Predicting multiple sclerosis from gait dynamics using an instrumented treadmill: a machine learning approach
Objective: Multiple Sclerosis (MS) is a neurological condition which widely affects people 50-
60 years of age. While clinical presentations of MS are highly heterogeneous, mobility …
60 years of age. While clinical presentations of MS are highly heterogeneous, mobility …
Deep learning for multiple sclerosis differentiation using multi-stride dynamics in gait
Objective: Multiple sclerosis (MS) is a chronic neurological condition of the central nervous
system leading to various physical, mental and psychiatric complexities. Mobility limitations …
system leading to various physical, mental and psychiatric complexities. Mobility limitations …
Using machine learning algorithms for identifying gait parameters suitable to evaluate subtle changes in gait in people with multiple sclerosis
K Trentzsch, P Schumann, G Śliwiński, P Bartscht… - Brain Sciences, 2021 - mdpi.com
In multiple sclerosis (MS), gait impairment is one of the most prominent symptoms. For a
sensitive assessment of pathological gait patterns, a comprehensive analysis and …
sensitive assessment of pathological gait patterns, a comprehensive analysis and …
Machine learning classification of multiple sclerosis patients based on raw data from an instrumented walkway
W Hu, O Combden, X Jiang, S Buragadda… - BioMedical Engineering …, 2022 - Springer
Background Using embedded sensors, instrumented walkways provide clinicians with
important information regarding gait disturbances. However, because raw data are …
important information regarding gait disturbances. However, because raw data are …
A multifactorial model of multiple sclerosis gait and its changes across different disability levels
Objective: Mobility assessment is critical in the clinical management of people with Multiple
Sclerosis (pwMS). Instrumented gait analysis provides a plethora of metrics for quantifying …
Sclerosis (pwMS). Instrumented gait analysis provides a plethora of metrics for quantifying …
A vision-based framework for predicting multiple sclerosis and Parkinson's disease gait dysfunctions—A deep learning approach
This study examined the effectiveness of av ision-based framework for m ultiple s clerosis
(MS) and Parkinson's disease (PD) gait dysfunction prediction. We collected gait video data …
(MS) and Parkinson's disease (PD) gait dysfunction prediction. We collected gait video data …
Remote monitoring in the home validates clinical gait measures for multiple sclerosis
A Supratak, G Datta, AR Gafson, R Nicholas… - Frontiers in …, 2018 - frontiersin.org
Background: The timed 25-foot walk (T25FW) is widely used as a clinic performance
measure, but has yet to be directly validated against gait speed in the home environment …
measure, but has yet to be directly validated against gait speed in the home environment …
Relationship between gait variables and domains of neurologic dysfunction in multiple sclerosis using six-minute walk test
A Qureshi, M Brandt-Pearce… - 2016 38th Annual …, 2016 - ieeexplore.ieee.org
Most multiple sclerosis (MS) patients eventually suffer from mobility impairment, and thus it is
critical that walking disability in MS be accurately assessed. The six-minute walk test …
critical that walking disability in MS be accurately assessed. The six-minute walk test …
A machine learning approach for gait speed estimation using skin-mounted wearable sensors: From healthy controls to individuals with multiple sclerosis
Gait speed is a powerful clinical marker for mobility impairment in patients suffering from
neurological disorders. However, assessment of gait speed in coordination with delivery of …
neurological disorders. However, assessment of gait speed in coordination with delivery of …
Wearables and deep learning classify fall risk from gait in multiple sclerosis
BM Meyer, LJ Tulipani, RD Gurchiek… - IEEE journal of …, 2020 - ieeexplore.ieee.org
Falls are a significant problem for persons with multiple sclerosis (PwMS). Yet fall prevention
interventions are not often prescribed until after a fall has been reported to a healthcare …
interventions are not often prescribed until after a fall has been reported to a healthcare …