Date of Award

Summer 8-2026

Document Type

Dissertation

Degree Name

Doctor of Philosophy (PhD)

Department

Mechanical & Aerospace Engineering

Program/Concentration

Mechanical Engineering

Committee Director

Julie Z Hao

Committee Member

Leryn Reynolds

Committee Member

Dipankar Ghosh

Committee Member

Krishnanand Kaipa

Abstract

This dissertation presents a single-degree-of-freedom (SDOF) based time–frequency analysis framework that can simultaneously extract a comprehensive set of cardiovascular autonomic indices from arterial pulse wave recordings obtained at rest and post-exercise, supporting non-invasive monitoring of autonomic recovery during cardiac rehabilitation. The framework rests on three technical contributions.

First, an SDOF analytical model of motion artefacts quantifies two physically distinct distortion mechanisms: additive baseline drift and Time-Varying System Parameter (TVSP) generated distortion of the Tissue-Contact-Sensor (TCS) stack. Baseline drift is slowly varying and removable by filtering; TVSP distortion rides on all harmonics of the true pulse signal and cannot be removed by conventional filtering. This provides a more complete physical basis for understanding signal distortion in tactile pulse sensing. Second, two hybrid time-frequency algorithms are developed: masking-based Empirical Mode Decomposition (EMD) followed by Hilbert Vibrational Decomposition (HVD), and Complex Demodulation (CDM) followed by HVD, each incorporating a cycle-matched padding strategy that reduces boundary distortions in instantaneous parameter estimation to a tolerable level. CDM followed by HVD is selected as the primary method on grounds of higher and more consistent correlation.

The framework is evaluated on arterial pulse data from 24 cardiac rehabilitation patients. Resting indices such as HR and HRV did not show the changes expected from cardiac rehabilitation; factors such as medication, device therapy, and rhythm conditions including atrial fibrillation, along with other unrecorded factors, could be involved. In contrast, exercise-derived indices HRR% and HRRe% showed some meaningful visit-to-visit change in several patients, though these observations are suggestive rather than definitive. The novel SHRV index distinguished progressive autonomic stabilization from ongoing autonomic instability in ways that conventional single-value HRV cannot capture. Normalized harmonic amplitude analysis showed that the post-exercise arterial stiffness response was either absent or substantially attenuated across the cardiac patient groups, consistent with impaired autonomic cardiovascular modulation.

The results support the feasibility of simultaneous multi-index cardiovascular assessment from the non-invasive arterial pulse waveform and position the SDOF-TF framework as a candidate platform for longitudinal non-invasive cardiovascular monitoring.

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DOI

10.25777/ftpy-6031

ISBN

9798193214311

ORCID

0000-0001-8405-2227

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