AIMC Topic: Wearable Electronic Devices

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Twistable and Stretchable Nasal Patch for Monitoring Sleep-Related Breathing Disorders Based on a Stacking Ensemble Learning Model.

ACS applied materials & interfaces
Obstructive sleep apnea syndrome disrupts sleep, destroys the homeostasis of biological systems such as metabolism and the immune system, and reduces learning ability and memory. The existing polysomnography used to measure sleep disorders is execute...

Digital Biomarker for Muscle Function Assessment Using Surface Electromyography With Electrical Stimulation and a Non-Invasive Wearable Device.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
Sarcopenia is a comprehensive degenerative disease with the progressive loss of skeletal muscle mass with age, accompanied by the loss of muscle strength and muscle dysfunction. Individuals with unmanaged sarcopenia may experience adverse outcomes. P...

AI-Based Denoising of Head Impact Kinematics Measurements With Convolutional Neural Network for Traumatic Brain Injury Prediction.

IEEE transactions on bio-medical engineering
OBJECTIVE: Wearable devices are developed to measure head impact kinematics but are intrinsically noisy because of the imperfect interface with human bodies. This study aimed to improve the head impact kinematics measurements obtained from instrument...

Machine-learning models for shoulder rehabilitation exercises classification using a wearable system.

Knee surgery, sports traumatology, arthroscopy : official journal of the ESSKA
PURPOSE: The objective of this study is to train and test machine-learning (ML) models to automatically classify shoulder rehabilitation exercises.

Predicting the Healing of Lower Extremity Fractures Using Wearable Ground Reaction Force Sensors and Machine Learning.

Sensors (Basel, Switzerland)
Lower extremity fractures pose challenges due to prolonged healing times and limited assessment methods. Integrating wearable sensors with machine learning can help overcome these challenges by providing objective assessment and predicting fracture h...

Advances in Machine Learning for Wearable Sensors.

ACS nano
Recent years have witnessed tremendous advances in machine learning techniques for wearable sensors and bioelectronics, which play an essential role in real-time sensing data analysis to provide clinical-grade information for personalized healthcare....

Kinematics-Based Predictions of External Loads during Handcycling.

Sensors (Basel, Switzerland)
The increased risk of cardiovascular disease in people with spinal cord injuries motivates work to identify exercise options that improve health outcomes without causing risk of musculoskeletal injury. Handcycling is an exercise mode that may be bene...

Machine learning and wearable sensors for automated Parkinson's disease diagnosis aid: a systematic review.

Journal of neurology
BACKGROUND: The diagnosis of Parkinson's disease is currently based on clinical evaluation. Despite clinical hallmarks, unfortunately, the error rate is still significant. Low in-vivo diagnostic accuracy of clinical evaluation mainly relies on the la...

Exo-Glove Shell: A Hybrid Rigid-Soft Wearable Robot for Thumb Opposition with an Under-Actuated Tendon-Driven System.

Soft robotics
Usability and functionality are important when designing hand-wearable robots; however, satisfying both indicators remains a challenging issue, even though researchers have made important progress with state-of-the-art robot components. Although hand...

Automatic Detection of Fatigued Gait Patterns in Older Adults: An Intelligent Portable Device Integrating Force and Inertial Measurements with Machine Learning.

Annals of biomedical engineering
PURPOSE: This study aimed to assess the feasibility of early detection of fatigued gait patterns for older adults through the development of a smart portable device.