Time-frequency analysis of rhythmic masticatory muscle activity

The aim of this study was to develop and validate under laboratory conditions an algorithm for a time-frequency analysis of rhythmic masticatory muscle activity (RMMA). The algorithm baseband demodulated the electromyographic (EMG) signal to provide a frequency versus time representation. Using appropriate thresholds for frequency and power parameters, it was possible to automatically assess the features of RMMA without examiner interaction. The algorithm was first tested using synthetic EMG signals and then using real EMG signals obtained from the masticatory muscles of 11 human subjects who underwent well-defined rhythmic, static, and possible confounding oral tasks. The accuracy of detection was quantified by receiver operating characteristics (ROC) curves. Sensitivity and specificity values were >/=90% and >/=96%, respectively. The areas under the ROC curves were >/=95% (standard error +/-0.1%). The proposed approach represents a promising tool to effectively investigate rhythmical contractions of the masticatory muscles. Muscle Nerve, 2009

FROM 3D SURVEYING DATA TO BIM TO BEM: THE INCUBE DATASET

In recent years, the improvement of sensors and methodologies for 3D reality-based surveying has exponentially enhanced the possibility of creating digital replicas of the real world. LiDAR technologies and photogrammetry are currently standard approaches for collecting 3D geometric information of indoor and outdoor environments at different scales. This information can potentially be part of a broader processing workflow that, starting from 3D surveyed data and through Building Information Models (BIM) generation, leads to more complex analyses of buildings’ features and behavior (Figure 1). However, creating BIM models, especially of historic and heritage assets (HBIM), is still resource-intensive and time-consuming due to the manual efforts required for data creation and enrichment. Improve 3D data processing, interoperability, and the automation of the BIM generation process are some of the trending research topics, and benchmark datasets are extremely helpful in evaluating newly developed algorithms and methodologies for these scopes. This paper introduces the InCUBE dataset, resulting from the activities of the recently funded EU InCUBE project, focused on unlocking the EU building renovation through integrated strategies and processes for efficient built-environment management (including the use of innovative renewable energy technologies and digitalization). The set of data collects raw and processed data produced for the Italian demo site in the Santa Chiara district of Trento (Italy). The diversity of the shared data enables multiple possible uses, investigations and developments, and some of them are presented in this contribution

Nerf for heritage 3d reconstruction

Conventional or learning-based 3D reconstruction methods from images have clearly shown their potential for 3D heritage documentation. Nevertheless, Neural Radiance Field (NeRF) approaches are recently revolutionising the way a scene can be rendered or reconstructed in 3D from a set of oriented images. Therefore the paper wants to review some of the last NeRF methods applied to various cultural heritage datasets collected with smartphone videos, touristic approaches or reflex cameras. Firstly several NeRF methods are evaluated. It turned out that Instant-NGP and Nerfacto methods achieved the best outcomes, outperforming all other methods significantly. Successively qualitative and quantitative analyses are performed on various datasets, revealing the good performances of NeRF methods, in particular for areas with uniform texture or shining surfaces, as well as for small datasets of lost artefacts. This is for sure opening new frontiers for 3D documentation, visualization and communication purposes of digital heritage

NERFBK: A HOLISTIC DATASET FOR BENCHMARKING NERF-BASED 3D RECONSTRUCTION

Neural Radiance Field methods are innovative solutions to derive 3D data from a set of oriented images. This paper introduces new real and synthetic image datasets - called NeRFBK - specifically designed for testing and comparing NeRF-based 3D reconstruction algorithms. More and more reconstruction algorithms and techniques are available nowadays, raising the need to evaluate and compare the quality of derived 3D products currently used in various domains and applications. However, gathering diverse data with precise ground truth is challenging and may not encompass all relevant applications. The NeRFBK dataset addresses this issue by providing multi-scale, indoor and outdoor datasets with high-resolution images and videos and camera parameters for testing and comparing NeRF-based algorithms. This paper presents the design and creation of the NeRFBK set of data, various examples and application scenarios, and highlights its potential for advancing the field of 3D reconstruction

NERFBK: A HOLISTIC DATASET FOR BENCHMARKING NERF-BASED 3D RECONSTRUCTION

Neural Radiance Field methods are innovative solutions to derive 3D data from a set of oriented images. This paper introduces new real and synthetic image datasets - called NeRFBK - specifically designed for testing and comparing NeRF-based 3D reconstruction algorithms. More and more reconstruction algorithms and techniques are available nowadays, raising the need to evaluate and compare the quality of derived 3D products currently used in various domains and applications. However, gathering diverse data with precise ground truth is challenging and may not encompass all relevant applications. The NeRFBK dataset addresses this issue by providing multi-scale, indoor and outdoor datasets with high-resolution images and videos and camera parameters for testing and comparing NeRF-based algorithms. This paper presents the design and creation of the NeRFBK set of data, various examples and application scenarios, and highlights its potential for advancing the field of 3D reconstruction

