This paper investigates the positioning of the pilot symbols, as well as the power distribution between the pilot and the communication symbols for the orthogonal time frequency space (OTFS) modulation scheme. We analyze the pilot placements that minimize the mean squared error (MSE) in estimating the channel taps. This allows us to identify two new pilot allocations for OTFS that save approximately 50% of the pilot overhead compared to existing allocations. In addition, we optimize the average channel capacity by adjusting the power distribution. We show that this leads to a significant increase in average capacity. The results provide valuable guidance for designing the OTFS parameters to achieve maximum capacity. Numerical simulations are performed to validate the findings.

Background: Short atrial fibrillation cycle lengths (AFCLs) and regular activation patterns are associated with drivers of atrial fibrillation, although the relation with underlying patterns of activation is incompletely understood. Previous studies used automated assessment of electrograms to determine fast and regular fibrillatory rates. Objective: We investigated the relation among AFCL, temporal variation in AFCL, and the occurrence of driver-like patterns of activation using high-density local activation time mapping. Methods: High-density epicardial mapping of the right atrium and left atrial ventricular groove including Bachmann's bundle was performed in 71 patients admitted for elective cardiac surgery. Recording sites with the shortest median AFCL or the smallest standard deviation of AFCL were identified. Patterns of activation included focal or rotational activation, smooth propagation, propagation with conduction block (CB), collision, and remnant activity. Results: There was a higher number of fibrillation waves with CB (81% [interquartile range (IQR) 76%–85%] vs 74% [68%–76%]; P < .001) and fractionated potentials (22% [12%–37%] vs 12% [9%–15%]; P < .001) at shortest median AFCL than at other recording sites. Smallest standard deviation sites harbored more smoothly propagating waves (33% [24%–54%] vs 17% [11%–25%]; P < .001) and a higher proportion of single potentials (76% [60%–89%] vs 59% [54%–65%]; P < .001). Both highly regular and fastest reactivated sites did not correspond to the origin of (repetitive) focal fibrillation waves. Conclusion: During extensive mapping, the fastest or most regularly activated areas are characterized by CB and smoothly propagating fibrillation waves instead of repetitive occurrence of focal or rotational activation patterns. This study rejects the concept of detecting drivers by identifying the fastest or most regularly activated recording sites.

The pursuit of sensitive and dependable biomarkers capable of capturing the neural processes associated with cognition is a prominent area of interest. Event-related potentials (ERPs) hold significant promise for assessing cognitive dysfunction in various neurological disorders. However, existing data analysis techniques often underutilize the available data and may benefit from potential enhancements. In this paper, we investigate biomarker extraction methods based on two ERP experiments. First, we derive average ERPs from the electroencephalography (EEG) recorded during each experiment and store them in third-order tensors with subjects, channels and time samples along the three modes. Then, we extract biomarkers from these datasets via tensor decompositions. We compare single tensor decompositions and joint tensor decompositions that fuse the data from the individual tensors. In a simulated ERP experiment we compare the benefits and limitations of different tensor-based data fusion methods. Finally, we investigate their performance on a real dataset obtained from schizophrenia patients.

The main focus of this paper is an active sensing application that involves selecting transmit and receive sensors to optimize the Cramér-Rao bound (CRB) on target parameters. Although the CRB is non-convex in the transmit and receive selection, we demonstrate that it is convex in the virtual array weight vector, which describes the multiplicity of the virtual array elements. Based on this finding, we propose a novel algorithm that optimizes the virtual array weight vector first and then finds a matching transceiver array. This greatly enhances the efficiency of the transmit and receive sensor selection problem.

Sound zone algorithms control the inputs to a loudspeaker array such that spatially distinct zones, each with separate audio content, are created. This work proposes a sound zone approach which includes a model of human auditory perception in the optimization problem designing the loudspeaker control filters. The control filters are therefore optimized directly for human experience, rather than by proxy through sound pressure, as is done in typical approaches. The proposed optimization problem features a perceptually weighted constraint on the bright zone reproduction error, which allows the user of the algorithm to specify the desired bright zone quality. The proposed method achieves 2 to 4 dB of additional acoustic contrast and is expected to yield less distracting dark-zone interference for the same perceived quality when compared to a traditional approach.

Objective: The severity of atrial fibrillation (AF) can be assessed from intra-operative epicardial measurements (high-resolution electrograms), using metrics such as conduction block (CB) and continuous conduction delay and block (cCDCB). These features capture differences in conduction velocity and wavefront propagation, but ignore complementary properties such as the morphology of the action potentials. In this work, we focus on such complementary properties, and derive features to detect variations in the atrial potential waveforms. Methods: We show that the spatial variation of atrial potential morphology during a single beat may be described by changes in the singular values of the epicardial measurement matrix. The method is non-parametric and requires little preprocessing. A corresponding singular value map points at areas subject to fractionation and block. Further, we developed an experiment where we simultaneously measure electrograms (EGMs) and a multi-lead ECG. Results: The captured data showed that the normalized singular values of the heartbeats during AF are higher than during SR, and that this difference is more pronounced for the (non-invasive) ECG data than for the EGM data, if the electrodes are positioned at favorable locations. Conclusion: Overall, the singular value-based features are a useful indicator to detect and evaluate AF. Significance: The proposed method might be beneficial for identifying electropathological regions in the tissue without estimating the local activation time.

