Wearable Monitoring and Interpretable Machine Learning Can Objectively Track Progression in Patients during Cardiac Rehabilitation.
Hélène De CannièreFederico CorradiChristophe SmeetsMelanie SchouttetenCarolina VaronChris Van HoofSabine Van HuffelWillemijn GroenendaalPieter M. VandervoortPublished in: Sensors (2020)
Keyphrases
- wearable sensors
- machine learning
- health monitoring
- continuous monitoring
- activity recognition
- physical activity
- cardiac surgery
- vital signs
- activities of daily living
- intensive care unit
- monitoring system
- neurological disorders
- intensive care
- heart disease
- human activities
- intensive care units
- normal subjects
- blood glucose
- medical care
- human computer interaction
- real time
- acute coronary syndrome
- critical care
- ground truth
- myocardial infarction
- patient specific
- sensor data
- cardiovascular disease
- data mining
- learning algorithm
- spinal cord injury
- ambient assisted living
- healthy volunteers
- ambient intelligence
- smart home
- heart rate
- fall detection
- gesture recognition
- clinically relevant
- health status
- decision trees
- daily activities
- augmented reality
- medical data
- wireless sensor networks
- disease progression