AIMC Topic: Wearable Electronic Devices

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Zero-Biased Bionic Fingertip E-Skin with Multimodal Tactile Perception and Artificial Intelligence for Augmented Touch Awareness.

Advanced materials (Deerfield Beach, Fla.)
Electronic skins (E-Skins) are crucial for future robotics and wearable devices to interact with and perceive the real world. Prior research faces challenges in achieving comprehensive tactile perception and versatile functionality while keeping syst...

Automated remote sleep monitoring needs uncertainty quantification.

Journal of sleep research
Wearable electroencephalography devices emerge as a cost-effective and ergonomic alternative to gold-standard polysomnography, paving the way for better health monitoring and sleep disorder screening. Machine learning allows to automate sleep stage c...

An Explainable Deep Learning Approach for Stress Detection in Wearable Sensor Measurements.

Sensors (Basel, Switzerland)
Stress has various impacts on the health of human beings. Recent success in wearable sensor development, combined with advancements in deep learning to automatically detect features from raw data, opens several interesting applications related to det...

A Novel Unsupervised Machine Learning Approach to Assess Postural Dynamics in Euthymic Bipolar Disorder.

IEEE journal of biomedical and health informatics
Bipolar disorder (BD) is a mood disorder with different phases alternating between euthymia, manic or hypomanic episodes, and depressive episodes. While motor abnormalities are commonly seen during depressive or manic episodes, not much attention has...

Machine learning-enabled detection of attention-deficit/hyperactivity disorder with multimodal physiological data: a case-control study.

BMC psychiatry
BACKGROUND: Attention-Deficit/Hyperactivity Disorder (ADHD) is a multifaceted neurodevelopmental psychiatric condition that typically emerges during childhood but often persists into adulthood, significantly impacting individuals' functioning, relati...

An Effective Deep Learning Framework for Fall Detection: Model Development and Study Design.

Journal of medical Internet research
BACKGROUND: Fall detection is of great significance in safeguarding human health. By monitoring the motion data, a fall detection system (FDS) can detect a fall accident. Recently, wearable sensors-based FDSs have become the mainstream of research, w...

Predicting Knee Joint Contact Force Peaks During Gait Using a Video Camera or Wearable Sensors.

Annals of biomedical engineering
PURPOSE: Estimating loading of the knee joint may be helpful in managing degenerative joint diseases. Contemporary methods to estimate loading involve calculating knee joint contact forces using musculoskeletal modeling and simulation from motion cap...

Exploring the Potential of a Smart Ring to Predict Postoperative Pain Outcomes in Orthopedic Surgery Patients.

Sensors (Basel, Switzerland)
Poor pain alleviation remains a problem following orthopedic surgery, leading to prolonged recovery time, increased morbidity, and prolonged opioid use after hospitalization. Wearable device data, collected during postsurgical recovery, may help amel...

Identification of footstrike pattern using accelerometry and machine learning.

Journal of biomechanics
Recent reports have suggested that there may be a relationship between footstrike pattern and overuse injury incidence and type. With the recent increase in wearable sensors, it is important to identify paradigms where the footstrike pattern can be d...

Conceptualization of Cloud-Based Motion Analysis and Navigation for Wearable Robotic Applications.

Sensors (Basel, Switzerland)
The behavior of pedestrians in a non-constrained environment is difficult to predict. In wearable robotics, this poses a challenge, since devices like lower-limb exoskeletons and active orthoses need to support different walking activities, including...