title: Estimation of left ventricular stroke volume based on pressure waves measured at the wrist: a method aimed at home-based use.
abstract: Continuous monitoring of stroke volume (SV) or cardiac output (CO) has long been the subject of numerous studies. The majority of existing methods are calibration-dependent, requiring invasive measurements of CO to initialize the estimation algorithms, thus limiting their application to the clinical setting. In the present study, a new calibration-free method aimed at home-based use has been developed, which allows noninvasive estimation of SV from oscillometric signals measured at the wrist. The estimation equation was constructed based on the PRAM method, with significant modifications to incorporate more patient-specific information. Furthermore, the estimation equation was optimized based on the clinical data acquired from 96 patients (the 'Training' group) to obtain the best comparison of estimated SV with echocardiographic SV. The resulting estimation equation was then applied directly to another patient group (the 'Testing' group) to examine its validity. Obtained results demonstrate that our estimations correlated closely with the measurements in both patient groups. In addition to being noninvasive and calibration-free, the proposed method can be fully automated, which may be valuable for the future development of home-based cardiac monitoring systems.
authors.affiliation: School of Naval Architecture, Ocean & Civil Engineering, Shanghai Jiao Tong University, 800 Dongchuan Road, Shanghai, China.
authors.forename: Zhipeng
authors.initials: Z
authors.lastname: Deng
authors.affiliation: Sky Innovation Technology (Shanghai) Co., Ltd., 2016 Yishan Road, Shanghai, China.
authors.forename: Chungang
authors.initials: C
authors.lastname: Zhang
authors.affiliation: Sky Innovation Technology (Shanghai) Co., Ltd., 2016 Yishan Road, Shanghai, China.
authors.forename: Ping
authors.initials: P
authors.lastname: Yu
authors.affiliation: The first people's Hospital of Kunshan, 91 West Qianjin Road, Kunshan, Jiangsu, China.
authors.forename: Jun
authors.initials: J
authors.lastname: Shao
authors.affiliation: School of Naval Architecture, Ocean & Civil Engineering, Shanghai Jiao Tong University, 800 Dongchuan Road, Shanghai, China SJTU-CU International Cooperative Research Center, Shanghai Jiao Tong University, 800 Dongchuan Road, Shanghai, China.
authors.forename: Fuyou
authors.initials: F
authors.lastname: Liang
mesh_terms: D000465:Algorithms; D062186:Arterial Pressure / Q000502:physiology*; D001794:Blood Pressure / Q000502:physiology*; D001795:Blood Pressure Determination / Q000379:methods*; D003198:Computer Simulation; D003936:Diagnosis, Computer-Assisted / Q000379:methods*; D005260:Female; D006801:Humans; D008297:Male; D008875:Middle Aged; D008955:Models, Cardiovascular; D009991:Oscillometry / Q000379:methods; D011673:Pulsatile Flow / Q000502:physiology*; D017534:Radial Artery; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D013318:Stroke Volume / Q000502:physiology*; D058067:Wavelet Analysis
keywords: Stroke volume; coefficient optimization; noninvasive estimation; oscillometric signals