Name
Abstract | ||
|---|---|---|
Intracranial pressure (ICP) is a cranial vital sign, crucial in the monitoring and treatment of several neurological injuries. The clinically accepted measurement modalities of ICP are highly invasive, carrying risks of infection and limiting the benefits of ICP measurement to a small subset of critically ill patients. This work aims to take a step towards developing an accurate noninvasive means of estimating ICP, by utilizing a model-based frequency-domain approach. The mean ICP and pulse pressures of ICE are estimated from arterial blood pressure (ABP) and cerebral blood flow velocity (CBFV) waveforms, and the estimates are validated on an adult population, comprising of around two hours of data from five patients. The algorithm was shown to have an accuracy (mean error) of 1.5 mmHg and a precision (standard deviation of the error) of 4.3 mmHg in estimating the mean ICP. These results are comparable to the previously reported errors among the currently accepted invasive measurement methods, and well within the clinically relevant range. |
Year | DOI | Venue |
|---|---|---|
2019 | 10.1109/EMBC.2019.8857042 | 2019 41ST ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY (EMBC) |
Field | DocType | Volume |
Population,Computer science,Mean squared error,Artificial intelligence,Blood pressure,Frequency domain,Computer vision,Internal medicine,Cardiology,Intracranial pressure,Cerebral blood flow,Standard deviation,Limiting | Conference | 2019 |
ISSN | Citations | PageRank |
1557-170X | 0 | 0.34 |
References | Authors | |
0 | 6 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Rohan Jaishankar | 1 | 0 | 0.68 |
| Andrea Fanelli | 2 | 11 | 3.33 |
| Aristotelis Filippidis | 3 | 0 | 0.34 |
| Thai Vu | 4 | 0 | 0.34 |
| James Holsapple | 5 | 0 | 0.34 |
| Thomas Heldt | 6 | 2 | 9.54 |