Subject Areas on Research
- Active tactile exploration using a brain-machine-brain interface.
- Auditory decision aiding in supervisory control of multiple unmanned aerial vehicles.
- Comparing the performance of expert user heuristics and an integer linear program in aircraft carrier deck operations.
- Decision-level fusion of EEG and pupil features for single-trial visual detection analysis.
- Future developments in brain-machine interface research.
- Human evolution is biological & technological evolution.
- Influencing Trust for Human-Automation Collaborative Scheduling of Multiple Unmanned Vehicles.
- Integrating ethics in design through the value-sensitive design approach.
- Optimizing the P300-based brain-computer interface: current status, limitations and future directions.
- Optimizing the automatic selection of spike detection thresholds using a multiple of the noise level.
- Physical strain and urgent need for ergonomic training among gynecologic oncologists who perform minimally invasive surgery.
- Position-Independent Decoding of Movement Intention for Proportional Myoelectric Interfaces.
- Study of on-line adaptive discriminant analysis for EEG-based brain computer interfaces.
- The muscle activation method: an approach to impedance control of brain-machine interfaces through a musculoskeletal model of the arm.
- Trust in automation: integrating empirical evidence on factors that influence trust.
Keywords of People
- Nicolelis, Miguel Angelo L., Duke School of Medicine Distinguished Professor in Neuroscience, Neurobiology