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@ARTICLE{Bourhis2001,
  author = {Bourhis, G. and Horn, O. and Habert, O. and Pruski, A.},
  title = {An autonomous vehicle for people with motor disabilities},
  journal = {Robotics Automation Magazine, {IEEE}},
  year = {2001},
  volume = {8},
  pages = {20 -28},
  number = {1},
  doi = {10.1109/100.924353},
  issn = {1070-9932},
  keywords = {VAHM;autonomous vehicle;handicapped aids;hardware;localisation;navigation;obstacle
	avoidance;path planning;smart wheelchair;software;computerised navigation;handicapped
	aids;intelligent control;path planning;position control;vehicles;},
  owner = {Radhika},
  timestamp = {2011.08.15}
}

@INPROCEEDINGS{Carlson2010,
  author = {Carlson, T. and Demiris, Y.},
  title = {Increasing robotic wheelchair safety with collaborative control:
	Evidence from secondary task experiments},
  booktitle = {Robotics and Automation ({ICRA}), 2010 {IEEE} International Conference
	on},
  year = {2010},
  pages = {5582 -5587},
  abstract = {Powered wheelchairs play a vital role in bringing independence to
	the severely mobility-impaired. Our robotic wheelchair aims to assist
	users in driving safely, without undermining their capabilities or
	curtailing the natural development of their skills. An important
	research question is to determine the conditions under which shared
	control is most beneficial. In this paper, we describe an experiment,
	where a distracting secondary task caused the majority of participants
	to crash the wheelchair when driving without assistance. However,
	when they were assisted by our collaborative controller, not only
	did they drive safely, but they also increased their performance
	in the secondary task. We demonstrate that a degree of shared control
	is beneficial even to proficient drivers under certain circumstances,
	for instance when they are under a heightened workload.},
  doi = {10.1109/ROBOT.2010.5509257},
  issn = {1050-4729},
  keywords = {collaborative control;mobility impaired;powered wheelchairs;robotic
	wheelchair safety;secondary task experiments;handicapped aids;mobile
	robots;safety;wheelchairs;},
  owner = {Radhika},
  timestamp = {2011.02.27}
}

@INPROCEEDINGS{Carlson2008,
  author = {Carlson, T. and Demiris, Y.},
  title = {Human-wheelchair collaboration through prediction of intention and
	adaptive assistance},
  booktitle = {Robotics and Automation, 2008. {ICRA} 2008. {IEEE} International
	Conference on},
  year = {2008},
  pages = {3926 -3931},
  abstract = {Powered wheelchair users want to be active drivers, not just passengers.
	However, in some situations (varying from person to person), they
	may require assistance; hence, research is being carried out into
	the development of 'smart' wheelchairs. Predominantly, this research
	has been derived from the field of mobile robotics, focussing on
	creating autonomous systems, which unfortunately tend to treat the
	human as little more than a precious piece of cargo. Instead, the
	design should be based around each individual user's abilities and
	desires, maximising the amount of control they are given. In this
	paper, we look at how collaborative control techniques can be used
	to achieve this, offering the user help, as and when it is required.
	We then evaluate the effects of this collaboration, which is built
	by predicting user intentions and responding to these predictions
	with adaptable levels of assistance.},
  doi = {10.1109/ROBOT.2008.4543814},
  issn = {1050-4729},
  keywords = {adaptive assistance;autonomous systems;collaborative control;human-wheelchair
	collaboration;intention prediction;mobile robotics;smart wheelchairs;handicapped
	aids;mobile robots;}
}

@ARTICLE{Cooper1995,
  author = {Cooper, R.A.},
  title = {Intelligent control of power wheelchairs},
  journal = {Engineering in Medicine and Biology Magazine, {IEEE}},
  year = {1995},
  volume = {14},
  pages = {423 -431},
  number = {4},
  doi = {10.1109/51.395325},
  issn = {0739-5175},
  keywords = {assistive technology;dynamic environment;electromagnetic interference
	related issues;fault-tolerant control;human/machine interaction research;improved
	mobility;independent mobility;independent self-guided mobility;motor
	control;power wheelchairs intelligent control;safe effective mobility;shared
	control;tuneable controllers;biocontrol;electric vehicles;handicapped
	aids;intelligent control;reviews;},
  owner = {Radhika},
  timestamp = {2011.08.13}
}

