A Non-linear Dynamics Approach to Classify Gait Signals of Patients with Parkinson's Disease.
Paula Andrea Pérez-ToroJuan Camilo Vásquez-CorreaTomas Arias-VergaraNicanor García-OspinaJuan Rafael Orozco-ArroyaveElmar NöthPublished in: WEA (2) (2018)
Keyphrases
- multiple sclerosis
- medical doctors
- early diagnosis
- patient groups
- cardiovascular disease
- clinical studies
- emergency department
- diagnostic tool
- disease progression
- clinically relevant
- deep brain stimulation
- amyotrophic lateral sclerosis
- signal processing
- signal analysis
- liver disease
- chronic obstructive pulmonary disease
- physiological data
- chronic disease
- cancer patients
- diabetic patients
- disease diagnosis
- clinical data
- medical practitioners
- human gait
- clinical trials
- gait analysis
- infectious disease
- physiological signals
- dynamic model
- human recognition
- joint angles
- brain activity
- high risk
- gait recognition
- wearable sensors
- disease outbreaks
- mild cognitive impairment
- medical treatment
- eeg data
- medical records
- biped robot
- colorectal cancer
- white matter
- lung cancer patients
- computer aided
- x ray