Hope your postdoctoral position in Singapore is great! Remember I emailed you a few months ago!
Listen, I've been studying your package since past january now, and seems to me like there is no reliable/robust way to handle gradient artefacts with NK... So I reviewed the literature about ECG signal processing and found how I could qualify and correct for false detection with mean-square error minimization. Thanks to Pekkanen's segmenter, I could come up with something not so terrible.
Hi @DominiqueMakowski ,
Hope your postdoctoral position in Singapore is great! Remember I emailed you a few months ago!
Listen, I've been studying your package since past january now, and seems to me like there is no reliable/robust way to handle gradient artefacts with NK... So I reviewed the literature about ECG signal processing and found how I could qualify and correct for false detection with mean-square error minimization. Thanks to Pekkanen's segmenter, I could come up with something not so terrible.
Anyways, I was wondering if you had any knowledge of higher-order statistics filter design such as this one : https://www.degruyter.com/view/j/bmte.2018.63.issue-4/bmt-2016-0232/bmt-2016-0232.xml ... or, Really, any other way to analyse my noisy signals.
I'd be willing to explore this and try to implement this 4th order central-moment filter! I'm currently waiting for one of the author's response.
Thanks