AIMC Topic: Wearable Electronic Devices

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A Validation Study of Freezing of Gait (FoG) Detection and Machine-Learning-Based FoG Prediction Using Estimated Gait Characteristics with a Wearable Accelerometer.

Sensors (Basel, Switzerland)
One of the most common symptoms observed among most of the Parkinson's disease patients that affects movement pattern and is also related to the risk of fall, is usually termed as "freezing of gait (FoG)". To allow systematic assessment of FoG, objec...

A wearable hip-assist robot reduces the cardiopulmonary metabolic energy expenditure during stair ascent in elderly adults: a pilot cross-sectional study.

BMC geriatrics
BACKGROUND: Stair ascent is one of the most important and challenging activities of daily living to maintain mobility and independence in elderly adults. Recently, various types of wearable walking assist robots have been developed to improve gait fu...

Tactile Sensing Applied to the Universal Gripper Using Conductive Thermoplastic Elastomer.

Soft robotics
There is increasing interest in the use of soft materials in robotic applications ranging from wearable devices to soft grippers. While soft structures provide a number of favorable properties to robotic systems, sensing of large deformable soft stru...

Recognition of Sedentary Behavior by Machine Learning Analysis of Wearable Sensors during Activities of Daily Living for Telemedical Assessment of Cardiovascular Risk.

Sensors (Basel, Switzerland)
With the recent advancement in wearable computing, sensor technologies, and data processing approaches, it is possible to develop smart clothing that integrates sensors into garments. The main objective of this study was to develop the method of auto...

Human Motion Recognition by Textile Sensors Based on Machine Learning Algorithms.

Sensors (Basel, Switzerland)
Wearable sensors for human physiological monitoring have attracted tremendous interest from researchers in recent years. However, most of the research involved simple trials without any significant analytical algorithms. This study provides a way of ...

Multi-stage SVM approach for cardiac arrhythmias detection in short single-lead ECG recorded by a wearable device.

Physiological measurement
OBJECTIVE: Use of wearable ECG devices for arrhythmia screening is limited due to poor signal quality, small number of leads and short records, leading to incorrect recognition of pathological events. This paper introduces a novel approach to classif...

Classifier Personalization for Activity Recognition Using Wrist Accelerometers.

IEEE journal of biomedical and health informatics
Intersubject variability in accelerometer-based activity recognition may significantly affect classification accuracy, limiting a reliable extension of methods to new users. In this paper, we propose an approach for personalizing classification rules...

Smartwatch User Interface Implementation Using CNN-Based Gesture Pattern Recognition.

Sensors (Basel, Switzerland)
In recent years, with an increase in the use of smartwatches among wearable devices, various applications for the device have been developed. However, the realization of a user interface is limited by the size and volume of the smartwatch. This study...

A Wearable Multi-Modal Bio-Sensing System Towards Real-World Applications.

IEEE transactions on bio-medical engineering
Multi-modal bio-sensing has recently been used as effective research tools in affective computing, autism, clinical disorders, and virtual reality among other areas. However, none of the existing bio-sensing systems support multi-modality in a wearab...

Feature Representation and Data Augmentation for Human Activity Classification Based on Wearable IMU Sensor Data Using a Deep LSTM Neural Network.

Sensors (Basel, Switzerland)
Wearable inertial measurement unit (IMU) sensors are powerful enablers for acquisition of motion data. Specifically, in human activity recognition (HAR), IMU sensor data collected from human motion are categorically combined to formulate datasets tha...