@INCOLLECTION{Cooper2003,
  author = {Cooper, R.A. and Boninger, M.L. and Cooper, R. and Thorman, T},
  title = {Wheelchairs and Seating},
  booktitle = {Spinal cord medicine: principles and practice},
  publisher = {Demos Medical Publishing, Inc.},
  year = {2003},
  editor = {Lin, V.W.},
  pages = {635-654},
  address = {New York},
  abstract = {Power wheelchair controllers become more sophisticated as motor control
	and human/machine interaction research progresses. The result of
	this increasing sophistication is that more people are provided with
	independent mobility. The challenge for engineering is to provide
	safe and effective mobility in a dynamic environment. Fortunately,
	many of the control methods outlined in here make that goal attainable.
	Tuneable controllers have had a significant impact, but they only
	allude to the possibilities for improved mobility. Shared control
	proves promising for expanding the number and variety of power wheelchair
	users. Integrated control will increase the independence of power
	wheelchair users in all realms of assistive technology. Fault-tolerant
	control can guide one towards safer and more reliable power wheelchairs.
	Fault-tolerant controllers may also be a cost effective solution
	to many electromagnetic interference related issues. Through thoughtful
	research and design, power wheelchair control will progress along
	safe and effective pathways towards providing users independent and
	self-guided mobility},
  owner = {Radhika},
  timestamp = {2011.08.13}
}

@MISC{Health2005,
  author = {{Department of Health}},
  howpublished = {The National Service Framework for long term conditions. Annex 4
	- Incidence and prevalence of some neurological conditions in the
	UK},
  year = {2005},
  citeseerurl = {http://www.dh.gov.uk/prod_consum_dh/groups/dh_digitalassets/@dh/@en/documents/digitalasset/dh_4106449.pdf},
  owner = {Radhika},
  timestamp = {2011.08.13}
}

@ARTICLE{Ding2005,
  author = {Ding, D. and Cooper, R.A.},
  title = {Electric powered wheelchairs},
  journal = {Control Systems, IEEE},
  year = {2005},
  volume = {25},
  pages = { 22 - 34},
  number = {2},
  abstract = {The purpose of this review is to convey the depth and breadth of the
	research conducted on electric-powered wheelchair (EPW) control technology
	as well as provide insights into future directions. We review the
	concepts and previous work on velocity control, traction control,
	suspension control, stability control, stair-climbing wheelchairs,
	and wheelchair navigation. The information gathered in this study
	is intended to promote awareness of the status of contemporary powered
	wheelchair control technology and increase the functional mobility
	of people who use EPWs.},
  doi = {10.1109/MCS.2005.1411382},
  issn = {1066-033X},
  keywords = { EPW control technology; electric powered wheelchairs; extremity impairments;
	functional mobility; stability control; stair-climbing wheelchairs;
	suspension control; traction control; velocity control; wheelchair
	navigation; electric vehicles; handicapped aids; motion control;
	navigation; stability; suspensions (mechanical components); velocity
	control;},
  owner = {Radhika},
  timestamp = {2011.08.13}
}

@INCOLLECTION{Eltorai2003,
  author = {Eltorai, I.M.},
  title = {History of spinal cord medicine},
  booktitle = {Spinal cord medicine: principles and practice},
  publisher = {Demos Medical Publishing, Inc.},
  year = {2003},
  editor = {V.W. Lin},
  pages = {3-14},
  address = {New York},
  owner = {Radhika},
  timestamp = {2011.08.13}
}

@MISC{Grychtol2010,
  author = {Grychtol, B.},
  title = {Virtual Reality Electric Powered Wheelchair Simulator for Brain Computer
	Interfaces},
  howpublished = {{PhD} thesis, Bioengineering Unit, University of Strathlcyde},
  year = {2010},
  owner = {Radhika},
  school = {University of Strathclyde},
  timestamp = {2011.08.13}
}

