AIMC Topic: Gait

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Leather-Based Shoe Soles for Real-Time Gait Recognition and Automatic Remote Assistance Using Machine Learning.

ACS applied materials & interfaces
Real-time monitoring of gait characteristics is crucial for applications in health monitoring, patient rehabilitation feedback, and telemedicine. However, the effective and stable acquisition and automatic analysis of gait information remain signific...

Unsupervised learning for real-time and continuous gait phase detection.

PloS one
Individuals with lower limb impairment after a stroke or spinal cord injury require rehabilitation, but traditional methods can be challenging for both patients and therapists. Robotic systems have been developed to help; however, they currently cann...

A Plantar Pressure Detection and Gait Analysis System Based on Flexible Triboelectric Pressure Sensor Array and Deep Learning.

Small (Weinheim an der Bergstrasse, Germany)
Gait detection is essential for the assessment of human health status and early diagnosis of diseases. The current gait analysis systems are bulky, limited in the scope of use, and cause interference with the movement of the measured person. Hence, i...

Effects of interval treadmill training on spatiotemporal parameters in children with cerebral palsy: A machine learning approach.

Journal of biomechanics
Quantifying individualized rehabilitation responses and optimizing therapy for each person is challenging. For interventions like treadmill training, there are multiple parameters, such as speed or incline, that can be adjusted throughout sessions. T...

Artificial intelligence-assisted oculo-gait measurements for cognitive impairment in cerebral small vessel disease.

Alzheimer's & dementia : the journal of the Alzheimer's Association
INTRODUCTION: Oculomotor and gait dysfunctions are closely associated with cognition. However, oculo-gait patterns and their correlation with cognition in cerebral small vessel disease (CSVD) remain unclear.

Effectiveness of robotic rehabilitation for gait and balance in people with multiple sclerosis: a systematic review.

Journal of neurology
This review investigated the effectiveness of robotic-assisted gait training (RAGT) in improving gait and balance performance in adults with multiple sclerosis (MS). Databases and registers were searched from inception to December 2023 to identify ra...

Convolutional neural network based detection of early stage Parkinson's disease using the six minute walk test.

Scientific reports
The heterogeneity of Parkinson's disease (PD) presents considerable challenges for accurate diagnosis, particularly during early-stage disease, when the symptoms may be extremely subtle. This study aimed to assess the accuracy of a convolutional neur...

Estimating intra- and inter-subject oxygen consumption in outdoor human gait using multiple neural network approaches.

PloS one
Oxygen consumption ([Formula: see text]) is an important measure for exercise test, such as walking and running, that can be measured outdoors using portable spirometers or metabolic analyzers. However, these devices are not feasible for regular use ...

Multifunctional Human-Computer Interaction System Based on Deep Learning-Assisted Strain Sensing Array.

ACS applied materials & interfaces
Continuous and reliable monitoring of gait is crucial for health monitoring, such as postoperative recovery of bone joint surgery and early diagnosis of disease. However, existing gait analysis systems often suffer from large volumes and the requirem...

Virtual Obstacle Avoidance Strategy: Navigating through a Complex Environment While Interacting with Virtual and Physical Elements.

Sensors (Basel, Switzerland)
Robotic walking devices can be used for intensive exercises to enhance gait rehabilitation therapies. Mixed Reality (MR) techniques may improve engagement through immersive and interactive environments. This article introduces an MR-based multimodal ...