AIMC Topic: Gait Analysis

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Parkinson's disease severity clustering based on gait activity from mobile device.

Scientific reports
Parkinson's disease (PD) is a neurodegenerative disorder characterized by motor symptoms, including gait impairments, which significantly affect patient mobility and quality of life. An accurate assessment of the severity of PD is crucial for clinica...

Intelligent Gait Analysis System Enabled by Liquid Metal-Embedded Sponge Triboelectric Sensor Arrays.

ACS applied materials & interfaces
Gait dynamics are pivotal biomarkers for early disease prediction and human health assessment. In this study, we propose an intelligent monitoring system that integrates flexible PDMS/liquid metal sponge triboelectric nanogenerator (PLMFT) arrays wit...

Revealing gait as a murine biomarker of injury, disease, and age with multivariate statistics and machine learning.

Scientific reports
Hundreds of rodent gait studies have been published over the past two decades, according to a PubMed search. Treadmill gait data, for example from the DigiGait system, generates over 30 + spatial and temporal measures. Despite this multi-dimensional ...

Deep Learning-based Gait Recognition and Evaluation of the Wounded.

Disaster medicine and public health preparedness
OBJECTIVES: Remote injury assessment during natural disasters poses major challenges for healthcare providers due to the inaccessibility of disaster sites. This study aimed to explore the feasibility of using artificial intelligence (AI) techniques f...

Gait Analysis in Neurologic Disorders: Methodology, Applications, and Clinical Considerations.

Neurology
Gait and balance disorders are a leading cause of morbidity, mortality, and disability in central and peripheral neurologic disorders. Neurologic gait disorders are classically evaluated with a clinical examination and visual pattern recognition. Gai...

Non-contact, non-visual, multi-person hallway gait monitoring.

Scientific reports
This paper presents a multi-person gait monitoring system designed for efficient operation in cluttered environments. The system demonstrates robust capabilities in tracking multiple closely spaced individuals and accurately extracting the walking sp...

Evidence Based Gait Analysis Interpretation Tools (EB-GAIT) treatment recommendation and outcome prediction models to support decision-making based on clinical gait analysis data.

PloS one
Clinical gait analysis (CGA) has historically relied on clinician experience and judgment, leading to modest, stagnant, and unpredictable outcomes. This paper introduces Evidence-Based Gait Analysis Interpretation Tools (EB-GAIT), a novel framework l...

Integrating deep learning in stride-to-stride muscle activity estimation of young and old adults with wearable inertial measurement units.

Scientific reports
Deep learning has become powerful and yet versatile tool that allows for the extraction of complex patterns from rich datasets. One field that can benefits from this advancement is human gait analysis. Conventional gait analysis requires a specialize...

Electrical grid-independent machine learning-assisted wearable gait analysis device with triboelectric-electromagnetic hybrid energy harvester.

Biosensors & bioelectronics
In this study, an Electrical grid-independent Machine learning-assisted Wearable device for Gait analysis (EMWG) with a ground reaction force sensor is presented. For gait analysis, a multi-layer perceptron is identified as the optimal model among va...

Utility of synthetic musculoskeletal gaits for generalizable healthcare applications.

Nature communications
Deep-neural-network-based artificial intelligence enables quantitative gait analysis with commodity sensors. However, current gait-analysis models are usually specialized for specific clinical populations and sensor settings due to the limited size a...