Non-Invasive Wearable Patch Utilizing Seismocardiography for Peri-Operative Use in Surgical Patients

• Published in: IEEE journal of biomedical and health informatics Vol. 25; no. 5; pp. 1572 - 1582
• Main Authors: Semiz, Beren, Carek, Andrew M., Johnson, Jessica C., Ahmad, Shireen, Heller, J. Alex, Vicente, Florencia G., Caron, Stacey, Hogue, Charles W., Etemadi, Mozziyar, Inan, Omer T.
• Format: Journal Article
• Language: English
• Published: United States IEEE 01.05.2021; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Biomedical monitoring; Doppler effect; EKG; Electrocardiography; Fluid management; Hemodynamics; Humans; Monitoring; Monitoring, Physiologic; Patients; Perioperative Care; Protocols; Seismocardiography; Signal processing; Signal Processing, Computer-Assisted; Signal quality; Sternum; Stroke; Stroke Volume; Surgery; transesophageal doppler; Wearable Electronic Devices; Wearable technology
• ISSN: 2168-2194; 2168-2208
• DOI: 10.1109/JBHI.2020.3032938

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.