[Wearable Devices: Perspectives on Assessing and Monitoring Human Physiological Status]

Overview

Journal Sheng Wu Yi Xue Gong Cheng Xue Za Zhi

Specialty Biomedical Engineering

Date 2023 Dec 28

PMID 38151926

Authors

Chung-Kang Peng

Xingran Cui

Zhengbo Zhang

Mengsun Yu

Affiliations

Soon will be listed here.

Abstract

This review article aims to explore the major challenges that the healthcare system is currently facing and propose a new paradigm shift that harnesses the potential of wearable devices and novel theoretical frameworks on health and disease. Lifestyle-induced diseases currently account for a significant portion of all healthcare spending, with this proportion projected to increase with population aging. Wearable devices have emerged as a key technology for implementing large-scale healthcare systems focused on disease prevention and management. Advancements in miniaturized sensors, system integration, the Internet of Things, artificial intelligence, 5G, and other technologies have enabled wearable devices to perform high-quality measurements comparable to medical devices. Through various physical, chemical, and biological sensors, wearable devices can continuously monitor physiological status information in a non-invasive or minimally invasive way, including electrocardiography, electroencephalography, respiration, blood oxygen, blood pressure, blood glucose, activity, and more. Furthermore, by combining concepts and methods from complex systems and nonlinear dynamics, we developed a novel theory of continuous dynamic physiological signal analysis-dynamical complexity. The results of dynamic signal analyses can provide crucial information for disease prevention, diagnosis, treatment, and management. Wearable devices can also serve as an important bridge connecting doctors and patients by tracking, storing, and sharing patient data with medical institutions, enabling remote or real-time health assessments of patients, and providing a basis for precision medicine and personalized treatment. Wearable devices have a promising future in the healthcare field and will be an important driving force for the transformation of the healthcare system, while also improving the health experience for individuals.

Citing Articles

[Digital twin hospitals: transforming the future of healthcare].

Hu H, Wang M, Lei Q, Yang K, Sun H, Liu X Sheng Wu Yi Xue Gong Cheng Xue Za Zhi. 2024; 41(2):376-382.

PMID: 38686420 PMC: 11058498. DOI: 10.7507/1001-5515.202310041.

References

Guo D, Thomas R, Liu Y, Shea S, Lu J, Peng C . Slow wave synchronization and sleep state transitions. Sci Rep. 2022; 12(1):7467. PMC: 9076647. DOI: 10.1038/s41598-022-11513-0. View

. Heart rate variability: standards of measurement, physiological interpretation and clinical use. Task Force of the European Society of Cardiology and the North American Society of Pacing and Electrophysiology. Circulation. 1996; 93(5):1043-65. View

Anand I, Greenberg B, Fogoros R, Libbus I, Katra R . Design of the Multi-Sensor Monitoring in Congestive Heart Failure (MUSIC) study: prospective trial to assess the utility of continuous wireless physiologic monitoring in heart failure. J Card Fail. 2010; 17(1):11-6. DOI: 10.1016/j.cardfail.2010.08.001. View

Zhang S, Li Y, Zhang S, Shahabi F, Xia S, Deng Y . Deep Learning in Human Activity Recognition with Wearable Sensors: A Review on Advances. Sensors (Basel). 2022; 22(4). PMC: 8879042. DOI: 10.3390/s22041476. View

Zhang S, Zhao Y, Nguyen D, Xu R, Sen S, Hester J . NeckSense: A Multi-Sensor Necklace for Detecting Eating Activities in Free-Living Conditions. Proc ACM Interact Mob Wearable Ubiquitous Technol. 2021; 4(2). PMC: 8248934. DOI: 10.1145/3397313. View

Holman H . The Relation of the Chronic Disease Epidemic to the Health Care Crisis. ACR Open Rheumatol. 2020; 2(3):167-173. PMC: 7077778. DOI: 10.1002/acr2.11114. View

Anand I, Tang W, Greenberg B, Chakravarthy N, Libbus I, Katra R . Design and performance of a multisensor heart failure monitoring algorithm: results from the multisensor monitoring in congestive heart failure (MUSIC) study. J Card Fail. 2012; 18(4):289-95. DOI: 10.1016/j.cardfail.2012.01.009. View

