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Selected Papers from the 2023 IEEE International Conference on Metrology for eXtended Reality, Artificial Intelligence and Neural Engineering (IEEE MetroXRAINE 2023)

A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Intelligent Sensors".

Deadline for manuscript submissions: closed (5 June 2024) | Viewed by 8591

Special Issue Editors

Prof. Dr. Egidio De Benedetto

E-Mail Website
Guest Editor
Department of Information Technology and Electrical Engineering, University of Naples Federico II, 80138 Naples, Italy
Interests: instrumentation; signal treatment and uncertainty estimation in biosensors; metrological characterization of biosensors; metrology; sensors; biomedical research; IoT; wearable devices
Special Issues, Collections and Topics in MDPI journals
Dr. Antonio Esposito

E-Mail Website
Guest Editor
Department of Information Technology and Electrical Engineering, University of Naples Federico II, 80125 Naples, Italy
Interests: measurement theory; electronic measurements; electronic instrumentation devices; wearable brain computer interface
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

The 2023 IEEE International Conference on Metrology for eXtended Reality, Artificial Intelligence and Neural Engineering—IEEE MetroXRAINE 2023 will be held on OCTOBER 25-27, 2023, in Milano, Italy (https://metroxraine.org/). This will be an international event, mainly aimed at creating a synergy between experts in eXtended reality, the brain–computer interface, and artificial intelligence, with special attention to measurement. Authors of papers related to sensors presented at the conference are invited to submit extended versions of their work to this Special Issue for publication.

Areas of interest include, but are not limited to:

  • Instrumental solutions and measurement principles for enhancing the accuracy and robustness of XR-BCI systems.
  • Display technologies and human vision.
  • Wearable sensors for neuroimaging.
  • User experience, perception and interactions in XR and BCI.
  • Multisensory experiences and improved immersion.
  • Psychophysical condition monitoring.
  • Advanced machine learning techniques for XR-BCI.
  • Deep learning-based classification.
  • VR-supported mindfulness-based on EEG signals.
  • Immersive user experience with XR-BCI.
  • Human-in-the-loop AI.
  • Bioengineering and rehabilitation.
  • Biosignal processing.
  • Instrumental solutions and measurement principles for smart industry.
  • New challenge for metrology in the digital transformation scenario.

You may choose our Joint Special Issue in Metrology.

Prof. Dr. Egidio De Benedetto
Dr. Antonio Esposito
Guest Editors

Manuscript Submission Information

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Published Papers (5 papers)

