AIMC Topic: Wearable Electronic Devices

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Non-Invasive Remote Monitoring in Heart Failure: Towards Wearable Devices and Artificial Intelligence Solutions : Short Title: Remote Monitoring and Wearable Devices in Heart Failure.

Current heart failure reports
PURPOSE OF REVIEW: This review examines the potential benefits of non-invasive remote monitoring in patients with heart failure (HF), focusing on early detection of clinical deterioration and reducing hospitalizations. Key questions addressed include...

An intelligent, compact wearable pressure-strain combo sensor system for continuous fetal movement monitoring.

Science advances
Continuous fetal movement monitoring in late pregnancy may improve fetal wellbeing and pregnancy outcomes. While fetal movements can be visualized with ultrasound, it is intermittent and limited to clinical settings. Inertial measurement units may en...

Rat robot autonomous border detection based on wearable sensors.

Bioinspiration & biomimetics
Bio-robots, a novel type of robot based on a brain-machine interface, have shown great potential in search and rescue tasks. Current research is focused on the bio-robot itself, such as locomotion, localization and navigation, but lacks interactions ...

Wearable sensing for badminton stroke recognition with one-dimensional convolutional neural network.

Scientific reports
Motivated by the need to improve the performance of badminton players, various motion monitoring systems have been developed to assist coaches in badminton technique instruction. While traditional video or optical methods are limited to fixed scenari...

Enhancing psychological resilience and decision-making in basketball players through emerging technologies.

Scientific reports
The combination of sports psychology and new wearable technology is allowing experts to assess psychological and cognitive performance in elite basketball more accurately. This study investigates the application of Human Activity Recognition (HAR) us...

The BRAINTEASER Datasets: Clinical, Wearable and Environmental Data for ALS & MS Progression Modeling.

Scientific data
Amyotrophic lateral sclerosis (ALS) and multiple sclerosis (MS) are debilitating diseases with unpredictable progression. Artificial Intelligence-based tools for modelling disease progression could significantly improve the quality of life for patien...

Effective and comfortable chain-linking anchoring with anisotropic stiffness for soft wearable robots.

Scientific reports
This study presents a wearable robot equipped with a novel anchoring structure designed to improve both force transmission efficiency and user comfort. While soft wearable robots are inherently more comfortable than rigid exoskeletons, they often suf...

Reducing Artifact Preprocessing in Heart Rate Variability-Based Personalized Psychosis Prediction Using Adaptive Long Short-Term Memory Models.

International journal of neural systems
This research looks at the use of long-short-term memory (LSTM) networks to predict psychosis, in patients within the schizophrenia spectrum, based on Heart Rate Variability (HRV) data acquired from wearable devices. Our primary objective is to test ...

Deep domain adaptation eliminates costly data required for task-agnostic wearable robotic control.

Science robotics
Data-driven methods have transformed our ability to assess and respond to human movement with wearable robots, promising real-world rehabilitation and augmentation benefits. However, the proliferation of data-driven methods, with the associated deman...

A multimodal physiological dataset for non-invasive blood glucose estimation.

Scientific data
Diabetes is a major health challenge that affects millions of people worldwide. Managing diabetes effectively requires monitoring blood glucose levels continuously, typically through invasive sensing devices such as continuous glucose monitors (CGMs)...