Ates H, Nguyen P, Gonzalez-Macia L, Morales-Narvaez E, Guder F, Collins J . End-to-end design of wearable sensors. Nat Rev Mater. 2022; 7(11):887-907. PMC: 9306444. DOI: 10.1038/s41578-022-00460-x. View

Poongodi M, Hamdi M, Malviya M, Sharma A, Dhiman G, Vimal S . Diagnosis and combating COVID-19 using wearable Oura smart ring with deep learning methods. Pers Ubiquitous Comput. 2021; 26(1):25-35. PMC: 7908947. DOI: 10.1007/s00779-021-01541-4. View

10.

Bayoumy K, Gaber M, Elshafeey A, Mhaimeed O, Dineen E, Marvel F . Smart wearable devices in cardiovascular care: where we are and how to move forward. Nat Rev Cardiol. 2021; 18(8):581-599. PMC: 7931503. DOI: 10.1038/s41569-021-00522-7. View

11.

Nelson B, Allen N . Accuracy of Consumer Wearable Heart Rate Measurement During an Ecologically Valid 24-Hour Period: Intraindividual Validation Study. JMIR Mhealth Uhealth. 2019; 7(3):e10828. PMC: 6431828. DOI: 10.2196/10828. View

12.

Hansen T, Li Y, Boggia J, Thijs L, Richart T, Staessen J . Predictive role of the nighttime blood pressure. Hypertension. 2010; 57(1):3-10. DOI: 10.1161/HYPERTENSIONAHA.109.133900. View

13.

Seshadri D, Davies E, Harlow E, Hsu J, Knighton S, Walker T . Wearable Sensors for COVID-19: A Call to Action to Harness Our Digital Infrastructure for Remote Patient Monitoring and Virtual Assessments. Front Digit Health. 2021; 2:8. PMC: 8521919. DOI: 10.3389/fdgth.2020.00008. View

14.

Smith G, Prytherch D, Meredith P, Schmidt P, Featherstone P . The ability of the National Early Warning Score (NEWS) to discriminate patients at risk of early cardiac arrest, unanticipated intensive care unit admission, and death. Resuscitation. 2013; 84(4):465-70. DOI: 10.1016/j.resuscitation.2012.12.016. View

15.

Han D, Bashar S, Mohagheghian F, Ding E, Whitcomb C, McManus D . Premature Atrial and Ventricular Contraction Detection using Photoplethysmographic Data from a Smartwatch. Sensors (Basel). 2020; 20(19). PMC: 7582300. DOI: 10.3390/s20195683. View

16.

Kim J, Campbell A, de Avila B, Wang J . Wearable biosensors for healthcare monitoring. Nat Biotechnol. 2019; 37(4):389-406. PMC: 8183422. DOI: 10.1038/s41587-019-0045-y. View

17.

Stehlik J, Schmalfuss C, Bozkurt B, Nativi-Nicolau J, Wohlfahrt P, Wegerich S . Continuous Wearable Monitoring Analytics Predict Heart Failure Hospitalization: The LINK-HF Multicenter Study. Circ Heart Fail. 2020; 13(3):e006513. DOI: 10.1161/CIRCHEARTFAILURE.119.006513. View

18.

Perez M, Mahaffey K, Hedlin H, Rumsfeld J, Garcia A, Ferris T . Large-Scale Assessment of a Smartwatch to Identify Atrial Fibrillation. N Engl J Med. 2019; 381(20):1909-1917. PMC: 8112605. DOI: 10.1056/NEJMoa1901183. View

19.

Silcock D, Corfield A, Gowens P, Rooney K . Validation of the National Early Warning Score in the prehospital setting. Resuscitation. 2015; 89:31-5. DOI: 10.1016/j.resuscitation.2014.12.029. View

20.

Ma C, Zhang P, Wang J, Zhang J, Pan L, Li X . Objective quantification of the severity of postural tremor based on kinematic parameters: A multi-sensory fusion study. Comput Methods Programs Biomed. 2022; 219:106741. DOI: 10.1016/j.cmpb.2022.106741. View