Automated Multicohort Mobility Assessment with an Instrumented L-test (iL-test)

IEEE Transactions on Neural Systems and Rehabilitation Engineering, Journal Year: 2025, Volume and Issue: 33, P. 717 - 727

Published: Jan. 1, 2025

The L-test is a performance-based measure to assess balance and mobility. Currently, the primary outcome from this test time required finish it. In study we present instrumented (iL-test), an wherein mobility evaluated by means of wearable inertial sensor worn at lower back. We analyzed data 113 people across seven cohorts: healthy adults, chronic obstructive pulmonary disease, multiple sclerosis, congestive heart failure, Parkinson's proximal femoral fracture, transfemoral amputation. iL-test automatic segmentation was validated using stereophotogrammetry. Univariate multivariate analyses were performed on 164 kinematic features derived signals identify distinct patterns different cohorts. accurately recognized segmented activities during for all cohorts (technical validity). A random forest classifier revealed that fracture amputation induced significantly compared with AUC values 0.89 0.99, respectively. Strong correlations found between clinical scores in amputation, consistent decreased movement ranges smoothness increasing disease severity. Furthermore, 90° 180° turns be important contributors differentiation amongst cohorts, underscoring need evaluate turn degrees directions. This emphasizes potential deliver automated assessment wide range conditions, indicating prospective avenue improved and, eventually, more informed healthcare interventions.

Language: Английский

Revisiting sensor-based intelligent fall risk assessment for older people: A systematic review

Engineering Applications of Artificial Intelligence, Journal Year: 2025, Volume and Issue: 144, P. 110176 - 110176

Published: Feb. 5, 2025

A machine learning approach to evaluate the impact of virtual balance/cognitive training on fall risk in older women

Frontiers in Computational Neuroscience, Journal Year: 2024, Volume and Issue: 18

Published: May 14, 2024

Novel technologies based on virtual reality (VR) are creating attractive environments with high ecological value, used both in basic/clinical neuroscience and modern medical practice. The study aimed to evaluate the effects of VR-based training an elderly population.

Language: Английский