@ARTICLE{Grychtol2010a,
  author = {Grychtol, B. and Lakany, H. and Valsan, G. and Conway, B. A.},
  title = {Human Behavior Integration Improves Classification Rates in Real-Time
	BCI},
  journal = {IEEE Trans Neural Syst Rehabil Eng},
  year = {2010},
  volume = {18},
  pages = {362--368},
  number = {4},
  abstract = {Brain-computer interfaces (BCI) offer potential for individuals with
	a variety of motor and sensory disabilities to interact with their
	environment, communicate and control mobility aids. Two key factors
	which affect <span class='snippet'>the</span> performance of a BCI
	and its usability are <span class='snippet'>the</span> feedback given
	to <span class='snippet'>the</span> participant and <span class='snippet'>the</span>
	subject's motivation. This paper presents <span class='snippet'>the</span>
	results from a study investigating <span class='snippet'>the</span>
	effects of feedback and motivation on <span class='snippet'>the</span>
	performance of <span class='snippet'>the</span> Strathclyde Brain
	Computer Interface. <span class='snippet'>The</span> paper discusses
	how <span class='snippet'>the</span> performance of <span class='snippet'>the</span>
	system can be improved by behavior integration and <span class='snippet'>human</span>-<span
	class='snippet'>in</span>-<span class='snippet'>the</span>-<span
	class='snippet'>loop</span> design.},
  doi = {10.1109/TNSRE.2010.2053218},
  owner = {xrb10173},
  timestamp = {2011.03.11}
}

@INPROCEEDINGS{Hart2006,
  author = {Hart, S. G.},
  title = {{NASA}-{T}ask {L}oad {I}ndex ({NASA}-{TLX}); 20 Years Later},
  booktitle = {Proceedings of the Human Factors and Ergonomics Society 50th Annual
	Meeting},
  year = {2006},
  pages = {904-908},
  address = {Santa Monica},
  publisher = {HFES},
  owner = {Radhika},
  timestamp = {2011.08.15},
  url = {http://human-factors.arc.nasa.gov/groups/TLX/downloads/HFES_2006_Paper.pdf}
}

@INCOLLECTION{Hart1988,
  author = {S. G. Hart and L. E. Staveland},
  title = {Development of {NASA}-{TLX} (Task Load Index): {R}esults of empirical
	and theoretical research},
  booktitle = {Human Mental Workload},
  publisher = {North Holland Press},
  year = {1988},
  editor = {P. A. Hancock and N. Meshkati},
  address = {Amsterdam},
  owner = {Radhika},
  timestamp = {2011.08.15},
  url = {http://human-factors.arc.nasa.gov/groups/TLX/downloads/NASA-TLXChapter.pdf}
}

@MISC{Hoyer1996,
  author = {H. Hoyer and U. Borgolte},
  title = {{OMNI}: Edited Final Report},
  howpublished = {{TIDE Project TP1097 - OMNI}},
  year = {1996},
  owner = {Radhika},
  timestamp = {2011.08.15}
}

@ARTICLE{Kuno2003,
  author = {Y. Kuno and N. Shimada and Y. Shirai},
  title = {Look where you're going [robotic wheelchair]},
  journal = {Robotics Automation Magazine, {IEEE}},
  year = {2003},
  volume = {10},
  pages = { 26 - 34},
  number = {1},
  abstract = { We propose a robotic wheelchair that observes the user and the environment.
	It can understand the user's intentions from his/her behaviors and
	the environmental information. It also observes the user when he/she
	is off the wheelchair, recognizing the user's commands indicated
	by hand gestures. Experimental results show our approach to be promising.
	Although the current system uses face direction, for people who find
	it difficult to move their faces, it can be modified to use the movements
	of the mouth, eyes, or any other body parts that they can move. Since
	such movements are generally noisy, the integration of observing
	the user and the environment will be effective in understanding the
	real intentions of the user and will be a useful technique for better
	human interfaces.},
  doi = {10.1109/MRA.2003.1191708},
  issn = {1070-9932},
  keywords = { body part movements; environmental information; eye movements; face
	direction; face recognition; hand gesture recognition; human interfaces;
	motion control; mouth movements; robotic wheelchair; user intentions;
	face recognition; gesture recognition; handicapped aids; medical
	robotics; mobile robots; motion control;}
}

