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Conference papers
Statistical and Neuro-fuzzy approaches for emboli detection
Abstract : Relation between cerebral emboli occurrence and stroke has been suggested these last years. Emboli detection has then become a constant concern while monitoring cerebral vascular pathologies. This detection is based on analysis of embolic TransCranial Doppler (TCD) signal. In practical experiments, most of detected emboli are big-size emboli ones, because of their easy-to-recognize signature in the TCD signal. The problem of small size emboli detection is an opened one and remains a challenge. Different approaches have been proposed to solve this problem. They use exclusively human expert knowledge or automatic collection of signal parameters. In this paper we propose to used both expert knowledge and automatic processing through neuro-fuzzy approach. Performances evaluation and comparison with high performance micro-emboli detection technique, namely Autoregressive (AR) modelling are provided, using in vitro in this work.
Keywords :
cerebral emboli occurrence
neuro-fuzzy approaches
statistical approaches
cerebral vascular pathology monitoring
embolic TransCranial Doppler signal detection
TCD signal detection
small size emboli detection
automatic signal parameter collection
human expert knowledge
performance evaluation
autoregressive modelling
AR modelling
high performance microemboli detection technique
stroke
https://hal.archives-ouvertes.fr/hal-03149794
Contributor : Françoise Grélaud <>
Submitted on : Wednesday, February 24, 2021 - 11:27:18 AM
Last modification on : Thursday, March 18, 2021 - 2:16:12 PM
Contributor : Françoise Grélaud <>
Submitted on : Wednesday, February 24, 2021 - 11:27:18 AM
Last modification on : Thursday, March 18, 2021 - 2:16:12 PM
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Statistical and Neuro-fuzzy ap...
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