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Research

20 pages, 3580 KiB  
Article
Wetsuit Thermal Resistivity Measurements
by Gianluca Crotti, Roberto Cantù, Stefano Malavasi, Gianluca Gatti, Christian Laurano and Cesare Svelto
Sensors 2024, 24(14), 4561; https://doi.org/10.3390/s24144561 - 14 Jul 2024
Viewed by 822
Abstract
In recent years, attention to the realization and characterization of wetsuits for scuba diving and other sea sports or activities has increased. The research has aimed to establish reliable and standardized measurement methods to objectively assess wetsuit quality, particularly focusing on their mechanical [...] Read more.
In recent years, attention to the realization and characterization of wetsuits for scuba diving and other sea sports or activities has increased. The research has aimed to establish reliable and standardized measurement methods to objectively assess wetsuit quality, particularly focusing on their mechanical and thermal properties. In this work, we describe and compare two different measurement methods for the characterization of neoprene wetsuit thermal resistivity. The first method follows the existing regulations in the field, while the second one, which we are originally proposing in this paper, offers an alternative yet accurate way based on a simplified experimental set-up and easier measurements. In both cases, the wetsuit sample under testing was shaped in the form of a cylindrical sleeve of proper dimensions and wrapped around a phantom containing water at a higher temperature and surrounded by water at a lower temperature. The wetsuit’s cylindrical surface allows heat flow from the warmer water on the inside to the colder water on the outside through the wetsuit area. In the first case, a thermal steady state was achieved, with constant heat flow from the phantom to the exterior. This was obtained with a power balance between two homogenous quantities. Electrically supplied thermal heating within the phantom was used to balance the thermal energy naturally flowing through the wetsuit’s surface. In this first case, a stable and fixed temperature difference was obtained between the inner and the outer surfaces of the wetsuit sample. In the second case, a thermal transient was analyzed during the cooling process of the phantom, and the thermal time constant was measured, providing the sample thermal resistance once the phantom thermal capacity was known. In both cases and methods, the heat flow and thermal resistance of other elements than the wetsuit must be evaluated and compensated for if they are not negligible. Finally, the thermal resistivity per unit area of the wetsuit material was obtained with the product of the wetsuit sample’s thermal resistance and the wetsuit area. The measurements, conducted until now by immersing the phantom in a free surface tank, show that both methods—under stationary and under transient temperature conditions—were valid to assess the wetsuit’s thermal resistivity. The stationary method somehow provided better accuracy while involving less well-known parameters but at the expense of a more complicated experimental set-up and additional energy consumption. The transitory method, on the other hand, is quite easy to implement and, after careful characterization of the phantom’s parameters, it provided similar results to the stationary one. An uncertainty budget was evaluated for both methods, and they did provide highly compatible measurement results, with resistivity values of 0.104(9) m2·K/W (stationary method) and 0.095(9) K·m2/W (transient method) for the same wetsuit sample under testing, which is also consistent with the values in the literature. We finally propose that the novel method is a valid alternative for characterization of the thermal insulation properties of a scuba diving wetsuit. Full article
(This article belongs to the Special Issue Selected Papers from the 2023 IEEE International Conference on Metrology for eXtended Reality, Artificial Intelligence and Neural Engineering (IEEE MetroXRAINE 2023))
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19 pages, 13395 KiB  
Article
Design of a Two-Degree-of-Freedom Mechanical Oscillator for Multidirectional Vibration Energy Harvesting to Power Wireless Sensor Nodes
by Hossein Shabanalinezhad, Cesare Svelto, Piero Malcovati and Gianluca Gatti
Sensors 2024, 24(14), 4531; https://doi.org/10.3390/s24144531 - 13 Jul 2024
Viewed by 3396
Abstract
Converting otherwise wasted kinetic energy present in the environment into usable electrical energy to power wireless sensor nodes, is a green strategy to avoid the use of batteries and wires. Most of the energy harvesters presented in the literature are based on the [...] Read more.
Converting otherwise wasted kinetic energy present in the environment into usable electrical energy to power wireless sensor nodes, is a green strategy to avoid the use of batteries and wires. Most of the energy harvesters presented in the literature are based on the exploitation of a one-degree-of-freedom arrangement, consisting of a tuned spring-mass system oscillating in the main direction of the exciting vibration source. However, if the direction of excitation changes, the efficiency of the harvester decreases. This paper thus proposes the idea of a curved cantilever beam with a two-degree-of-freedom arrangement, where the two bending natural frequencies of the mechanical resonator are designed to be equal. This is thought to lead to a configuration design that can be used in practical circumstances where excitation varies its direction in the plane. This, in turn, may possibly lead to a more effective energy-harvesting solution to power nodes in a wireless sensor network. Full article
(This article belongs to the Special Issue Selected Papers from the 2023 IEEE International Conference on Metrology for eXtended Reality, Artificial Intelligence and Neural Engineering (IEEE MetroXRAINE 2023))
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31 pages, 10402 KiB  
Article
Virtual Experience Toolkit: An End-to-End Automated 3D Scene Virtualization Framework Implementing Computer Vision Techniques
by Pau Mora, Clara Garcia, Eugenio Ivorra, Mario Ortega and Mariano L. Alcañiz
Sensors 2024, 24(12), 3837; https://doi.org/10.3390/s24123837 - 13 Jun 2024
Viewed by 1316
Abstract
Virtualization plays a critical role in enriching the user experience in Virtual Reality (VR) by offering heightened realism, increased immersion, safer navigation, and newly achievable levels of interaction and personalization, specifically in indoor environments. Traditionally, the creation of virtual content has fallen under [...] Read more.
