title: Assessment of brain-machine interfaces from the perspective of people with paralysis.
abstract: OBJECTIVE
  One of the main goals of brain-machine interface (BMI) research is to restore function to people with paralysis. Currently, multiple BMI design features are being investigated, based on various input modalities (externally applied and surgically implantable sensors) and output modalities (e.g. control of computer systems, prosthetic arms, and functional electrical stimulation systems). While these technologies may eventually provide some level of benefit, they each carry associated burdens for end-users. We sought to assess the attitudes of people with paralysis toward using various technologies to achieve particular benefits, given the burdens currently associated with the use of each system.
  
  
  METHODS
  We designed and distributed a technology survey to determine the level of benefit necessary for people with tetraplegia due to spinal cord injury to consider using different technologies, given the burdens currently associated with them. The survey queried user preferences for 8 BMI technologies including electroencephalography, electrocorticography, and intracortical microelectrode arrays, as well as a commercially available eye tracking system for comparison. Participants used a 5-point scale to rate their likelihood to adopt these technologies for 13 potential control capabilities.
  
  
  RESULTS
  Survey respondents were most likely to adopt BMI technology to restore some of their natural upper extremity function, including restoration of hand grasp and/or some degree of natural arm movement. High speed typing and control of a fast robot arm were also of interest to this population. Surgically implanted wireless technologies were twice as 'likely' to be adopted as their wired equivalents.
  
  
  CONCLUSIONS
  Assessing end-user preferences is an essential prerequisite to the design and implementation of any assistive technology. The results of this survey suggest that people with tetraplegia would adopt an unobtrusive, autonomous BMI system for both restoration of upper extremity function and control of external devices such as communication interfaces.
authors.affiliation: Department of Neurosurgery, Stanford University, Stanford, CA, USA.
authors.forename: Christine H
authors.initials: CH
authors.lastname: Blabe
authors.forename: Vikash
authors.initials: V
authors.lastname: Gilja
authors.forename: Cindy A
authors.initials: CA
authors.lastname: Chestek
authors.forename: Krishna V
authors.initials: KV
authors.lastname: Shenoy
authors.forename: Kim D
authors.initials: KD
authors.lastname: Anderson
authors.forename: Jaimie M
authors.initials: JM
authors.lastname: Henderson
mesh_terms: D000293:Adolescent; D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D062207:Brain-Computer Interfaces; D003143:Communication Devices for People with Disabilities / Q000523:psychology / Q000706:statistics & numerical data*; D004569:Electroencephalography / Q000523:psychology / Q000706:statistics & numerical data*; D005260:Female; D019538:Health Care Surveys; D006801:Humans; D008297:Male; D008875:Middle Aged; D020380:Needs Assessment; D057240:Patient Preference / Q000523:psychology / Q000706:statistics & numerical data*; D011782:Quadriplegia / Q000453:epidemiology / Q000523:psychology / Q000534:rehabilitation*; D012371:Robotics / Q000706:statistics & numerical data*; D013672:Technology; D014481:United States / Q000453:epidemiology; D055815:Young Adult