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Photoplethysmography (PPG)-based blood pressure (BP) estimation is a challenging task, particularly on resource-constrained wearable devices. However, fully on-board processing is desirable to ensure user data confidentiality. Recent deep…

Background. Wearable accelerometry devices allow collection of high-density activity data in large epidemiological studies both in-the-lab as well as in-the-wild (free-living). Such data can be used to detect and identify periods of…

Quantitative Methods · Quantitative Biology 2017-11-20 Jacek K. Urbanek , Vadim Zipunnikov , Tamara Harris , Ciprian Crainiceanu , Jaroslaw Harezlak , Nancy W. Glynn

Consumer-grade smartwatches offer a new personalized health monitoring option for general consumers globally as cardiovascular diseases continue to prevail as the leading cause of global mortality. The development and validation of reliable…

Human-Computer Interaction · Computer Science 2025-12-04 Jathushan Kaetheeswaran , Boyi Ma , Ali Abedi , Milad Lankarany , Shehroz Khan

Wearable electronics hold great potential in defining new paradigms of modern healthcare, including personalized health management, precision medicine, and athletic performance optimization. This stems from their ability in enabling…

Biomolecules · Quantitative Biology 2025-12-02 Yuhan Zheng

The vast majority of cardiovascular diseases may be preventable if early signs and risk factors are detected. Cardiovascular monitoring with body-worn sensor devices like sensor patches allows for the detection of such signs while…

Background: Photoplethysmography (PPG) is a non-invasive optical sensing technique widely used to capture hemodynamic information, with broad deployment in both clinical monitoring systems and wearable devices. In recent years, the…

Artificial Intelligence · Computer Science 2026-05-06 Guangkun Nie , Jiabao Zhu , Gongzheng Tang , Deyun Zhang , Shijia Geng , Qinghao Zhao , Shenda Hong

In the process of patient diagnosis, non-invasive measurements are widely used due to their low risks and quick results. Electrocardiogram (ECG), as a non-invasive method to collect heart activities, is used to diagnose cardiac conditions.…

Machine Learning · Computer Science 2025-12-11 Yuhao Xu , Jiaying Lu , Sirui Ding , Defu Cao , Xiao Hu , Carl Yang

Smart wearables enable continuous tracking of established biomarkers such as heart rate, heart rate variability, and blood oxygen saturation via photoplethysmography (PPG). Beyond these metrics, PPG waveforms contain richer physiological…

Biometric authentication using physiological signals offers a promising path toward secure and user-friendly access control in wearable devices. While electrocardiogram (ECG) signals have shown high discriminability, their intrusive sensing…

Cryptography and Security · Computer Science 2025-08-20 Wei Shao , Zequan Liang , Ruoyu Zhang , Ruijie Fang , Ning Miao , Ehsan Kourkchi , Setareh Rafatirad , Houman Homayoun , Chongzhou Fang

Smart watches and other wearable devices are equipped with photoplethysmography (PPG) sensors for monitoring heart rate and other aspects of cardiovascular health. However, PPG signals collected from such devices are susceptible to…

Signal Processing · Electrical Eng. & Systems 2023-07-12 Pranay Jain , Cheng Ding , Cynthia Rudin , Xiao Hu

Electrocardiography (ECG) is the clinical gold standard for cardiovascular disease (CVD) assessment, yet continuous monitoring is constrained by the need for dedicated hardware and trained personnel. Photoplethysmography (PPG) is ubiquitous…

Machine Learning · Computer Science 2026-01-22 Xiaocheng Fang , Jiarui Jin , Haoyu Wang , Che Liu , Jieyi Cai , Yujie Xiao , Guangkun Nie , Bo Liu , Shun Huang , Hongyan Li , Shenda Hong

Walking speed estimation is an essential component of mobile apps in various fields such as fitness, transportation, navigation, and health-care. Most existing solutions are focused on specialized medical applications that utilize body-worn…

Computers and Society · Computer Science 2019-03-07 Aawesh Shrestha , Myounggyu Won

Automatic detection and tracking of emotional states has the potential for helping individuals with various mental health conditions. While previous studies have captured physiological signals using wearable devices in laboratory settings,…

Signal Processing · Electrical Eng. & Systems 2024-01-12 Michal K. Grzeszczyk , Anna Lisowska , Arkadiusz Sitek , Aneta Lisowska

Objective- Heart rate monitoring using wrist type Photoplethysmographic (PPG) signals is getting popularity because of construction simplicity and low cost of wearable devices. The task becomes very difficult due to the presence of various…

Healthcare data now span EHRs, medical imaging, genomics, and wearable sensors, but most diagnostic models still process these modalities in isolation. This limits their ability to capture early, cross-modal disease signatures. This paper…

Machine Learning · Computer Science 2025-12-18 Md Talha Mohsin , Ismail Abdulrashid

Electrocardiogram (ECG) biometrics have emerged as a promising modality for continuous, liveness-aware authentication in wearable systems. However, many prior studies report overly optimistic results due to data leakage (e.g., random splits…

Machine Learning · Computer Science 2026-05-05 Milad Parvan

Biometric measurements captured from medical devices, such as blood pressure gauges, glucose monitors, and weighing scales, are essential to tracking a patient's health. Trends in these measurements can accurately track diabetes,…

Computer Vision and Pattern Recognition · Computer Science 2018-07-16 Varun N. Shenoy , Oliver O. Aalami

Wearable sensors inWireless Body Area Networks (WBANs) provide health and physical activity monitoring. Modern communication systems have extended this monitoring remotely. In this survey, various types of wearable sensors discussed, their…

Systems and Control · Computer Science 2016-11-15 A. Rehman , M. Mustafa , N. Javaid , U. Qasim , Z. A. Khan

Automatic classification of running styles can enable runners to obtain feedback with the aim of optimizing performance in terms of minimizing energy expenditure, fatigue, and risk of injury. To develop a system capable of classifying…

Machine Learning · Computer Science 2021-09-24 Setareh Rahimi Taghanaki , Michael Rainbow , Ali Etemad

Head-based signals such as EEG, EMG, EOG, and ECG collected by wearable systems will play a pivotal role in clinical diagnosis, monitoring, and treatment of important brain disorder diseases. However, the real-time transmission of the…