Standardized measurement of quality of upper limb movement after stroke: consensus-based core recommendations from the second stroke recovery and …
G Kwakkel, EEH van Wegen… - … and neural repair, 2019 - journals.sagepub.com
The second Stroke Recovery and Rehabilitation Roundtable “metrics” task force developed
consensus around the recognized need to add kinematic and kinetic movement …
consensus around the recognized need to add kinematic and kinetic movement …
Machine learning for 3D kinematic analysis of movements in neurorehabilitation
A Arac - Current neurology and neuroscience reports, 2020 - Springer
Abstract Purpose of Review Recent advances in the machine learning field, especially in
deep learning, provide the opportunity for automated, detailed, and unbiased analysis of …
deep learning, provide the opportunity for automated, detailed, and unbiased analysis of …
Assessment of neurological impairment and recovery using statistical models of neurologically healthy behavior
SH Scott, CR Lowrey, IE Brown… - … and Neural Repair, 2023 - journals.sagepub.com
While many areas of medicine have benefited from the development of objective
assessment tools and biomarkers, there have been comparatively few improvements in …
assessment tools and biomarkers, there have been comparatively few improvements in …
Smoothness metric during reach-to-grasp after stroke: part 2. longitudinal association with motor impairment
Background The cause of smoothness deficits as a proxy for quality of movement post stroke
is currently unclear. Previous simulation analyses showed that spectral arc length (SPARC) …
is currently unclear. Previous simulation analyses showed that spectral arc length (SPARC) …
Multivariate functional additive mixed models
Multivariate functional data can be intrinsically multivariate like movement trajectories in 2D
or complementary such as precipitation, temperature and wind speeds over time at a given …
or complementary such as precipitation, temperature and wind speeds over time at a given …
Elastic analysis of irregularly or sparsely sampled curves
We provide statistical analysis methods for samples of curves in two or more dimensions,
where the image, but not the parameterization of the curves, is of interest and suitable …
where the image, but not the parameterization of the curves, is of interest and suitable …
[HTML][HTML] Joint and individual analysis of breast cancer histologic images and genomic covariates
The two main approaches in the study of breast cancer are histopathology (analyzing visual
characteristics of tumors) and genomics. While both histopathology and genomics are …
characteristics of tumors) and genomics. While both histopathology and genomics are …
Functional approach for two way dimension reduction in time series
The rise in data has led to the need for dimension reduction techniques, especially in the
area of non-scalar variables, including time series, natural language processing, and …
area of non-scalar variables, including time series, natural language processing, and …
Curvature and Torsion estimation of 3D functional data: A geometric approach to build the mean shape under the Frenet Serret framework
The analysis of curves has been routinely dealt with using tools from functional data
analysis. However its extension to multi-dimensional curves poses a new challenge due to …
analysis. However its extension to multi-dimensional curves poses a new challenge due to …
Functional additive models on manifolds of planar shapes and forms
The “shape” of a planar curve and/or landmark configuration is considered its equivalence
class under translation, rotation, and scaling, its “form” its equivalence class under …
class under translation, rotation, and scaling, its “form” its equivalence class under …