Time-Frequency Techniques in Wrist Pulse Signals
Nidhi Garg1, Nikita Babbar2
1Nidhi Garg*, Department of Electronics and Communication, University Institute of Engineering and Technology (UIET), Panjab University (PU), Chandigarh, India.
2Nikita Babbar , Department of Electronics and Communication, University Institute of Engineering and Technology (UIET), Panjab University (PU), Chandigarh, India.
Manuscript received on September 17, 2019. | Revised Manuscript received on 24 September, 2019. | Manuscript published on October 10, 2019. | PP: 2679-2682 | Volume-8 Issue-12, October 2019. | Retrieval Number: L25201081219/2019©BEIESP | DOI: 10.35940/ijitee.L2520.1081219
Open Access | Ethics and Policies | Cite | Mendeley | Indexing and Abstracting
© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Wrist pulse signal has been the traditional way of diagnosing human health in India. It is a low frequency, non-stationary signal. There are broadly three techniques of analyzing a signal – time, frequency and time-frequency domain. The individual time and frequency domain representations of the signal do not provide much information on properties of a non-stationary signal. However, the time-frequency distributions of a non-stationary signal overcome these problems and provide more information about the pulse signal. This paper presents the various time-frequency distribution techniques for analyzing non-stationary wrist pulse signals .
Keywords: Wrist Pulse Signals, Non Stationary Signal, Time-Frequency Domain.
Scope of the Article: Frequency Selective Surface