- Rehabilitation Technology
- Prosthetics and Artificial Limbs
- Artificial Intelligence
- Machine Learning
- Reinforcement Learning
- Assistive Robotics
Adaptive rehabilitation technology, Alleviating motor disabilities, Artificial Intelligence, Assistive robotics, Automated assays, Automation, Autonomous robotics, Biomedical signal processing, consumable meat, Control systems, Data analysis, Data science, Diagnostic technology, E. Coli, Engineering design, Environment modelling, Eye tracking, Food adulterants, Functional outcomes, Lab-on-a-chip, Machine intelligence, Machine learning, Meat screening, Metrics, Microfluidics, Motion Capture, Pathogen detection, pathogen screening, Pathogenic E. Coli detection, Pattern analysis, Prediction learning, Prosthetics, Rehab Technology, rehabilitation, Rehabilitation technology, Reinforcement Learning, Robotic arms, Screening, Sensory feedback, Shared control, Software design, Supplementing motor disabilities, Technology development
Adaptive Rehabilitation Technology
- Real-time machine learning for artificial limbs and multi-function powered prostheses.
- Algorithms and adaptive computational techniques that increase patients' ability to customize and control their assistive biomedical devices and environments.
- Prediction learning to improve users' ability to switch between the modes and functions of assistive devices.
- Long-term brain-body-machine and brain-computer interaction.
Intelligent Systems and Interfaces
- Reinforcement learning and artificial intelligence methods for use in complex real-world environments.
- Human-machine interfaces: theoretical and applied methods for communicating between complex distributed systems.
- Human instruction and training of machine learning systems.
- Prediction, representation, and control learning that is grounded in data-dense, real-time sensorimotor experience.
- Continuous-action actor-critic policy gradient algorithms.
Biomedical Pattern Analysis
- Model-free interpretation of real-time, multi-signal human biofeedback (for example, myoelectric signals).
- Outcome measures based on motion capture, eye tracking, and biosignal tracking for prosthetics and other human-machine interfaces.