AIMC Topic: Walking

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EMG-based prediction of step direction for a better control of lower limb wearable devices.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVES: Lower-limb wearable devices can significantly improve the quality of life of subjects suffering from debilitating conditions, such as amputations, neurodegenerative disorders, and stroke-related impairments. Current control...

Wearable Robot Design Optimization Using Closed-Form Human-Robot Dynamic Interaction Model.

Sensors (Basel, Switzerland)
Wearable robots are emerging as a viable and effective solution for assisting and enabling people who suffer from balance and mobility disorders. Virtual prototyping is a powerful tool to design robots, preventing the costly iterative physical protot...

Enhancing fall risk assessment: instrumenting vision with deep learning during walks.

Journal of neuroengineering and rehabilitation
BACKGROUND: Falls are common in a range of clinical cohorts, where routine risk assessment often comprises subjective visual observation only. Typically, observational assessment involves evaluation of an individual's gait during scripted walking pro...

Improving trunk posture control in children with CP through a cable-driven robotic hippotherapy: A randomized controlled feasibility study.

Gait & posture
BACKGROUND: Many children with cerebral palsy (CP) show impairments in trunk posture control, one crucial factor contributing to impairments in gait and arm manipulation.

Self-Supervised Learning Improves Accuracy and Data Efficiency for IMU-Based Ground Reaction Force Estimation.

IEEE transactions on bio-medical engineering
OBJECTIVE: Recent deep learning techniques hold promise to enable IMU-driven kinetic assessment; however, they require large extents of ground reaction force (GRF) data to serve as labels for supervised model training. We thus propose using existing ...

Exploring the Impact of the Class on In-the-Wild Human Activity Recognition.

Sensors (Basel, Switzerland)
Monitoring activities of daily living (ADLs) plays an important role in measuring and responding to a person's ability to manage their basic physical needs. Effective recognition systems for monitoring ADLs must successfully recognize naturalistic ac...

Real-Time Tracking Data and Machine Learning Approaches for Mapping Pedestrian Walking Behavior: A Case Study at the University of Moratuwa.

Sensors (Basel, Switzerland)
The growing urban population and traffic congestion underline the importance of building pedestrian-friendly environments to encourage walking as a preferred mode of transportation. However, a major challenge remains, which is the absence of such ped...

Experiment-free exoskeleton assistance via learning in simulation.

Nature
Exoskeletons have enormous potential to improve human locomotive performance. However, their development and broad dissemination are limited by the requirement for lengthy human tests and handcrafted control laws. Here we show an experiment-free meth...

AiCarePWP: Deep learning-based novel research for Freezing of Gait forecasting in Parkinson.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVES: Episodes of Freezing of Gait (FoG) are among the most debilitating motor symptoms of Parkinson's Disease (PD), leading to falls and significantly impacting patients' quality of life. Accurate assessment of FoG by neurologis...

Prediction of Achilles Tendon Force During Common Motor Tasks From Markerless Video.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
Remodeling of the Achilles tendon (AT) is partly driven by its mechanical environment. AT force can be estimated with neuromusculoskeletal (NMSK) modeling; however, the complex experimental setup required to perform the analyses confines use to the l...