AIMC Topic: Accelerometry
Clear Filters Showing 221 to 230 of 261 articles
Processing UK Biobank High Resolution Accelerometry Data for Unsupervised Identification of Activity Profiles and Their Differences in Clinically Relevant Outcome Parameters - The ATLAS Index Revisited.
Studies in health technology and informatics
May 15, 2025
Accelerometer data obtained with wearable devices over extended periods of time provides objective, valuable information on activity behavior. Building on previous work to derive easy-to-interpret activity parameters - the Activity Types from Long-te...
Long Short-Term Memory Network for Accelerometer-Based Hypertension Classification.
Studies in health technology and informatics
May 15, 2025
This study investigates the application of a Long Short-Term Memory (LSTM) architecture for classifying hypertension using accelerometer data, specifically focusing on physical activity and sleep from the publicly available NHANES 2011-2012 dataset. ...
Hidden Markov model-based similarity measure (HMM-SM) for gait quality assessment of lower-limb prosthetic users using inertial sensor signals.
Journal of neuroengineering and rehabilitation
May 12, 2025
BACKGROUND: Gait quality indices, such as the Gillette Gait Index or Gait Profile Score (GPS), can provide clinicians with objective, straightforward measures to quantify gait pathology and monitor changes over time. However, these methods often requ...
Validation of a fingertip home sleep apnea testing system using deep learning AI and a temporal event localization analysis.
Sleep
May 12, 2025
STUDY OBJECTIVES: This paper validates TipTraQ, a compact home sleep apnea testing (HSAT) system. TipTraQ comprises a fingertip-worn device, a mobile application, and a cloud-based deep learning artificial intelligence (AI) system. The device utilize...
Comparative Analysis of Machine Learning Approaches for Fetal Movement Detection with Linear Acceleration and Angular Rate Signals.
Sensors (Basel, Switzerland)
May 7, 2025
Reduced fetal movement (RFM) can indicate that a fetus is at risk, but current monitoring methods provide only a "snapshot in time" of fetal health and require trained clinicians in clinical settings. To improve antenatal care, there is a need for co...
Speech Detection via Respiratory Inductance Plethysmography, Thoracic Impedance, Accelerometers, and Gyroscopes: A Machine Learning-Informed Comparative Study.
Psychophysiology
Feb 1, 2025
Speech production interferes with the measurement of changes in cardiac vagal activity during acute stress by attenuating the expected drop in heart rate variability. Speech also induces cardiac sympathetic changes similar to those induced by psychol...
Machine Learning Models to Identify Clinically Significant Anxiety in Short-Term Insomnia Using Accelerometers.
Depression and anxiety
Jan 1, 2025
Clinically significant anxiety (CSA) is common in individuals with short-term insomnia. This study aims to explore the relationship between CSA and the subjective and objective parameters of sleep in patients with short-term insomnia and construct ma...
Predicting physical functioning status in older adults: insights from wrist accelerometer sensors and derived digital biomarkers of physical activity.
Journal of the American Medical Informatics Association : JAMIA
Nov 1, 2024
OBJECTIVE: Conventional physical activity (PA) metrics derived from wearable sensors may not capture the cumulative, transitions from sedentary to active, and multidimensional patterns of PA, limiting the ability to predict physical function impairme...
Comparing Cadence vs. Machine Learning Based Physical Activity Intensity Classifications: Variations in the Associations of Physical Activity With Mortality.
Scandinavian journal of medicine & science in sports
Sep 1, 2024
Step cadence-based and machine-learning (ML) methods have been used to classify physical activity (PA) intensity in health-related research. This study examined the association of intensity-specific PA duration with all-cause (ACM) and CVD mortality ...
Simulating Accelerometer Signals of Parkinson's Gait Using Generative Adversarial Networks.
Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Jul 1, 2024
Wearable technologies have been demonstrated to have value in the objective assessment of Parkinson's disease. However, certain symptoms such as freezing of gait are challenging to monitor using current approaches. Data augmentation, wherein syntheti...
Stay Ahead of Medical AI
Join thousands of healthcare professionals staying informed about the latest AI breakthroughs in medicine. Get curated insights delivered to your inbox.
Subscribe NowPopular Topics
- Machine Learning 31032
- Neural Networks, Computer 29717
- Algorithms 26831
- Deep Learning 26345
- Artificial Intelligence 24290
- Robotics 13311
- Image Processing, Computer-Assisted 9521
- Retrospective Studies 9110
- Magnetic Resonance Imaging 6181
- Reproducibility of Results 5592
- Tomography, X-Ray Computed 4770
- Support Vector Machine 4686
- Computational Biology 4236
- Brain 4050
- Computer Simulation 3881
Recent Journals
- Scientific reports 5940
- Sensors (Basel, Switzerland) 4794
- PloS one 4015
- Neural networks : the official journal of the International Neural Network Society 2929
- Computational intelligence and neuroscience 1931
- Computers in biology and medicine 1854
- Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference 1686
- Studies in health technology and informatics 1278
- IEEE journal of biomedical and health informatics 1130
- Journal of chemical information and modeling 998
- Nature communications 943
- Computer methods and programs in biomedicine 883
- Bioinformatics (Oxford, England) 861
- Briefings in bioinformatics 853
- IEEE transactions on neural networks and learning systems 826