Visualization methods for assisting detection of cardiovascular neuropathy

David J Cornforth; Mika P Tarvainen; Herbert Jelinek

doi:10.1109/EMBC.2014.6945159

Visualization methods for assisting detection of cardiovascular neuropathy

David J Cornforth, Mika P Tarvainen, Herbert Jelinek

Research output: Book chapter/Published conference paper › Conference paper › peer-review

1 Citation (Scopus)

Abstract

Visualization models can assist in understanding the complex pattern of disease, where the signs may be buried in complex data. In this work we propose a new method for visualization of data derived from Heart Rate Variability (HRV) analysis, to indicate whether a person has developed, or is developing, signs of definite Cardiac Autonomic Neuropathy (CAN). Here, the visualizations are compared with actual data recorded from people attending a diabetes clinic with and without definite CAN. Indications from the new visualization technique are compared to the results of established diagnostic measures using the Ewing battery of tests. We find the proposed method to offer useful insights into this disease, as rather than relying upon a binary yes/no decision, it offers a comprehensive picture of the complexity of this disease.

Original language	English
Title of host publication	Proceedings of the 2014 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society
Place of Publication	United States
Publisher	IEEE, Institute of Electrical and Electronics Engineers
Pages	6675-6678
Number of pages	4
ISBN (Electronic)	9781424479290
DOIs	https://doi.org/10.1109/EMBC.2014.6945159
Publication status	Published - 2014
Event	2014 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC) - Sheraton Hotel & Towers, Chicago, United States Duration: 26 Aug 2014 → 30 Aug 2014 https://web.archive.org/web/20140621102347/http://embc.embs.org/2014/ (Archived page)

Conference

Conference	2014 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)
Abbreviated title	Discovering, Innovating, and Engineering Future Biomedicine
Country/Territory	United States
City	Chicago
Period	26/08/14 → 30/08/14
Internet address	https://web.archive.org/web/20140621102347/http://embc.embs.org/2014/ (Archived page)

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Cornforth, D. J., Tarvainen, M. P., & Jelinek, H. (2014). Visualization methods for assisting detection of cardiovascular neuropathy. In Proceedings of the 2014 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (pp. 6675-6678). IEEE, Institute of Electrical and Electronics Engineers. https://doi.org/10.1109/EMBC.2014.6945159

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title = "Visualization methods for assisting detection of cardiovascular neuropathy",

abstract = "Visualization models can assist in understanding the complex pattern of disease, where the signs may be buried in complex data. In this work we propose a new method for visualization of data derived from Heart Rate Variability (HRV) analysis, to indicate whether a person has developed, or is developing, signs of definite Cardiac Autonomic Neuropathy (CAN). Here, the visualizations are compared with actual data recorded from people attending a diabetes clinic with and without definite CAN. Indications from the new visualization technique are compared to the results of established diagnostic measures using the Ewing battery of tests. We find the proposed method to offer useful insights into this disease, as rather than relying upon a binary yes/no decision, it offers a comprehensive picture of the complexity of this disease.",

author = "Cornforth, {David J} and Tarvainen, {Mika P} and Herbert Jelinek",

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year = "2014",

doi = "10.1109/EMBC.2014.6945159",

language = "English",

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booktitle = "Proceedings of the 2014 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society",

publisher = "IEEE, Institute of Electrical and Electronics Engineers",

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Cornforth, DJ, Tarvainen, MP & Jelinek, H 2014, Visualization methods for assisting detection of cardiovascular neuropathy. in Proceedings of the 2014 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE, Institute of Electrical and Electronics Engineers, United States, pp. 6675-6678, 2014 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), Chicago, Illinois, United States, 26/08/14. https://doi.org/10.1109/EMBC.2014.6945159

Visualization methods for assisting detection of cardiovascular neuropathy. / Cornforth, David J; Tarvainen, Mika P; Jelinek, Herbert.
Proceedings of the 2014 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society. United States: IEEE, Institute of Electrical and Electronics Engineers, 2014. p. 6675-6678.

Research output: Book chapter/Published conference paper › Conference paper › peer-review

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N2 - Visualization models can assist in understanding the complex pattern of disease, where the signs may be buried in complex data. In this work we propose a new method for visualization of data derived from Heart Rate Variability (HRV) analysis, to indicate whether a person has developed, or is developing, signs of definite Cardiac Autonomic Neuropathy (CAN). Here, the visualizations are compared with actual data recorded from people attending a diabetes clinic with and without definite CAN. Indications from the new visualization technique are compared to the results of established diagnostic measures using the Ewing battery of tests. We find the proposed method to offer useful insights into this disease, as rather than relying upon a binary yes/no decision, it offers a comprehensive picture of the complexity of this disease.

AB - Visualization models can assist in understanding the complex pattern of disease, where the signs may be buried in complex data. In this work we propose a new method for visualization of data derived from Heart Rate Variability (HRV) analysis, to indicate whether a person has developed, or is developing, signs of definite Cardiac Autonomic Neuropathy (CAN). Here, the visualizations are compared with actual data recorded from people attending a diabetes clinic with and without definite CAN. Indications from the new visualization technique are compared to the results of established diagnostic measures using the Ewing battery of tests. We find the proposed method to offer useful insights into this disease, as rather than relying upon a binary yes/no decision, it offers a comprehensive picture of the complexity of this disease.

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ER -

Visualization methods for assisting detection of cardiovascular neuropathy

Abstract

Conference

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