Multi-model long short-term memory network for gait recognition using window-based data segment
Inertial Measurement Units (IMUs)-based gait analysis is a promising and attractive
approach for user recognition. Recently, the adoption of deep learning techniques has …
approach for user recognition. Recently, the adoption of deep learning techniques has …
A lightweight attention-based CNN model for efficient gait recognition with wearable IMU sensors
Wearable sensors-based gait recognition is an effective method to recognize people's
identity by recognizing the unique way they walk. Recently, the adoption of deep learning …
identity by recognizing the unique way they walk. Recently, the adoption of deep learning …
Gait recognition with wearable sensors using modified residual block-based lightweight cnn
Gait recognition with wearable sensors is an effective approach to identifying people by
recognizing their distinctive walking patterns. Deep learning-based networks have recently …
recognizing their distinctive walking patterns. Deep learning-based networks have recently …
Hidden Markov Model based stride segmentation on unsupervised free-living gait data in Parkinson's disease patients
Background To objectively assess a patient's gait, a robust identification of stride borders is
one of the first steps in inertial sensor-based mobile gait analysis pipelines. While many …
one of the first steps in inertial sensor-based mobile gait analysis pipelines. While many …
Ecological validity of a deep learning algorithm to detect gait events from real-life walking bouts in mobility-limiting diseases
Introduction The clinical assessment of mobility, and walking specifically, is still mainly
based on functional tests that lack ecological validity. Thanks to inertial measurement units …
based on functional tests that lack ecological validity. Thanks to inertial measurement units …
Analyzing gait symmetry with automatically synchronized wearable sensors in daily life
T Steinmetzer, S Wilberg, I Bönninger… - Microprocessors and …, 2020 - Elsevier
Gait deviations such as asymmetry are one of the characteristic symptoms of motor
dysfunctions that contribute to the risk of falls. Our objective is to measure gait abnormalities …
dysfunctions that contribute to the risk of falls. Our objective is to measure gait abnormalities …
Impact of depression on gait variability in Parkinson's disease
Objective The goal of this study was to analyze how depression associated with Parkinson's
disease (PD) affected gait variability in these patients using a dual-task paradigm …
disease (PD) affected gait variability in these patients using a dual-task paradigm …
An inertial sensor-based gait analysis pipeline for the assessment of real-world stair ambulation parameters
Climbing stairs is a fundamental part of daily life, adding additional demands on the postural
control system compared to level walking. Although real-world gait analysis studies likely …
control system compared to level walking. Although real-world gait analysis studies likely …
Comparison of algorithms and classifiers for stride detection using wearables
T Steinmetzer, I Bönninger, M Reckhardt… - Neural Computing and …, 2020 - Springer
Sensor-based systems for diagnosis or therapy support of motor dysfunctions need
methodologies of automatically stride detection from movement sequences. In this proposal …
methodologies of automatically stride detection from movement sequences. In this proposal …
Adaptive treadmill-assisted virtual reality-based gait rehabilitation for post-stroke physical reconditioning—A feasibility study in low-resource settings
Objectives: Individuals with chronic stroke suffer from heterogeneous functional limitations,
including cardiovascular dysfunction and gait disorders (associated with increased energy …
including cardiovascular dysfunction and gait disorders (associated with increased energy …