Virtualization plays a critical role in enriching the user experience in Virtual Reality (VR) by offering heightened realism, increased immersion, safer navigation, and newly achievable levels of interaction and personalization, specifically in indoor environments. Traditionally, the creation of virtual content has fallen under one of two broad categories: manual methods crafted by graphic designers, which are labor-intensive and sometimes lack precision; traditional Computer Vision (CV) and Deep Learning (DL) frameworks that frequently result in semi-automatic and complex solutions, lacking a unified framework for both 3D reconstruction and scene understanding, often missing a fully interactive representation of the objects and neglecting their appearance. To address these diverse challenges and limitations, we introduce the Virtual Experience Toolkit (VET), an automated and user-friendly framework that utilizes DL and advanced CV techniques to efficiently and accurately virtualize real-world indoor scenarios. The key features of VET are the use of ScanNotate, a retrieval and alignment tool that enhances the precision and efficiency of its precursor, supported by upgrades such as a preprocessing step to make it fully automatic and a preselection of a reduced list of CAD to speed up the process, and the implementation in a user-friendly and fully automatic Unity3D application that guides the users through the whole pipeline and concludes in a fully interactive and customizable 3D scene. The efficacy of VET is demonstrated using a diversified dataset of virtualized 3D indoor scenarios, supplementing the ScanNet dataset. Full article
(This article belongs to the Special Issue Selected Papers from the 2023 IEEE International Conference on Metrology for eXtended Reality, Artificial Intelligence and Neural Engineering (IEEE MetroXRAINE 2023))
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23 pages, 1944 KiB  
Article
Performance Assessment for the Validation of Wireless Communication Engines in an Innovative Wearable Monitoring Platform
by Alessio Serrani and Andrea Aliverti
Sensors 2024, 24(9), 2782; https://doi.org/10.3390/s24092782 - 26 Apr 2024
Cited by 1 | Viewed by 818
Abstract
In today’s health-monitoring applications, there is a growing demand for wireless and wearable acquisition platforms capable of simultaneously gathering multiple bio-signals from multiple body areas. These systems require well-structured software architectures, both to keep different wireless sensing nodes synchronized each other and to [...] Read more.
In today’s health-monitoring applications, there is a growing demand for wireless and wearable acquisition platforms capable of simultaneously gathering multiple bio-signals from multiple body areas. These systems require well-structured software architectures, both to keep different wireless sensing nodes synchronized each other and to flush collected data towards an external gateway. This paper presents a quantitative analysis aimed at validating both the wireless synchronization task (implemented with a custom protocol) and the data transmission task (implemented with the BLE protocol) in a prototype wearable monitoring platform. We evaluated seven frequencies for exchanging synchronization packets (10 Hz, 20 Hz, 30 Hz, 40 Hz, 50 Hz, 60 Hz, 70 Hz) as well as two different BLE configurations (with and without the implementation of a dynamic adaptation of the BLE Connection Interval parameter). Additionally, we tested BLE data transmission performance in five different use case scenarios. As a result, we achieved the optimal performance in the synchronization task (1.18 ticks as median synchronization delay with a Min-Max range of 1.60 ticks and an Interquartile range (IQR) of 0.42 ticks) when exploiting a synchronization frequency of 40 Hz and the dynamic adaptation of the Connection Interval. Moreover, BLE data transmission proved to be significantly more efficient with shorter distances between the communicating nodes, growing worse by 30.5% beyond 8 m. In summary, this study suggests the best-performing network configurations to enhance the synchronization task of the prototype platform under analysis, as well as quantitative details on the best placement of data collectors. Full article
(This article belongs to the Special Issue Selected Papers from the 2023 IEEE International Conference on Metrology for eXtended Reality, Artificial Intelligence and Neural Engineering (IEEE MetroXRAINE 2023))
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9 pages, 1983 KiB  
Communication
Investigation of Climate Effects on the Physiological Parameters of Dairy Livestock (Cow vs. Buffalo)
by Nadia Piscopo, Roberta Matera, Alessio Cotticelli, Lucia Trapanese, Oscar Tamburis, Roberta Cimmino and Angela Salzano
Sensors 2024, 24(4), 1164; https://doi.org/10.3390/s24041164 - 10 Feb 2024
Cited by 1 | Viewed by 1193
Abstract
Nowadays climate change is affecting the planet’s biodiversity, and livestock practices must adapt themselves to improve production without affecting animal welfare. This work investigates the influence that some climatic parameters such as Environment Temperature, Relative Humidity, Thermal excursion and Temperature–Humidity Index (THI), can [...] Read more.
Nowadays climate change is affecting the planet’s biodiversity, and livestock practices must adapt themselves to improve production without affecting animal welfare. This work investigates the influence that some climatic parameters such as Environment Temperature, Relative Humidity, Thermal excursion and Temperature–Humidity Index (THI), can have on milk quantity and quality in two different dairy species (buffaloes and cows) raised on the same farm. A further aim was to understand if THI threshold used for cows could also be used for buffaloes. The climatic parameters were recorded daily through a meteorological station located inside the farm. Milk quantity (converted into ECM) and quality (Fat Percentage—FP; Protein Percentage—PP; Somatic Cell Count—SCC) were measured. Data were analyzed with Spearman’s correlation index, separately for buffaloes and cows. The results indicate a greater sensitivity of cows to heat stress and a strong negative correlation of the ECM with meteorological data (p < 0.01). The results of this study may stimulate the use of integrated technologies (sensors, software) in the dairy sector, since the IoT (sensors, software) helps to enhance animal well-being and to optimize process costs, with a precision livestock farming approach. Full article
(This article belongs to the Special Issue Selected Papers from the 2023 IEEE International Conference on Metrology for eXtended Reality, Artificial Intelligence and Neural Engineering (IEEE MetroXRAINE 2023))
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