@ARTICLE{Millan2003,
  author = {Millán, José del R.},
  title = {Adaptive brain interfaces},
  journal = {Communications of the {ACM}},
  year = {2003},
  volume = {Volume 46, Issue 3},
  pages = {74-80},
  abstract = {Users interact with physical devices through nothing more than the
	voluntary control of their own mental activity.},
  comment = {BR},
  owner = {Radhika},
  timestamp = {2011.02.13},
  url = {http://delivery.acm.org/10.1145/640000/636773/p74-millan.pdf?key1=636773&key2=6699267921&coll=DL&dl=ACM&CFID=9773590&CFTOKEN=90962465}
}

@ARTICLE{Millan2009,
  author = {Millán, José del R. and Ferran Galán and Dirk Vanhooydonck and Eileen
	Lew and Johan Philips and Marnix Nuttin},
  title = {Asynchronous non-invasive brain-actuated control of an intelligent
	wheelchair},
  journal = {31st Annual International Conference of the {IEEE} Engineering in
	Medicine and Biology Society ({EMBS}), 2009.},
  year = {2009},
  pages = {3361-3364},
  abstract = {In this paper we present further results of our asynchronous and non-invasive
	BMI for the continuous control of an intelligent wheelchair. Three
	subjects participated in two experiments where they steered the wheelchair
	spontaneously, without any external cue. To do so the users learn
	to voluntary modulate EEG oscillatory rhythms by executing three
	mental tasks (i.e., mental imagery) that are associated to different
	steering commands. Importantly, we implement shared control techniques
	between the BMI and the intelligent wheelchair to assist the subject
	in the driving task. The results show that the three subjects could
	achieve a significant level of mental control, even if far from optimal,
	to drive an intelligent wheelchair.},
  owner = {Radhika},
  timestamp = {2011.02.13},
  url = {http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=5332828}
}

@INPROCEEDINGS{Moon2005,
  author = {Inhyuk Moon and Myungjoon Lee and Junuk Chu and Museong Mun},
  title = {Wearable {EMG}-based {HCI} for Electric-Powered Wheelchair Users
	with Motor Disabilities},
  booktitle = {Robotics and Automation, 2005. {ICRA} 2005. {P}roceedings of the
	2005 {IEEE} International Conference on},
  year = {2005},
  pages = { 2649 - 2654},
  abstract = { Electromyogram (EMG) signal generated by voluntary contraction of
	muscles is often used in rehabilitation devices because of its distinct
	output characteristics compared to other bio-signals. This paper
	proposes a wearable EMG-based human-computer interface (HCI) for
	electric-powered wheelchair users with motor disabilities by C4 or
	C5 level spinal cord injury. User expresses his intention as shoulder
	elevation gestures, which are recognized by comparing EMG signals
	acquired from the levator scapulae muscles with a preset threshold
	value. In this paper HCI command to control electric-powered wheelchair
	is made of combinations of left-, right-and both-shoulders elevation
	gestures. The proposed wearable HCI hardware consists of two active
	surface electrodes, a high-speed micro-controller, a Bluetooth module,
	and a battery. Experimental results using the wearable EMG based
	HCI and the electric-powered wheelchair developed show the proposed
	wearable EMG-based HCI is feasible for the users with severe motor
	disabilities. },
  doi = {10.1109/ROBOT.2005.1570513},
  keywords = { Double threshold ; Electric-powered wheelchair; Electromyogram (EMG)
	; Wearable human-computer interface (HCI) ;}
}

@MISC{NASA1986,
  author = {{NASA}},
  title = {{T}ask {L}oad {I}ndex {(NASA-TLX)}, v1.0: paper and pencil package},
  howpublished = {{NASA} {A}mes {R}esearch {C}enter},
  year = {1986},
  owner = {Radhika},
  timestamp = {2011.08.15},
  url = {http://human-factors.arc.nasa.gov/groups/TLX/downloads/TLX.pdf}
}