Effect of weather on temporal pain patterns in patients with temporomandibular disorders and migraine

Patients with masticatory muscle pain and migraine typically report that the intensity of pain fluctuates over time and is affected by weather changes. Weather variables, such as ambient temperature and humidity, may vary significantly depending on whether the individual is outdoor or indoor. It is, therefore, important to assess these variables at the individual level using portable monitors, during everyday life. This study aimed to determine and compare the temporal patterns of pain in individuals affected with facial and head pain and to investigate its relation with weather changes. Eleven patients (27·3 ± 7·4 years) with chronic masticatory muscle pain (MP) and twenty (33·1 ± 8·7 years) with migraine headache (MH) were asked to report their current pain level on a visual analogue scale (VAS) every hour over fourteen consecutive days. The VAS scores were collected using portable data-loggers, which were also used to record temperature, atmospheric pressure and relative humidity. VAS scores varied markedly over time in both groups. Pain VAS scores fluctuate less in the MP group than in the MH group, but their mean, minimum and maximum values were higher than those of migraine patients (all P < 0·05). Pain scores <2 cm were more common in the MH than in the MP group (P < 0·001). Perceived intensity of pain was negatively associated with atmospheric pressure in the MP group and positively associated with temperature and atmospheric in the MH group. Our results reveal that patients with masticatory muscle pain and patients with migraine present typical temporal pain patterns that are influenced in a different way by weather changes

Efficient Low-Frequency SSVEP Detection with Wearable EEG Using Normalized Canonical Correlation Analysis

Recent studies show that the integrity of core perceptual and cognitive functions may be tested in a short time with Steady-State Visual Evoked Potentials (SSVEP) with low stimulation frequencies, between 1 and 10 Hz. Wearable EEG systems provide unique opportunities to test these brain functions on diverse populations in out-of-the-lab conditions. However, they also pose significant challenges as the number of EEG channels is typically limited, and the recording conditions might induce high noise levels, particularly for low frequencies. Here we tested the performance of Normalized Canonical Correlation Analysis (NCCA), a frequency-normalized version of CCA, to quantify SSVEP from wearable EEG data with stimulation frequencies ranging from 1 to 10 Hz. We validated NCCA on data collected with an 8-channel wearable wireless EEG system based on BioWolf, a compact, ultra-light, ultra-low-power recording platform. The results show that NCCA correctly and rapidly detects SSVEP at the stimulation frequency within a few cycles of stimulation, even at the lowest frequency (4 s recordings are sufficient for a stimulation frequency of 1 Hz), outperforming a state-of-the-art normalized power spectral measure. Importantly, no preliminary artifact correction or channel selection was required. Potential applications of these results to research and clinical studies are discussed

Methods, data and tools for facilitating a 3D cultural heritage space

In recent years, the cultural heritage (CH) sector has experienced a rapid evolution due to the introduction of increasingly powerful digital technologies and ICT (Information and Communication Technologies) solutions. As for many other domains, digital data, Artificial Intelligence (AI), and Extended Reality (XR) are opening up extraordinary opportunities for expanding heritage knowledge capabilities while boosting the research on innovative solutions for its valorisation and preservation. Being aware of the fundamental and strategic role of CH in the history and identity of the European countries, the European Commission has assumed a central role in fuelling the policy debate and putting together stakeholders to take a step forward in CH digitization and use, primarily through initiatives, programs, and recommendations. Within this framework, the ongoing European 5DCulture project (https://www.5dculture.eu/) has been funded to enrich the offer of 3D CH digital assets in the common European Data Space for Cultural Heritage by creating high-quality 3D contents and to foster their re-use in several sectors, from tourism to education. Through 8 re-use scenarios around historic buildings and cityscapes, archaeology, and fashion, the project aims to deliver a set of digital tools and increase the capacity of CH institutions to more effectively re-use their 3D digital assets

A regional assessment of cumulative impact mapping on Mediterranean coralligenous Outcrops

In the last decade, the 'Cumulative Pressure and Impact Assessment' (CPIA) approach emerged as a tool to map expected impacts on marine ecosystems. However, CPIA assumes a linear response of ecosystems to increasing level of cumulative pressure weighting sensitivity to different anthropogenic pressures through expert judgement. We applied CPIA to Mediterranean coralligenous outcrops over 1000 km of the Italian coastline. Extensive field surveys were conducted to assess the actual condition of coralligenous assemblages at varying levels of human pressure. As pressure increased, a clear shift from bioconstructors to turf-dominated assemblages was found. The linear model originally assumed for CPIA did not fit the actual relationship between expected cumulative impact versus assemblage degradation. A log-log model, instead, best fitted the data and predicted a different map of cumulative impact in the study area able to appreciate the whole range of impact scenarios. Hence, the relative importance of different drivers in explaining the observed pattern of degradation was not aligned with weights from the expert opinion. Such findings stress the need for more incisive efforts to collect empirical evidence on ecosystem-specific responses to human pressure in order to refine CPIA predictions