- like time based, frequency domain base or non linear based parameters from HRV in connection with parameters from central nervous system (EEG or NIRS).
Thank you for your reply:
We got data from HRV and EEG during cycling exercise with constant workload and different cadence. At start and end we got same cadence, so we could also investigate influence of duration. I just want to find someone who already discussed data from autonomic nervous system in connection with data from central nervous system DURING exercise. In HRV data we found cadence and duration dependent changes especially in non-linear parameters like dfa-1-alpha. May be we could discuss these data in connection to complex fatigue models because of decreasing complexity of RR-fluctuations and retraction of the homeodynamic system.
If you got interesting hints let me know. Thomas
I attempt to evidence that in this case during exercise we lose stationarity.
Also the analysis of variability as resulting in my profile could be appropriate,
unfortunately the system does not accept answers containing more than few words.
Hi Thomas,
Indeed, as mentioned by Pr. Conte, your use-case leads to a non-stationary HRV and the use of the standard FFT method is meaningless here. Non-linear analysis is needed.
You might want to check the dynamic Sympathetic/Parasympathetic activities using our approach by downloading CODESNA_HRV here:
http://www.codesna.com/en/products/codesna_hrv/
You might find some correlations with the EEG from the autonomic regulation.
On the below user guide you will find some examples of results you will get from your data:
http://www.codesna.com/wp-content/uploads/guide-utilisateur/User_Guide_CODESNA_HRV.pdf
Let me know if you have any question.
Regards,
Vasile
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