developed for zero-feedback distributed beamforming. The proposed receivers are compared with non-coherent energy harvesting reception, based on simple time-division multiple access. It is shown that the proposed zero-feedback distributed beamforming receivers overcome connectivity adversities at the low-SNR regime. This is achieved by exploiting signals' alignment of M distributed transmitters (i.e., beamforming), even with commodity radios, at the expense of network (total) power consumption. Application scenarios include resource-constrained WSNs or emergency radio situations.

Can online buddies and bandwagon cues enhance user participation in online health communities?

Individuals are more likely to obtain information and support from online health communities than offer help to other users (Fox & Jones, 2009; Preece, Nonnecke, & Andrews, 2004). The current study attempts to resolve this problem of under-contribution by proposing two theory-based persuasive strategies—a specific request in the form of an online buddy and collective community feedback in the form of bandwagon cues. A 2 (online buddy: absence vs. presence) by 2 (bandwagon cues: weak vs. strong) between-participants experiment tested the effects of these strategies on psychological outcomes, including perceived responsibility, social presence, sense of community, and perceived helpfulness, as well as their posting attitudes, posting intentions, and website attitudes, across two sessions. Contrary to expectations, we found that the assignment of online buddies in a health community forum leads to negative psychological and behavioral consequences, especially in the absence of strong community feedback. Furthermore, the online buddy feature interacts with bandwagon cues to activate different cognitive processes, leading to differential interpretation of the meanings of those bandwagon cues—either as compliments (in the presence of online buddy) or as unreliable feedback (in the absence of online buddy). Theoretical and practical implications are discussed.

On the Design of Hybrid Automatic Repeat Request Schemes with Unreliable Feedback

\gls{HARQ} schemes are employed in mobile communication systems to reduce the residual Frame Error Rate (FER) after channel decoding. If decoding fails, the receiver requests the transmission of additional redundancy about these frames to improve the decoding success. Signaling is carried out over a feedback link from the receiver back to the transmitter. However, errors on the feedback link severely influence the behavior of the HARQ system and may degrade the overall system performance. In this contribution, the impact of HARQ signaling errors on the FER, the average number of HARQ transmissions per frame, and the system throughput is investigated. We derive analytical expressions for all performance measures based on FER simulations of the HARQ system with reliable feedback. The theoretical results are verified by the example of the LTE physical layer, however, they are also applicable to other communication systems. Moreover, target requirements for the maximum tolerable feedback error probabilities are derived which are used to develop design guidelines for HARQ feedback transceivers.

Throughput maximization over slowly fading channels using quantized and erroneous feedback

We design a conceptual transmission scheme that adjusts rate and power of data codewords to send them over a slowly fading channel, when quantized and possibly erroneous channel state information (CSI) is available at the transmitter. The goal is to maximize the data throughput or the expected data rate using a multi-layer superposition coding technique and temporal power control at the transmitter. The main challenge here is to design a CSI quantizer structure for a noisy feedback link. This structure resembles conventional joint source and channel coding schemes, however, with a newly introduced quasi-gray bit-mapping. Our results show that with proper CSI quantizer design, even erroneous feedback can provide performance gains. Also, with an unreliable feedback link, superposition coding provides significant gains when feedback channel is poorly conditioned and channel uncertainty at the transmitter is severe, whereas power control is more effective with more reliable feedback.

Short Bowel Patients Treated for Two Years with Glucagon-Like Peptide 2 (GLP-2): Compliance, Safety, and Effects on Quality of Life

Background and aims. Glucagon-like peptide 2 (GLP-2) has been shown to improve intestinal absorption in short bowel syndrome (SBS) patients in a short-term study. This study describes safety, compliance, and changes in quality of life in 11 SBS patients at baseline, week 13, 26, and 52 during two years of subcutaneous GLP-2 treatment, 400 microgram TID, intermitted by an 8-week washout period. Methods. Safety and compliance was evaluated during the admissions. The Sickness Impact Profile (SIP), Short Form 36 (SF 36), and Inflammatory Bowel Disease Questionnaire (IBDQ) evaluated quality of life. Results. The predominant adverse event was transient abdominal discomfort in 5 of 11 patients, but in 2, both suffering from Crohns disease, it progressed to abdominal pain and led to discontinuation of GLP-2 treatment. One had a fibrostenotic lesion electively resected at the jejuno-ascendo-anastomosis. The investigator excluded a patient due to unreliable feedback. Stoma nipple enlargement was seen in all 9 jejunostomy patients. Reported GLP-2 compliance was excellent (>93%). GLP-2 improved the overall quality of life VAS-score (4.1 ± 2.8 cm versus 6.0 ± 2.4 cm, P < .01), the overall SIP score (10.3 ± 8.9% versus 6.2 ± 9.5%, P < .001), the mental component of the SF-36 (45 ± 13% versus 53 ± 11%, P < .05), and the overall IBDQ score (5.1 ± 0.9 versus 5.4 ± 0.9, P < .007) in the 8 patients completing the study. Conclusions. Long-term treatment with GLP-2 is feasible in SBS patients, although caution must be exercised in patients with a history of abdominal pain. Although conclusions cannot be made in a noncontrolled trial, the high reported compliance might reflect a high treatment satisfaction, where the clinical benefits of GLP-2 may outweigh the discomforts of injections.

Optimal power control in MIMO systems with quantized feedback - [transactions papers

We treat the problem of outage minimization via power control in MIMO systems with quantized feedback. We formulate the optimal quantized power control design for a general MIMO system and provide the numerical procedure for finding the optimal solution. Our results not only extend but also show the deficiency of the existing quantized power control schemes for MISO systems. We further propose a design based on the pre-evaluation of the packet error rate performance of practical MIMO systems employing short-length LDPC codes and QAM modulations and with possibly unreliable feedback links. It is demonstrated that with only a few bits of feedback, the resulting quantized power control strategy achieves considerable gain over a system without power control.