AIMC Topic: Wearable Electronic Devices

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Walking Speed and Uncertainty Estimation Using Mixture Density Networks for Dynamic Ambulatory Environments.

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
Walking speed, often considered a representative indicator of activity levels, becomes notably reduced as muscle strength and cardiovascular function decline with aging. Wearable walking rehabilitation devices aim to alleviate the effort during walki...
Male Algorithms Walking Speed Humans Female Uncertainty Neural Networks, Computer Wearable Electronic Devices Aged Walking
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Remote Motor Rehabilitation: EMG-IMU based Deep Learning Model Improves the Estimate of Wrist Kinematics.

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
Technology for motor rehabilitation faces challenges in uncontrolled settings, such as at home. In these real-world scenarios, robust signals like electromyographic (EMG) and inertial measurement unit (IMU) data are crucial for decoding continuous hu...
Biomechanical Phenomena Male Humans Deep Learning Rehabilitation Neural Networks, Computer Female Wearable Electronic Devices Adult Wrist Electromyography
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ECG Beat-By-Beat Classification Using Hybrid Transformer Neural Network Model in Smart Health.

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 cardiac monitors can be used to detect potential heart attack by syncing with smartphone apps for instant data analysis and alerts. Our goal is to build an efficient smart health application to help patients prevent and early diagnose the ri...
Electrocardiography Signal Processing, Computer-Assisted Algorithms Wearable Electronic Devices Smartphone Humans Neural Networks, Computer
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Cough-DL: A Deep Learning Model for Ear-Worn Cough Detection.

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
Cough serves as a crucial bio-marker for evaluation and monitoring of pulmonary conditions. With growing interest towards automatic cough detection systems, it's important to acknowledge the existing hurdles on the way for a robust cough counter. The...
Deep Learning Wearable Electronic Devices Cough Signal Processing, Computer-Assisted Sound Spectrography Monitoring, Ambulatory Humans
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Enhanced In-Home Human Activity Recognition Using Multimodal Sensing and Spatiotemporal Machine Learning Architecture.

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
In this research, we present an enhanced human activity recognition (HAR) framework using advanced machine learning models incorporating temporal dynamics, leveraging multimodal sensor data. Data from wearable wristbands and real-time location system...
Human Activities Algorithms Wearable Electronic Devices Activities of Daily Living Humans Neural Networks, Computer Machine Learning
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Enhancing Wearable based Real-Time Glucose Monitoring via Phasic Image Representation Learning based Deep Learning.

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
In the U.S., over a third of adults are pre-diabetic, with 80% unaware of their status. This underlines the need for better glucose monitoring to prevent type 2 diabetes and related heart diseases. Existing wearable glucose monitors are limited by th...
Signal Processing, Computer-Assisted Blood Glucose Self-Monitoring Blood Glucose Image Processing, Computer-Assisted Humans Machine Learning Algorithms Deep Learning Wearable Electronic Devices
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Physical, Social and Cognitive Stressor Identification using Electrocardiography-derived Features and Machine Learning from a Wearable Device.

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
Anxiety is a prevalent and detrimental mental health condition affecting young adults, particularly in college students who face a range of stressors including academic pressures, interpersonal relationships, and financial concerns. The ability to pr...
Electrocardiography Support Vector Machine Signal Processing, Computer-Assisted Stress, Psychological Wearable Electronic Devices Cognition Heart Rate Machine Learning Female Young Adult Adult Male Anxiety Humans
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Deep Learning-Based Subject Independent Human Activity Recognition using Smart Lacelock Data.

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
Human Activity Recognition (HAR) field is rapidly growing and the classification of human activities based on sensor data is crucial for applications in healthcare, rehabilitation and numerous other sectors. In this paper we use a novel device and at...
Algorithms Deep Learning Wearable Electronic Devices Humans Neural Networks, Computer Accelerometry Human Activities Shoes
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Shared-task Self-supervised Learning for Estimating Free Movement Unified Parkinson's Disease Rating Scale III.

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
The Unified Parkinson's Disease Rating Scale (UP-DRS) is used to recognize patients with Parkinson's disease (PD) and rate its severity in clinical settings. Machine learning and wearables can reduce the need for clinical examinations and provide a r...
Aged Supervised Machine Learning Male Movement Severity of Illness Index Middle Aged Humans Wearable Electronic Devices Neural Networks, Computer Parkinson Disease Female
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Clinical Assessment of a Lightweight CNN Model for Real-Time Atrial Fibrillation Prediction in Continuous Wearable Monitoring.

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
Atrial Fibrillation (AFib) represents a prevalent cardiac arrhythmia associated with substantial risk for affected individuals. The integration of wearable devices, coupled with advanced predictive models, opens pathways for non-invasive and real-tim...
Neural Networks, Computer Female Male Humans Monitoring, Physiologic Electrocardiography, Ambulatory Atrial Fibrillation Middle Aged Wearable Electronic Devices Electrocardiography
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