Hearing impairment is a prevalent problem with daily challenges like impaired speech intelligibility and sound localisation. One of the shortcomings of spatial filtering in hearing aids is that speech intelligibility is often not optimised directly, meaning that different auditory processes contributing to intelligibility are often not considered. One example is the perceptual phenomenon known as spatial release from masking (SRM). This paper develops a signal model that explicitly considers SRM in the beamforming design, achieved by transforming the binaural intelligibility prediction model (BSIM) into a signal processing framework. The resulting extended signal model is used to analyse the performance of reference beamformers and design a novel beamformer that more closely considers how the auditory system perceives binaural sound. It can be shown that the binaural minimum variance distortionless response (BMVDR) beamformer is also an optimal solution for the extended, perceived model, suggesting that SRM does not play a significant role in intelligibility enhancement after optimal beamforming. However, the optimal beamformer is no longer unique in the extended signal model. The additional secondary degrees of freedom can be used to preserve binaural cues of interfering sources while still achieving the same perceived performance of the BMVDR beamformer, though with a possible high sensitivity to intelligibility model mismatch errors.

Background: Dominant frequencies (DFs) or complex fractionated atrial electrograms (CFAEs), indicative of focal sources or rotational activation, are used to identify target sites for atrial fibrillation (AF) ablation in clinical studies, although the relationship among DF, CFAE, and activation patterns remains unclear. Objectives: This study sought to investigate the relationship between patterns of activation underlying DF and CFAE sites during AF. Methods: Epicardial high-resolution mapping of the right and left atrium including Bachmann's bundle was performed in 71 participants. We identified the highest dominant frequency (DF _max) and highest degree of CFAE (CFAE _max) with the use of existing clinical criteria and classified patterns of activation as focal or rotational activation and smooth propagation, conduction block (CB), collision and remnant activity, and fibrillation potentials as single, double, or fractionated potentials containing, respectively, 1, 2, or 3 or more negative deflections. Relationships among activation patterns, DF _max, and potential types were investigated. Results: DF _max were primarily located at the left atrioventricular groove and did not harbor focal activation (proportion focal waves: 0% [IQR: 0%-2%]). Compared with non-DF _max sites, DF _max were characterized by more frequent smooth propagation (22% [IQR: 7%-48%] vs 17% [IQR: 11%-24%]; P = 0.001), less frequent conduction block (69% [IQR: 51%-81%] vs 74% [IQR: 69%-78%]; P = 0.006), a higher proportion of single potentials (72% [IQR: 55%-84%] vs 6%1 [IQR: 55%-65%]; P = 0.003), and a lower proportion of fractionated potentials (4% [IQR: 1%-11%] vs 12% [IQR: 9%-15%]; P = 0.004). CFAE _max were mainly found at the pulmonary veins area, and only 1% [IQR: 0%-2%] of all CFAE _max contained focal activation. Compared with non-CFAE _max sites, CFAE _max sites were characterized by less frequent smooth propagation (1% [IQR: 0%-1%] vs 17% [IQR: 12%-24%]; P < 0.001) and more frequent remnant activity (20% [IQR: 12%-29%] vs 8% [IQR: 5%-10%]; P < 0.001), and harbored predominantly fractionated potentials (52% [IQR: 43%-66%] vs 12% [IQR: 9%-14%]; P < 0.001). Conclusions: Focal or rotational patterns of activation were not consistently detected at DF _max domains and CFAE _max sites. These findings do not support the concept of targeting DF _max or CFAE _max according to existing criteria for AF ablation.

Acoustic-scene-related parameters such as relative transfer functions (RTFs) and power spectral densities (PSDs) of the target source, late reverberation and ambient noise are essential for microphone array signal processing and are challenging to estimate. Existing methods typically only estimate a subset of the parameters by assuming the other parameters are known. This can lead to unmatched scenarios and reduced estimation performance on the parameters of interest. Moreover, many methods process time frames independently, despite they share common information such as the same RTF. In this work, we consider a noisy scenario by modelling the noise component as a spatially homogeneous sound field with a time-invariant spatial coherence matrix and time-varying PSD. We first modify an existing alternating least squares (ALS) method to obtain more accurate estimates using a single time frame. Then, we extend the method to use multiple time frames that share the same RTF. Furthermore, we propose more robust constraints on the PSDs to avoid large estimation errors. We compare our proposed methods to the state-of-the-art simultaneously confirmatory factor analysis (SCFA) method, a joint maximum likelihood estimation (JMLE) method and an existing ALS-based method. The experimental results in terms of estimation accuracy, noise reduction performance, predicted speech quality, and predicted speech intelligibility demonstrate that our proposed methods achieve similar performance compared to the state-of-the-art SCFA method, which outperforms the existing ALS method in all scenarios and outperforms the JMLE method particularly in low SNR scenarios. Moreover, our proposed methods have significantly lower computational complexity than SCFA.

Moving-coil electrodynamic loudspeakers and dynamic microphones use the same linear actuator technology at the core of their operation. Utilising this similarity, loudspeakers have a possible use as recording devices in cases where using dedicated microphones is not feasible. Such a use case exists in public address and voice alarm systems. This paper evaluates the feasibility of using the loudspeakers already in place in these systems as recording devices to provide information back to the system. A system using a single loudspeaker as both a playback and recording device simultaneously is analysed, modelled and simulated. The results show that using a current measuring set-up with an analogue-to-digital converter capable of detecting a range of roughly 120 dB, a speech signal incident at 46 dBSPL in a cone of 150° from a loudspeaker can be successfully estimated in an office room with an announcement playing at 88 dBSPL and background interference present at the same time. As the estimated signal is unknown to the system, the solution generalises to other signal types as well.