Functional near-infrared spectroscopy (fNIRS) is a brain imaging technique used to estimate neuronal activity by measuring blood oxygenation. In this paper, we develop and evaluate an extensive set of fNIRS features for workload estimation, combining them with respiration and heartbeat signals. Our subject- and session-independent workload estimator is validated in a virtual flight simulator, where workload is objectively assessed based on task performance. We experiment with various regression models and feature ablations, identifying the most effective fNIRS features. The best fNIRS-based model achieves a correlation of 0.3188 with objective workload labels, improving to 0.3268 when incorporating breathing signals. This study demonstrates the value of our novel fNIRS feature set for workload estimation.

People enjoy listening to music as part of their life. This makes music an excellent choice for designing a user-friendly brain-computer interface (BCI) for long-term use. We propose a novel BCI system using music stimuli that relies on brain signals collected via Smartfones, an EEG recording device integrated into a pair of headphones. In a user study of the proposed system, participants were asked to pay attention to one of three musical instruments playing simultaneously from separate spatial directions. We used a stimulus reconstruction method to decode attention from EEG signals. Results show that the proposed system can achieve good decoding accuracy (>70%) while providing superior user-friendliness compared to a traditional EEG setup.

The generation of high quality true random numbers is essential in security applications. For secure communication, we also require high quality true random number generators (TRNGs) in embedded and IoT devices. This paper provides insights into modern TRNG design principles and their evaluation, based on standard's requirements and design experience. We illustrate our approach with a case study of a recently proposed delay chain based TRNG.

When using a set of generic head-related transfer functions (HRTFs) for spatial sound rendering, personalisation can be considered to minimise localisation errors. This typically involves tuning the characteristics of the HRTFs or a parametric model according to the listener's anthropometry. However, measuring anthropometric features directly remains a challenge in practical applications, and the mapping between anthropometric and acoustic features is an open research problem. Here we propose matching a face template to a listener's head scan or depth image to extract anthropometric information. The deformation of the template is used to personalise the interaural time differences (ITDs) of a generic HRTF set. The proposed method is shown to outperform reference methods when used with high-resolution 3-D scans. Experiments with single-frame depth images indicate that the method is applicable to lower resolution or partial scans which are quicker and easier to obtain than full 3-D scans. These results suggest that the proposed method may be a viable option for ITD personalisation in practical applications.

In the public switched telephone network (PSTN), 911 (emergency) services are handled by a dedicated, point-to-point analog network infrastructure. In contrast, 911 in IP telephony is constrained by IP's flat addressing scheme and dynamic IP address assignment, best-effort service model and inherent dynamicity in network topology connectivity. To serve crucial E911 needs of accurate assistance dispatch with callback facility in IP telephony, the existing model from analog telephony is not applicable. We investigate ways of resolving location information of an IP telephony 911 caller and propose a novel approach to convey geographic location information parameters of connected hosts by extending the DHCP protocol. The case scenario of voice over IP (VoIP) in local area networks (LAN) is used as the basis for our approach and specifically, University of Missouri Kansas City's (UMKC) VoIP network has been considered for possible deployment of this approach.

Stratification of compliant control requires that we know whether, for any contact configurations under the same contact formation, them exists a CF-compliant motion connecting them. This motivates the question of whether a given CF has disjoint regions of configurations. It is the geometric features of the contacting objects that may cause disjoint regions of contact configurations under the same topological contact formation. In this paper we further analyze such geometric features between two contacting polygons. This paper presents a vocabulary and a hierarchical method that we have found useful in analyzing CFs to determine the connectedness of their regions of CF-compliant configurations. The hierarchical analysis method simplifies the detection of disjoint regions in a CF through a series of tests of increasing complexity on the geometric relations between the two objects in contact under the CF.

An object with certain geometric features, when it is in contact with another object, may cause disjoint regions of contact configurations under the same topological contact formation (CF). In this paper we analyze such geometric features and introduce the concept of limiting channel element of CF-compliance (LIMITEL). We further develop a simple algorithm for finding potential LIMITELs of an arbitrary polygon that may cause disjoint regions of contact configurations, given a second, contacting polygon. The algorithm is purely geometric and assumes exact knowledge of the geometries of the objects.

A full tactile sensing suite for the finger segments and palm of the Utah/MIT dextrous hand is presented. The rubber-based sensors employ capacitance sensing and floating electrodes in the top layer, and contain local electronics for excitation, filtering, analog-to-digital conversion, and serial communication. Experimental results on static, dynamic, and spatial properties are presented. Use of the tactile sensor in contact force control is demonstrated.