Machine learning in human movement biomechanics: Best practices, common pitfalls, and new opportunities
Traditional laboratory experiments, rehabilitation clinics, and wearable sensors offer
biomechanists a wealth of data on healthy and pathological movement. To harness the …
biomechanists a wealth of data on healthy and pathological movement. To harness the …
[HTML][HTML] A comprehensive survey on the detection, classification, and challenges of neurological disorders
Simple Summary This study represents a resourceful review article that can deliver
resources on neurological diseases and their implemented classification algorithms to …
resources on neurological diseases and their implemented classification algorithms to …
A support vector machine-based ensemble algorithm for breast cancer diagnosis
This research studies a support vector machine (SVM)-based ensemble learning algorithm
for breast cancer diagnosis. Illness diagnosis plays a critical role in designating treatment …
for breast cancer diagnosis. Illness diagnosis plays a critical role in designating treatment …
IMU-based classification of Parkinson's disease from gait: A sensitivity analysis on sensor location and feature selection
Inertial measurement units (IMUs) have a long-lasting popularity in a variety of industrial
applications from navigation systems to guidance and robotics. Their use in clinical practice …
applications from navigation systems to guidance and robotics. Their use in clinical practice …
A new rolling bearing fault diagnosis method based on multiscale permutation entropy and improved support vector machine based binary tree
Y Li, M Xu, Y Wei, W Huang - Measurement, 2016 - Elsevier
A new bearing vibration feature extraction method based on multiscale permutation entropy
(MPE) and improved support vector machine based binary tree (ISVM-BT) is put forward in …
(MPE) and improved support vector machine based binary tree (ISVM-BT) is put forward in …
Classification of Parkinson's disease gait using spatial-temporal gait features
Quantitative gait assessment is important in diagnosis and management of Parkinson's
disease (PD); however, gait characteristics of a cohort are dispersed by patient physical …
disease (PD); however, gait characteristics of a cohort are dispersed by patient physical …
[HTML][HTML] Analysis of big data in gait biomechanics: Current trends and future directions
The increasing amount of data in biomechanics research has greatly increased the
importance of developing advanced multivariate analysis and machine learning techniques …
importance of developing advanced multivariate analysis and machine learning techniques …
A fault diagnosis scheme for rolling bearing based on local mean decomposition and improved multiscale fuzzy entropy
Y Li, M Xu, R Wang, W Huang - Journal of Sound and Vibration, 2016 - Elsevier
This paper presents a new rolling bearing fault diagnosis method based on local mean
decomposition (LMD), improved multiscale fuzzy entropy (IMFE), Laplacian score (LS) and …
decomposition (LMD), improved multiscale fuzzy entropy (IMFE), Laplacian score (LS) and …
Automatic identification of respiratory diseases from stethoscopic lung sound signals using ensemble classifiers
This paper investigates the application of different homogeneous ensemble learning
methods to perform multi-class classification of respiratory diseases. The case sample …
methods to perform multi-class classification of respiratory diseases. The case sample …
A survey on gait recognition via wearable sensors
MD Marsico, A Mecca - ACM Computing Surveys (CSUR), 2019 - dl.acm.org
Gait is a biometric trait that can allow user authentication, though it is classified as a “soft”
one due to a certain lack in permanence and to sensibility to specific conditions. The earliest …
one due to a certain lack in permanence and to sensibility to specific conditions. The earliest …