Evaluation and development of methods for time-frequency analysis of heart rate variability
(2015) FMS820 20151Mathematical 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:
http://lup.lub.lu.se/student-papers/record/7752474
- author
- Reinhold, Isabella LU
- supervisor
- organization
- course
- FMS820 20151
- year
- 2015
- 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}}, }