AIMC Topic: Postural Balance

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A deep learning tool for fully automated measurements of sagittal spinopelvic balance from X-ray images: performance evaluation.

European spine journal : official publication of the European Spine Society, the European Spinal Deformity Society, and the European Section of the Cervical Spine Research Society
PURPOSE: The purpose of this study is to evaluate the performance of a novel deep learning (DL) tool for fully automated measurements of the sagittal spinopelvic balance from X-ray images of the spine in comparison with manual measurements.

The detection of age groups by dynamic gait outcomes using machine learning approaches.

Scientific reports
Prevalence of gait impairments increases with age and is associated with mobility decline, fall risk and loss of independence. For geriatric patients, the risk of having gait disorders is even higher. Consequently, gait assessment in the clinics has ...

Assessment of Balance Control Subsystems by Artificial Intelligence.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
Recent studies have shown that balance performance assessment based on artificial intelligence (AI) is feasible. However, balance control is very complex and requires different subsystems to participate, which have not been evaluated individually yet...

Fall Risk Prediction in Multiple Sclerosis Using Postural Sway Measures: A Machine Learning Approach.

Scientific reports
Numerous postural sway metrics have been shown to be sensitive to balance impairment and fall risk in individuals with MS. Yet, there are no guidelines concerning the most appropriate postural sway metrics to monitor impairment. This investigation im...

A Robust Balance-Control Framework for the Terrain-Blind Bipedal Walking of a Humanoid Robot on Unknown and Uneven Terrain.

Sensors (Basel, Switzerland)
Research on a terrain-blind walking control that can walk stably on unknown and uneven terrain is an important research field for humanoid robots to achieve human-level walking abilities, and it is still a field that needs much improvement. This pape...

Using supervised learning machine algorithm to identify future fallers based on gait patterns: A two-year longitudinal study.

Experimental gerontology
INTRODUCTION: Given their major health consequences in the elderly, identifying people at risk of fall is a major challenge faced by clinicians. A lot of studies have confirmed the relationships between gait parameters and falls incidence. However, a...

A controller for walking derived from how humans recover from perturbations.

Journal of the Royal Society, Interface
Humans can walk without falling despite some external perturbations, but the control mechanisms by which this stability is achieved have not been fully characterized. While numerous walking simulations and robots have been constructed, no full-state ...

Ankle torque steadiness and gait speed after a single session of robot therapy in individuals with chronic hemiparesis: a pilot study.

Topics in stroke rehabilitation
Anklebot therapy has proven to be effective in improving hemiparetic gait. However, neither ankle torque steadiness nor the relationship between changes in force control and functional tasks after therapy with Anklebot were described. To assess whet...

Dynamic neural network approach to targeted balance assessment of individuals with and without neurological disease during non-steady-state locomotion.

Journal of neuroengineering and rehabilitation
BACKGROUND: Clinical balance assessments often rely on functional tasks as a proxy for balance (e.g., Timed Up and Go). In contrast, analyses of balance in research settings incorporate quantitative biomechanical measurements (e.g., whole-body angula...