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Evaluation and development of methods for time-frequency analysis of heart rate variability

Reinhold, Isabella LU (2015) FMS820 20151
Mathematical Statistics
Abstract
Non-stationary signals are very common in nature, consider for example speech, music or heart rate. Using the concept of time-frequency analysis this thesis studies the performance of different time-frequency distributions of both simulated and real non-stationary signals. The signals studied are linear and non-linear frequency modulated (FM) signals. Two methods are studied to increase performance of the signals' time-frequency distributions. Since lag-independent kernels perform well with slow varying frequency modulated signals both methods use these. One method uses filtering with compact support lag-independent kernels and the other uses a penalty function with multitapers corresponding to lag-independent kernels. These methods are... (More)
Non-stationary signals are very common in nature, consider for example speech, music or heart rate. Using the concept of time-frequency analysis this thesis studies the performance of different time-frequency distributions of both simulated and real non-stationary signals. The signals studied are linear and non-linear frequency modulated (FM) signals. Two methods are studied to increase performance of the signals' time-frequency distributions. Since lag-independent kernels perform well with slow varying frequency modulated signals both methods use these. One method uses filtering with compact support lag-independent kernels and the other uses a penalty function with multitapers corresponding to lag-independent kernels. These methods are then evaluated using two performance measures and the results are used to improve the time-frequency distributions of heart rate variability signals. The thesis suggests that both of these methods improve the time-frequency distribution of such signals. (Less)
Please use this url to cite or link to this publication:
author
Reinhold, Isabella LU
supervisor
organization
course
FMS820 20151
year
type
H2 - Master's Degree (Two Years)
subject
language
English
id
7752474
date added to LUP
2017-01-30 14:54:07
date last changed
2017-01-30 14:54:07
@misc{7752474,
  abstract     = {Non-stationary signals are very common in nature, consider for example speech, music or heart rate. Using the concept of time-frequency analysis this thesis studies the performance of different time-frequency distributions of both simulated and real non-stationary signals. The signals studied are linear and non-linear frequency modulated (FM) signals. Two methods are studied to increase performance of the signals' time-frequency distributions. Since lag-independent kernels perform well with slow varying frequency modulated signals both methods use these. One method uses filtering with compact support lag-independent kernels and the other uses a penalty function with multitapers corresponding to lag-independent kernels. These methods are then evaluated using two performance measures and the results are used to improve the time-frequency distributions of heart rate variability signals. The thesis suggests that both of these methods improve the time-frequency distribution of such signals.},
  author       = {Reinhold, Isabella},
  language     = {eng},
  note         = {Student Paper},
  title        = {Evaluation and development of methods for time-frequency analysis of heart rate variability},
  year         = {2015},
}