@MISC{Centre2010,
  author = {{National Spinal Cord Injury Statistical Centre}},
  howpublished = {Spinal cord injury facts and figures at a glance},
  year = {2010},
  owner = {Radhika},
  timestamp = {2011.08.13},
  url = {http://www.nscisc.uab.edu/}
}

@INPROCEEDINGS{Nuttin2002,
  author = {Nuttin, M. and Vanhooydonck, D. and Demeester, E. and Van Brussel,
	H.},
  title = {Selection of suitable human-robot interaction techniques for intelligent
	wheelchairs},
  booktitle = {Robot and Human Interactive Communication, 2002. {P}roceedings. 11th
	{IEEE} International Workshop on},
  year = {2002},
  pages = { 146 - 151},
  abstract = { There are many user interfaces already available to drive electric
	wheelchairs. These enable users to convey their intention explicitly
	to the wheelchair control system. However, we have observed users
	who find it nonetheless extremely difficult to do so. For some severely
	disabled users it is almost impossible to drive a conventional electric
	wheelchair in a safe way. This paper explores several ways of implicit
	communication to assist the user to perform daily manoeuvres. Some
	initial user trials have been performed at a hospital. The results
	are evaluated and conclusions are drawn on the selection of suitable
	human-robot interaction techniques.},
  doi = {10.1109/ROMAN.2002.1045613},
  issn = { },
  keywords = { electric wheelchairs; human-robot interaction techniques; intelligent
	wheelchairs; user interfaces; wheelchair control system; collision
	avoidance; handicapped aids; mobile robots; user interfaces;}
}

@INPROCEEDINGS{Parikh2005,
  author = {Parikh, S.P. and Grassi, V., Jr. and Kumar, V. and Jun Okamoto, Jr.},
  title = {Usability Study of a Control Framework for an Intelligent Wheelchair},
  booktitle = {Robotics and Automation, 2005. {ICRA} 2005. {P}roceedings of the
	2005 {IEEE} International Conference on},
  year = {2005},
  pages = { 4745 - 4750},
  abstract = { We describe the development and assessment of a computer controlled
	wheelchair called the SMARTCHAIR. A shared control framework with
	different levels of autonomy allows the human operator to stay in
	complete control of the chair at each level while ensuring her safety.
	The framework incorporates deliberative motion plans or controllers,
	reactive behaviors, and human user inputs. At every instant in time,
	control inputs from these three different sources are blended continuously
	to provide a safe trajectory to the destination, while allowing the
	human to maintain control and safely override the autonomous behavior.
	In this paper, we present usability experiments with 50 participants
	and demonstrate quantitatively the benefits of human-robot augmentation.
	},
  doi = {10.1109/ROBOT.2005.1570853},
  keywords = { Wheelchair navigation ; smart wheelchairs ; usability studies ; user
	evaluations ; wheelchair control;}
}

@INPROCEEDINGS{Petry2010,
  author = {Petry, M.R. and Moreira, A.P. and Braga, R.A.M. and Reis, L.P.},
  title = {Shared control for obstacle avoidance in intelligent wheelchairs},
  booktitle = {Robotics Automation and Mechatronics ({RAM}), 2010 {IEEE} Conference
	on},
  year = {2010},
  pages = {182 -187},
  abstract = {Intelligent wheelchairs operating in dynamic environments need to
	sense its neighborhood and adapt the control signal, in real-time,
	to avoid collisions and protect the user. In this paper we propose
	a robust, real-time obstacle avoidance extension of the classic potential
	field methodology. Our algorithm is specially adapted to share the
	wheelchair's control with the user avoiding risky situations. This
	method relies on the idea of virtual forces, generated by the user
	command (attractive force) and by the objects detected on each ultrasonic
	sensor (repulsive forces), acting on the wheelchair. The resultant
	wheelchair's behavior is obtained by the sum of the attractive force
	and all the repulsive forces at a given position. Experimental results
	from drive tests in a cluttered office environment provided statistical
	evidence that the proposed algorithm is effective to reduce the number
	of collisions and still improve the user's safety perception.},
  doi = {10.1109/RAMECH.2010.5513193},
  keywords = {attractive force;intelligent wheelchairs;obstacle avoidance;potential
	field methodology;repulsive forces;shared control;ultrasonic sensor;user
	safety perception;collision avoidance;handicapped aids;medical robotics;mobile
	robots;safety;wheelchairs;},
  owner = {Radhika},
  timestamp = {2011.03.06}
}

