Man-Machine Systems

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  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. 
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  Keywords of People

  • Nicolelis, Miguel Angelo L., Duke School of Medicine Distinguished Professor in Neuroscience, Neurobiology