Vector-Based Analysis of the Similarity Between Breathing and Heart Rate During Paced Deep Breathing

Kleyko, Denis; Osipov, Evgeny; Wiklund, Urban

doi:10.22489/cinc.2018.146

Cited by 3 publications

(2 citation statements)

References 4 publications

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“…In [220,221], BSC was applied to biomedical signals: heart rate and respiration. The need for comparing these signals emerged in the scope of a deep breathing test for assessing autonomic function.…”

Section: Similarity Estimation Of Biomedical Signalsmentioning

confidence: 99%

A Survey on Hyperdimensional Computing aka Vector Symbolic Architectures, Part II: Applications, Cognitive Models, and Challenges

et al. 2023

Self Cite

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This is Part II of the two-part comprehensive survey devoted to a computing framework most commonly known under the names Hyperdimensional Computing and Vector Symbolic Architectures (HDC/VSA). Both names refer to a family of computational models that use high-dimensional distributed representations and rely on the algebraic properties of their key operations to incorporate the advantages of structured symbolic representations and vector distributed representations. Holographic Reduced Representations [322, 327] is an influential HDC/VSA model that is well-known in the machine learning domain and often used to refer to the whole family. However, for the sake of consistency, we use HDC/VSA to refer to the field. Part I of this survey [223] covered foundational aspects of the field, such as the historical context leading to the development of HDC/VSA, key elements of any HDC/VSA model, known HDC/VSA models, and the transformation of input data of various types into high-dimensional vectors suitable for HDC/VSA. This second part surveys existing applications, the role of HDC/VSA in cognitive computing and architectures, as well as directions for future work. Most of the applications lie within the Machine Learning/Artificial Intelligence domain, however, we also cover other applications to provide a complete picture. The survey is written to be useful for both newcomers and practitioners.

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Section: Similarity Estimation Of Biomedical Signalsmentioning

confidence: 99%

A Survey on Hyperdimensional Computing aka Vector Symbolic Architectures, Part II: Applications, Cognitive Models, and Challenges

et al. 2023

Self Cite

View full text Add to dashboard Cite

show abstract

“…In [Kleyko et al, 2018b], [Kleyko et al, 2019b], BSC was applied to biomedical signals: heart rate and respiration. The need for comparing these signals emerged in the scope of a deep breathing test for assessing autonomic function.…”

Section: Similarity Estimation Of Biomedical Signalsmentioning

confidence: 99%

A Survey on Hyperdimensional Computing aka Vector Symbolic Architectures, Part II: Applications, Cognitive Models, and Challenges

Kleyko,

Rachkovskij,

Osipov

et al. 2021

Preprint

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This is Part II of the two-part comprehensive survey devoted to a computing framework most commonly known under the names Hyperdimensional Computing and Vector Symbolic Architectures (HDC/VSA). Both names refer to a family of computational models that use high-dimensional distributed representations and rely on the algebraic properties of their key operations to incorporate the advantages of structured symbolic representations and vector distributed representations. Holographic Reduced Representations [Plate, 1995], [Plate, 2003] is an influential HDC/VSA model that is well-known in the machine learning domain and often used to refer to the whole family. However, for the sake of consistency, we use HDC/VSA to refer to the area.Part I of this survey [Kleyko et al., 2021c] covered foundational aspects of the area, such as historical context leading to the development of HDC/VSA, key elements of any HDC/VSA model, known HDC/VSA models, and transforming input data of various types into high-dimensional vectors suitable for HDC/VSA. This second part surveys existing applications, the role of HDC/VSA in cognitive computing and architectures, as well as directions for future work. Most of the applications lie within the machine learning/artificial intelligence domain, however we also cover other applications to provide a thorough picture. The survey is written to be useful for both newcomers and practitioners.

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Virtual reality based Neural Sensors with Respirator for Cardiorespiratory Synchrony Training System

Lu,

Yeh,

et al. 2024

2024 9th IEEE International Conference on Smart Cloud (SmartCloud)

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Vector-Based Analysis of the Similarity Between Breathing and Heart Rate During Paced Deep Breathing

Cited by 3 publications

References 4 publications

A Survey on Hyperdimensional Computing aka Vector Symbolic Architectures, Part II: Applications, Cognitive Models, and Challenges

A Survey on Hyperdimensional Computing aka Vector Symbolic Architectures, Part II: Applications, Cognitive Models, and Challenges

A Survey on Hyperdimensional Computing aka Vector Symbolic Architectures, Part II: Applications, Cognitive Models, and Challenges

Virtual reality based Neural Sensors with Respirator for Cardiorespiratory Synchrony Training System

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