Probabilistic Modelling of Gait for Robust Passive Monitoring in Daily Life

Probabilistic Modelling of Gait for Robust Passive Monitoring in Daily Life

Passive monitoring in daily life may provide valuable insights into a person's health throughout the day. Wearable sensor devices play a key role in enabling such monitoring in a non-obtrusive fashion. However, sensor data collected in daily life reflect multiple health and behavior-related fac...

Full description

Bibliographic Details
Main Authors: Badawy, R. (Author), Bloem, B.R (Author), Claes, K. (Author), Evers, L.J.W (Author), Heskes, T.M (Author), Little, M.A (Author), Meinders, M.J (Author), Raykov, Y.P (Author)
Format: Article
Language:English
Published: Institute of Electrical and Electronics Engineers Inc. 2021
Subjects:
acceleration
Activities of Daily Living
Age-matched controls
algorithm
Article
artifact
brain depth stimulation
Clinical diagnosis
controlled study
daily life activity
Daily living activities
Diagnosis
Digital devices
electromagnetism
electronic device
Fourier transform
gait
Gait
gait detection
gait disorder
Gait modelling
health monitoring
human
Humans
machine learning
mathematical model
measurement accuracy
measurement precision
Motor fluctuations
nerve cell network
nervous system parameters
Parkinson disease
Parkinson Disease
Parkinsons disease
passive monitoring
Passive monitoring
principal component analysis
Probabilistic framework
Probabilistic modelling
probabilistic reasoning
sensitivity and specificity
signal noise ratio
steady state
stochastic model
walking
Walking
Wearable Electronic Devices
wearable sensing
Wearable sensors
Online Access:View Fulltext in Publisher

Internet

View Fulltext in Publisher

Similar Items