IEEE journal of biomedical and health informatics
Dec 31, 2019
OBJECTIVE: This study aims to understand breathing patterns during daily activities by developing a wearable respiratory and activity monitoring (WRAM) system.
Recent studies have reported the application of artificial neural network (ANN) techniques on data of inertial measurement units (IMUs) to predict ground reaction forces (GRFs), which could serve as quantitative indicators of sports performance or re...
Advanced materials (Deerfield Beach, Fla.)
Dec 16, 2019
Inspired by the human somatosensory system, pressure applied to multiple pressure sensors is received in parallel and combined into a representative signal pattern, which is subsequently processed using machine learning. The pressure signals are comb...
IEEE journal of biomedical and health informatics
Dec 11, 2019
Fall risk assessment is essential to predict and prevent falls in geriatric populations, especially patients with life-long conditions like neurological disorders. Inertial sensor-based pervasive gait analysis systems have become viable means to faci...
Early diagnosis of Parkinson's diseases (PD) is challenging; applying machine learning (ML) models to gait characteristics may support the classification process. Comparing performance of ML models used in various studies can be problematic due to di...
Continuous kinematic monitoring of runners is crucial to inform runners of inappropriate running habits. Motion capture systems are the gold standard for gait analysis, but they are spatially limited to laboratories. Recently, wearable sensors have g...
IEEE transactions on biomedical circuits and systems
Nov 28, 2019
Artificial neural network (ANN) and its variants are favored algorithm in designing cardiac arrhythmia classifier (CAC) for its high accuracy. However, the implementation of ultralow power ANN-CAC is challenging due to the intensive computations. Mor...
Wearable sensors have the potential to enable comprehensive patient characterization and optimized clinical intervention. Critical to realizing this vision is accurate estimation of biomechanical time-series in daily-life, including joint, segment, a...
Human voice recognition systems (VRSs) are a prerequisite for voice-controlled human-machine interfaces (HMIs). In order to avoid interference from unexpected background noises, skin-attachable VRSs are proposed to directly detect physiological mecha...
Falls have become a relevant public health issue due to their high prevalence and negative effects in elderly people. Wearable fall detector devices allow the implementation of continuous and ubiquitous monitoring systems. The effectiveness for analy...