Literature DB >> 26208369

BioWatch: A Noninvasive Wrist-Based Blood Pressure Monitor That Incorporates Training Techniques for Posture and Subject Variability.

Simi Susan Thomas, Viswam Nathan, Chengzhi Zong, Karthikeyan Soundarapandian, Xiangrong Shi, Roozbeh Jafari.   

Abstract

Noninvasive continuous blood pressure (BP) monitoring is not yet practically available for daily use. Challenges include making the system easily wearable, reducing noise level and improving accuracy. Variations in each person's physical characteristics, as well as the possibility of different postures, increase the complexity of continuous BP monitoring, especially outside the hospital. This study attempts to provide an easily wearable solution and proposes training to specific posture and individual for further improving accuracy. The wrist watch-based system we developed can measure electrocardiogram and photoplethysmogram. From these two signals, we measure pulse transit time through which we can obtain systolic and diastolic blood pressure through regression techniques. In this study, we investigate various functions to perform the training to obtain blood pressure. We validate measurements on different postures and subjects, and show the value of training the device to each posture and each subject. We observed that the average RMSE between the measured actual systolic BP and calculated systolic BP is between 7.83 to 9.37 mmHg across 11 subjects. The corresponding range of error for diastolic BP is 5.77 to 6.90 mmHg. The system can also automatically detect the arm position of the user using an accelerometer with an average accuracy of 98%, to make sure that the sensor is kept at the proper height. This system, called BioWatch, can potentially be a unified solution for heart rate, SPO2 and continuous BP monitoring.

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Mesh:

Year:  2015        PMID: 26208369     DOI: 10.1109/JBHI.2015.2458779

Source DB:  PubMed          Journal:  IEEE J Biomed Health Inform        ISSN: 2168-2194            Impact factor:   5.772


  23 in total

Review 1.  A Systematic Review of Wearable Patient Monitoring Systems - Current Challenges and Opportunities for Clinical Adoption.

Authors:  Mirza Mansoor Baig; Hamid GholamHosseini; Aasia A Moqeem; Farhaan Mirza; Maria Lindén
Journal:  J Med Syst       Date:  2017-06-19       Impact factor: 4.460

2.  Toward Ubiquitous Blood Pressure Monitoring via Pulse Transit Time: Predictions on Maximum Calibration Period and Acceptable Error Limits.

Authors:  Ramakrishna Mukkamala; Jin-Oh Hahn
Journal:  IEEE Trans Biomed Eng       Date:  2017-09-22       Impact factor: 4.538

3.  Cuffless Blood Pressure Monitoring from an Array of Wrist Bio-Impedance Sensors Using Subject-Specific Regression Models: Proof of Concept.

Authors:  Bassem Ibrahim; Roozbeh Jafari
Journal:  IEEE Trans Biomed Circuits Syst       Date:  2019-10-10       Impact factor: 3.833

Review 4.  Advancing Artificial Intelligence in Health Settings Outside the Hospital and Clinic.

Authors:  Nakul Aggarwal; Mahnoor Ahmed; Sanjay Basu; John J Curtin; Barbara J Evans; Michael E Matheny; Shantanu Nundy; Mark P Sendak; Carmel Shachar; Rashmee U Shah; Sonoo Thadaney-Israni
Journal:  NAM Perspect       Date:  2020-11-30

5.  A Meta-Learning Approach for Fast Personalization of Modality Translation Models in Wearable Physiological Sensing.

Authors:  Ali Akbari; Jonathan Martinez; Roozbeh Jafari
Journal:  IEEE J Biomed Health Inform       Date:  2022-04-14       Impact factor: 7.021

6.  A Wrist-Worn Strap with an Array of Electrodes for Robust Physiological Sensing.

Authors:  Bassem Ibrahim; Justin McMurray; And Roozbeh Jafari
Journal:  Annu Int Conf IEEE Eng Med Biol Soc       Date:  2018-07

7.  Pulse Wave Modeling Using Bio-Impedance Simulation Platform Based on a 3D Time-Varying Circuit Model.

Authors:  Bassem Ibrahim; Drew A Hall; Roozbeh Jafari
Journal:  IEEE Trans Biomed Circuits Syst       Date:  2021-03-30       Impact factor: 3.833

8.  Developing Personalized Models of Blood Pressure Estimation from Wearable Sensors Data Using Minimally-trained Domain Adversarial Neural Networks.

Authors:  Lida Zhang; Nathan C Hurley; Bassem Ibrahim; Erica Spatz; Harlan M Krumholz; Roozbeh Jafari; Bobak J Mortazavi
Journal:  Proc Mach Learn Res       Date:  2020-08

Review 9.  A Wearable Tele-Health System towards Monitoring COVID-19 and Chronic Diseases.

Authors:  Wei Jiang; Sumit Majumder; Samarth Kumar; Sophini Subramaniam; Xiaohe Li; Ridha Khedri; Tapas Mondal; Mansour Abolghasemian; Imran Satia; M Jamal Deen
Journal:  IEEE Rev Biomed Eng       Date:  2022-01-20

Review 10.  A Viewpoint on Wearable Technology-Enabled Measurement of Wellbeing and Health-Related Quality of Life in Parkinson's Disease.

Authors:  Janet M T van Uem; Tom Isaacs; Alan Lewin; Eros Bresolin; Dina Salkovic; Alberto J Espay; Helen Matthews; Walter Maetzler
Journal:  J Parkinsons Dis       Date:  2016-03-10       Impact factor: 5.568

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