Signal processing approaches to analyzing patient cardiovascular state
Thesis (M. Eng.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2011.
| Main Author: | |
|---|---|
| Other Authors: | |
| Format: | Thesis |
| Language: | eng |
| Published: |
Massachusetts Institute of Technology
2011
|
| Subjects: | |
| Online Access: | http://hdl.handle.net/1721.1/66448 |
| _version_ | 1826214496570441728 |
|---|---|
| author | Mishra, Ekavali |
| author2 | George C. Verghese and Thomas Heldt. |
| author_facet | George C. Verghese and Thomas Heldt. Mishra, Ekavali |
| author_sort | Mishra, Ekavali |
| collection | MIT |
| description | Thesis (M. Eng.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2011. |
| first_indexed | 2024-09-23T16:06:41Z |
| format | Thesis |
| id | mit-1721.1/66448 |
| institution | Massachusetts Institute of Technology |
| language | eng |
| last_indexed | 2024-09-23T16:06:41Z |
| publishDate | 2011 |
| publisher | Massachusetts Institute of Technology |
| record_format | dspace |
| spelling | mit-1721.1/664482019-04-10T18:00:38Z Signal processing approaches to analyzing patient cardiovascular state Mishra, Ekavali George C. Verghese and Thomas Heldt. Massachusetts Institute of Technology. Dept. of Electrical Engineering and Computer Science. Massachusetts Institute of Technology. Dept. of Electrical Engineering and Computer Science. Electrical Engineering and Computer Science. Thesis (M. Eng.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2011. Cataloged from PDF version of thesis. Includes bibliographical references (p. 51-52). There is a wealth of unanalyzed data stored in patient records that could yield insight into a patient's cardiovascular state during surgery and causes of fluctuations in hemodynamics. Recent work suggests that time spent outside a certain blood pressure range corresponds to an increased risk of adverse outcomes after surgery. An analysis of blood pressures recorded during surgery could also be tied to patient fluid responsiveness, pulse pressure variability (PPV) can be a predictor of fluid responsiveness in surgical patients. Thus, a comparison of physiological variables such as cardiac output (CO), total peripheral resistance (TPR), and PPV of patients who experience adverse outcomes to those who do not could help explain the link between adverse outcomes and intraoperative blood pressure variations. Data from patients undergoing cardiothoracic surgery was used to investigate intraoperative hemodynamics. Patients were separated into two groups: those who experienced adverse outcomes within 30 days of surgery (cases) and those who did not (controls). A comparison of blood pressure values extracted from patient data revealed that cases had higher systolic and lower diastolic values during surgery. CO and TPR were computed from these data but a comparison of variability for the two groups yielded no conclusive results. by Ekavali Mishra. M.Eng. 2011-10-17T21:27:08Z 2011-10-17T21:27:08Z 2011 2011 Thesis http://hdl.handle.net/1721.1/66448 755791023 eng M.I.T. theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. See provided URL for inquiries about permission. http://dspace.mit.edu/handle/1721.1/7582 52 p. application/pdf Massachusetts Institute of Technology |
| spellingShingle | Electrical Engineering and Computer Science. Mishra, Ekavali Signal processing approaches to analyzing patient cardiovascular state |
| title | Signal processing approaches to analyzing patient cardiovascular state |
| title_full | Signal processing approaches to analyzing patient cardiovascular state |
| title_fullStr | Signal processing approaches to analyzing patient cardiovascular state |
| title_full_unstemmed | Signal processing approaches to analyzing patient cardiovascular state |
| title_short | Signal processing approaches to analyzing patient cardiovascular state |
| title_sort | signal processing approaches to analyzing patient cardiovascular state |
| topic | Electrical Engineering and Computer Science. |
| url | http://hdl.handle.net/1721.1/66448 |
| work_keys_str_mv | AT mishraekavali signalprocessingapproachestoanalyzingpatientcardiovascularstate |