Related references
Note: Only part of the references are listed.A deep learning method for continuous noninvasive blood pressure monitoring using photoplethysmography
Hao Liang et al.
PHYSIOLOGICAL MEASUREMENT (2023)
Measuring psychosocial stress with heart rate variability-based methods in different health and age groups
Santtu M. Seipajarvi et al.
PHYSIOLOGICAL MEASUREMENT (2022)
Wrist Photoplethysmography Signal Quality Assessment for Reliable Heart Rate Estimate and Morphological Analysis
Serena Moscato et al.
SENSORS (2022)
Reduced heart-rate variability and increased risk of hypertension-a prospective study of the ELSA-Brasil
Rosangela A. Hoshi et al.
JOURNAL OF HUMAN HYPERTENSION (2021)
Photoplethysmography (PPG): state-of-the-art methods and applications
John Allen et al.
PHYSIOLOGICAL MEASUREMENT (2021)
The Application of Deep Learning Algorithms for PPG Signal Processing and Classification
Filipa Esgalhado et al.
COMPUTERS (2021)
Common wearable devices demonstrate variable accuracy in measuring heart rate during supraventricular tachycardia
Nicholas Sequeira et al.
HEART RHYTHM (2020)
An examination of single day vs. multi-day heart rate variability and its relationship to heart rate recovery following maximal aerobic exercise in females
Emily Bechke et al.
SCIENTIFIC REPORTS (2020)
Locomotion in virtual environments predicts cardiovascular responsiveness to subsequent stressful challenges
Joao Rodrigues et al.
NATURE COMMUNICATIONS (2020)
Longer apneas and hypopneas are associated with greater ultra-short-term HRV in obstructive sleep apnea
Salla Hietakoste et al.
SCIENTIFIC REPORTS (2020)
Investigating sources of inaccuracy in wearable optical heart rate sensors
Brinnae Bent et al.
NPJ DIGITAL MEDICINE (2020)
Heart Rate Estimation From Wrist-Worn Photoplethysmography: A Review
Dwaipayan Biswas et al.
IEEE SENSORS JOURNAL (2019)
Apple Watch, Wearables, and Heart Rhythm: where do we stand?
Joel M. Raja et al.
ANNALS OF TRANSLATIONAL MEDICINE (2019)
Accuracy of commercially available heart rate monitors in athletes: a prospective study
Selena R. Pasadyn et al.
CARDIOVASCULAR DIAGNOSIS AND THERAPY (2019)
Developing and adopting safe and effective digital biomarkers to improve patient outcomes
Andrea Coravos et al.
NPJ DIGITAL MEDICINE (2019)
Deep Learning-Based Electrocardiogram Signal Noise Detection and Screening Model
Dukyong Yoon et al.
HEALTHCARE INFORMATICS RESEARCH (2019)
Analysis: An optimal filter for short photoplethysmogram signals
Yongbo Liang et al.
SCIENTIFIC DATA (2018)
TROIKA: A General Framework for Heart Rate Monitoring Using Wrist-Type Photoplethysmographic Signals During Intensive Physical Exercise
Zhilin Zhang et al.
IEEE TRANSACTIONS ON BIOMEDICAL ENGINEERING (2015)
Signal-Quality Indices for the Electrocardiogram and Photoplethysmogram: Derivation and Applications to Wireless Monitoring
Christina Orphanidou et al.
IEEE JOURNAL OF BIOMEDICAL AND HEALTH INFORMATICS (2015)
Signal quality measures for pulse oximetry through waveform morphology analysis
J. Abdul Sukor et al.
PHYSIOLOGICAL MEASUREMENT (2011)