AIMC Topic: Wearable Electronic Devices

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Personalized Clustering for Emotion Recognition Improvement.

Sensors (Basel, Switzerland)
Emotion recognition through artificial intelligence and smart sensing of physical and physiological signals (affective computing) is achieving very interesting results in terms of accuracy, inference times, and user-independent models. In this sense,...

Machine Learning and Statistical Analyses of Sensor Data Reveal Variability Between Repeated Trials in Parkinson's Disease Mobility Assessments.

Sensors (Basel, Switzerland)
Mobility tasks like the Timed Up and Go test (TUG), cognitive TUG (cogTUG), and walking with turns provide insights into the impact of Parkinson's disease (PD) on motor control, balance, and cognitive function. We assess the test-retest reliability o...

Review on Portable-Powered Lower Limb Exoskeletons.

Sensors (Basel, Switzerland)
Advancements in science and technology have driven the growing use of robots in daily life, with Portable-Powered Lower Limb Exoskeletons (PPLLEs) emerging as a key innovation. The selection of mechanisms, control strategies, and sensors directly inf...

Haptiknit: Distributed stiffness knitting for wearable haptics.

Science robotics
Haptic devices typically rely on rigid actuators and bulky power supply systems, limiting wearability. Soft materials improve comfort, but careful distribution of stiffness is required to ground actuation forces and enable load transfer to the skin. ...

Labyrinthine Wrinkle-Patterned Fiber Sensors Based on a 3D Stress Complementary Strategy for Machine Learning-Enabled Medical Monitoring and Action Recognition.

Small (Weinheim an der Bergstrasse, Germany)
Fiber strain sensors show good application potential in the field of wearable smart fabrics and equipment because of their characteristics of easy deformation and weaving. However, the integration of fiber strain sensors with sensitive response, good...

Domain Adversarial Convolutional Neural Network Improves the Accuracy and Generalizability of Wearable Sleep Assessment Technology.

Sensors (Basel, Switzerland)
Wearable accelerometers are widely used as an ecologically valid and scalable solution for long-term at-home sleep monitoring in both clinical research and care. In this study, we applied a deep learning domain adversarial convolutional neural networ...

Improvement of an Edge-IoT Architecture Driven by Artificial Intelligence for Smart-Health Chronic Disease Management.

Sensors (Basel, Switzerland)
One of the health challenges in the 21st century is to rethink approaches to non-communicable disease prevention. A solution is a smart city that implements technology to make health smarter, enables healthcare access, and contributes to all resident...

Integrating AI-driven wearable devices and biometric data into stroke risk assessment: A review of opportunities and challenges.

Clinical neurology and neurosurgery
Stroke is a leading cause of morbidity and mortality worldwide, and early detection of risk factors is critical for prevention and improved outcomes. Traditional stroke risk assessments, relying on sporadic clinical visits, fail to capture dynamic ch...

Sustainable Silk Fibroin Ionic Touch Screens for Flexible Biodegradable Electronics with Integrated AI and IoT Functionality.

Advanced materials (Deerfield Beach, Fla.)
The increasing prevalence of electronic devices has led to a significant rise in electronic waste (e-waste), necessitating the development of sustainable materials for flexible electronics. In this study, silk fibroin ionic touch screen (SFITS) is in...

DS-MS-TCN: Otago Exercises Recognition With a Dual-Scale Multi-Stage Temporal Convolutional Network.

IEEE journal of biomedical and health informatics
The Otago Exercise Program (OEP) represents a crucial rehabilitation initiative tailored for older adults, aimed at enhancing balance and strength. Despite previous efforts utilizing wearable sensors for OEP recognition, existing studies have exhibit...