Non-Invasive Wearable Patch Utilizing Seismocardiography for Peri-Operative Use in Surgical Patients
| Autor: | Beren Semiz, Florencia Garcia Vicente, Charles W. Hogue, Shireen Ahmad, Stacey Caron, Mozziyar Etemadi, J. Alex Heller, Jessica C. Johnson, Omer T. Inan, Andrew M. Carek |
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| Rok vydání: | 2021 |
| Předmět: |
medicine.medical_specialty
Remote patient monitoring Wearable computer 030204 cardiovascular system & hematology Article Perioperative Care Electrocardiography Wearable Electronic Devices 03 medical and health sciences 0302 clinical medicine Health Information Management 030202 anesthesiology Internal medicine Humans Medicine In patient Electrical and Electronic Engineering Monitoring Physiologic medicine.diagnostic_test business.industry Non invasive Signal Processing Computer-Assisted Stroke Volume Perioperative Stroke volume Computer Science Applications Cardiology business Biotechnology Surgical patients |
| Zdroj: | IEEE J Biomed Health Inform |
| ISSN: | 2168-2208 2168-2194 |
| Popis: | Objective: Optimizing peri-operative fluid management has been shown to improve patient outcomes and the use of stroke volume (SV) measurement has become an accepted tool to guide fluid therapy. The Transesophageal Doppler (TED) is a validated, minimally invasive device that allows clinical assessment of SV. Unfortunately, the use of the TED is restricted to the intra-operative setting in anesthetized patients and requires constant supervision and periodic adjustment for accurate signal quality. However, post-operative fluid management is also vital for improved outcomes. Currently, there is no device regularly used in clinics that can track patient's SV continuously and non-invasively both during and after surgery. Methods: In this paper, we propose the use of a wearable patch mounted on the mid-sternum, which captures the seismocardiogram (SCG) and electrocardiogram (ECG) signals continuously to predict SV in patients undergoing major surgery. In a study of 12 patients, hemodynamic data was recorded simultaneously using the TED and wearable patch. Signal processing and regression techniques were used to derive SV from the signals (SCG and ECG) captured by the wearable patch and compare it to values obtained by the TED. Results: The results showed that the combination of SCG and ECG contains substantial information regarding SV, resulting in a correlation and median absolute error between the predicted and reference SV values of 0.81 and 7.56 mL, respectively. Significance: This work shows promise for the proposed wearable-based methodology to be used as an alternative to TED for continuous patient monitoring and guiding peri-operative fluid management. |
| Databáze: | OpenAIRE |
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