{"title":"The EXPERIENCE Project: Automatic virtualization of “extended personal reality” through biomedical signal processing and explainable artificial intelligence [Applications Corner]","authors":"Gaetano Valenza;Mariano Alcañiz;Vladimir Carli;Gabriela Dudnik;Claudio Gentili;Jaime Guixeres Provinciale;Simone Rossi;Nicola Toschi;Virginie van Wassenhove","doi":"10.1109/MSP.2023.3344430","DOIUrl":"https://doi.org/10.1109/MSP.2023.3344430","url":null,"abstract":"The transformation of communication media has revolutionized social interactions, incorporating audio and video into our lives. Despite the recent availability of virtual reality (VR) technology, its widespread adoption faces obstacles. Technological challenges in creating VR environments and scientific confounding concerning interindividual variability in responses to virtual simulations are key factors hindering its broader integration. The EXPERIENCE project makes real the complex interplay among multisensory perception, emotional responses, and extended social interactions by allowing the public-at-large to create their own VR environments automatically through portable devices (e.g., smartphones/tablets) without the need for technical skills. The VR environment augmented by an individual’s physiological responses, psychological and cognitive descriptors, and behavioral outcomes defines the individual’s subjective experience, namely, an individual’s extended personal reality (EPR). The virtualization of a person’s EPR provides a holistic and quantitative environment that can be shared with others to transfer personalized psychological and emotional responses. Additionally, EPR assessment enables subsequent manipulation of the VR through explainable artificial intelligence (AI) routines merging multisensory biofeedback, individualized perception of time-space, and neuromodulation. This technology can be exploited in a plethora of innovative scenarios, including mental healthcare, gaming, e-learning, and neuroeconomics, also leading to the creation of a new market for sharing and selling (virtual) \u0000<italic>experiences</i>\u0000.","PeriodicalId":13246,"journal":{"name":"IEEE Signal Processing Magazine","volume":null,"pages":null},"PeriodicalIF":14.9,"publicationDate":"2024-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140559334","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Introducing the New Area Editors for SPM [Society News]","authors":"","doi":"10.1109/MSP.2024.3377282","DOIUrl":"https://doi.org/10.1109/MSP.2024.3377282","url":null,"abstract":"Provides society information that may include news, reviews or technical notes that should be of interest to practitioners and researchers.","PeriodicalId":13246,"journal":{"name":"IEEE Signal Processing Magazine","volume":null,"pages":null},"PeriodicalIF":14.9,"publicationDate":"2024-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10502198","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140559336","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"In Memoriam: Allen Gorin [In Memoriam]","authors":"","doi":"10.1109/MSP.2023.3346228","DOIUrl":"https://doi.org/10.1109/MSP.2023.3346228","url":null,"abstract":"Recounts the career and contributions of Allen Gorin.","PeriodicalId":13246,"journal":{"name":"IEEE Signal Processing Magazine","volume":null,"pages":null},"PeriodicalIF":14.9,"publicationDate":"2024-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10502222","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140559415","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"An Exciting Juncture for Signal Processing Research: On Building Bridges, Challenges, and Opportunities [From the Editor]","authors":"Tülay Adali","doi":"10.1109/MSP.2024.3377308","DOIUrl":"https://doi.org/10.1109/MSP.2024.3377308","url":null,"abstract":"A warm greeting to the signal processing community as I start my term as the editor-in-chief of \u0000<italic>IEEE Signal Processing Magazine</i>\u0000 (\u0000<italic>SPM</i>\u0000). I hope to be worthy of the confidence invested in me and to be able to follow successfully in Christian Jutten’s footsteps. He led our magazine for three years with dedication and brought timely topics like green signal processing, ethics, and reproducibility to the attention of our community. I certainly have big shoes to fill!","PeriodicalId":13246,"journal":{"name":"IEEE Signal Processing Magazine","volume":null,"pages":null},"PeriodicalIF":14.9,"publicationDate":"2024-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10502029","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140559275","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"2023 Index IEEE Signal Processing Magazine Vol. 40","authors":"","doi":"10.1109/MSP.2023.3332238","DOIUrl":"10.1109/MSP.2023.3332238","url":null,"abstract":"","PeriodicalId":13246,"journal":{"name":"IEEE Signal Processing Magazine","volume":null,"pages":null},"PeriodicalIF":14.9,"publicationDate":"2023-11-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10317600","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135763511","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Sub-Nyquist Coherent Imaging Using an Optimizing Multiplexed Sampling Scheme [Tips & Tricks]","authors":"Yeonwoo Jeong;Behnam Tayebi;Jae-Ho Han","doi":"10.1109/MSP.2023.3310710","DOIUrl":"https://doi.org/10.1109/MSP.2023.3310710","url":null,"abstract":"Several techniques have been developed to overcome the limitation of sensor bandwidth for 2D signals \u0000<xref>[1]</xref>\u0000. Though compressive sensing is an attractive technique that reduces the number of measurements required to record information on a sparse signal basis \u0000<xref>[2]</xref>\u0000, \u0000<xref>[3]</xref>\u0000, recording information beyond the Nyquist frequency remains difficult when working with nonsparse signals. Given this constraint, this article focuses on the use of the physical bandwidth of a coherent signal in the complex form instead of its intensity form. The resulting trick combines holographic multiplexing with sampling scheme optimization to obtain the information in a 2D coherent signal from beyond the Nyquist frequency range. The prerequisites for understanding this article are a knowledge of basic algebra and the Fourier transform. Familiarity with holography is also beneficial.","PeriodicalId":13246,"journal":{"name":"IEEE Signal Processing Magazine","volume":null,"pages":null},"PeriodicalIF":14.9,"publicationDate":"2023-11-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"71902875","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"2024 IEEE Conference on Computational Imaging Using Synthetic Apertures (CISA)","authors":"","doi":"10.1109/MSP.2023.3316949","DOIUrl":"https://doi.org/10.1109/MSP.2023.3316949","url":null,"abstract":"","PeriodicalId":13246,"journal":{"name":"IEEE Signal Processing Magazine","volume":null,"pages":null},"PeriodicalIF":14.9,"publicationDate":"2023-11-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10313226","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"71903520","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Luis Albert Zavala-Mondragón;Peter H.N. de With;Fons van der Sommen
{"title":"A Signal Processing Interpretation of Noise-Reduction Convolutional Neural Networks: Exploring the mathematical formulation of encoding-decoding CNNs","authors":"Luis Albert Zavala-Mondragón;Peter H.N. de With;Fons van der Sommen","doi":"10.1109/MSP.2023.3300100","DOIUrl":"https://doi.org/10.1109/MSP.2023.3300100","url":null,"abstract":"Encoding-decoding convolutional neural networks (CNNs) play a central role in data-driven noise reduction and can be found within numerous deep learning algorithms. However, the development of these CNN architectures is often done in an ad hoc fashion and theoretical underpinnings for important design choices are generally lacking. Up to now, there have been different existing relevant works that have striven to explain the internal operation of these CNNs. Still, these ideas are either scattered and/or may require significant expertise to be accessible for a bigger audience. To open up this exciting field, this article builds intuition on the theory of deep convolutional framelets (TDCFs) and explains diverse encoding-decoding (ED) CNN architectures in a unified theoretical framework. By connecting basic principles from signal processing to the field of deep learning, this self-contained material offers significant guidance for designing robust and efficient novel CNN architectures.","PeriodicalId":13246,"journal":{"name":"IEEE Signal Processing Magazine","volume":null,"pages":null},"PeriodicalIF":14.9,"publicationDate":"2023-11-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"71903526","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}