@INPROCEEDINGS{Philips2007,
  author = {Philips, J. and Millán, J. del R. and Vanacker, G. and Lew, E. and
	Galan, F. and Ferrez, P.W. and Van Brussel, H. and Nuttin, M.},
  title = {Adaptive Shared Control of a Brain-Actuated Simulated Wheelchair},
  booktitle = {Rehabilitation Robotics, 2007. {ICORR} 2007. {IEEE} 10th International
	Conference on},
  year = {2007},
  pages = {408 -414},
  abstract = {The use of shared control techniques has a profound impact on the
	performance of a robotic assistant controlled by human brain signals.
	However, this shared control usually provides assistance to the user
	in a constant and identical manner each time. Creating an adaptive
	level of assistance, thereby complementing the user's capabilities
	at any moment, would be more appropriate. The better the user can
	do by himself, the less assistance he receives from the shared control
	system; and vice versa. In order to do this, we need to be able to
	detect when and in what way the user needs assistance. An appropriate
	assisting behaviour would then be activated for the time the user
	requires help, thereby adapting the level of assistance to the specific
	situation. This paper presents such a system, helping a brain-computer
	interface (BCI) subject perform goal-directed navigation of a simulated
	wheelchair in an adaptive manner. Whenever the subject has more difficulties
	in driving the wheelchair, more assistance will be given. Experimental
	results of two subjects show that this adaptive shared control increases
	the task performance. Also, it shows that a subject with a lower
	BCI performance has more need for extra assistance in difficult situations,
	such as manoeuvring in a narrow corridor.},
  doi = {10.1109/ICORR.2007.4428457},
  keywords = {adaptive shared control;brain actuated simulated wheelchair;brain
	signal controlled robotic assistant;brain-computer interface;goal
	directed navigation task;human brain signals;bioelectric phenomena;handicapped
	aids;man-machine systems;medical control systems;neurophysiology;robots;}
}

@INPROCEEDINGS{Prassler1998,
  author = {Prassler, E. and Scholz, J. and Strobel, M.},
  title = {{MAid}: mobility assistance for elderly and disabled people},
  booktitle = {Industrial Electronics Society, 1998. {IECON} 1998. {P}roceedings
	of the 24th Annual Conference of the {IEEE}},
  year = {1998},
  volume = {4},
  pages = {2493 - 2498},
  doi = {10.1109/IECON.1998.724118},
  owner = {Radhika},
  timestamp = {2011.08.16}
}

@INCOLLECTION{Prassler1999,
  author = {Prassler, Erwin and Scholz, Jens and Strobel, Matthias and Fiorini,
	Paolo},
  title = {{MAid}: A Robotic Wheelchair Operating in Public Environments},
  booktitle = {Sensor Based Intelligent Robots},
  publisher = {Springer Berlin - Heidelberg},
  year = {1999},
  editor = {Christensen, Henrik and Bunke, Horst and Noltemeier, Hartmut},
  volume = {1724},
  series = {Lecture Notes in Computer Science},
  pages = {68-95},
  abstract = {In this paper we describe the hardware design, the control and navigation
	system, and our preliminary experiments with the robotic wheelchair
	MAid (Mobility Aid for Elderly and Disabled People). MAidâ€™s general
	task is to transport people with severely impaired motion skills
	such as, for example, paraplegia, multiple sclerosis, poliomyelitis,
	or muscular dystrophy. Following the advice of disabled people and
	physicians we did not set out to re-invent and re-develop the set
	of standard skills of so-called intelligent wheelchairs, such as
	FollowWall, FollowCorridor, PassDoorway which are commonly described
	in the literature. These maneuvers do not always require fine motion
	control and disabled people, in spite of their disability, are often
	well capable of navigating their wheelchair along a corridor and
	actually eager to do it. In our work we focused instead on maneuvers
	which are very burdensome because they take a long time and require
	extreme attention. One of these functions is deliberative locomotion
	in rapidly changing, large-scale environments, such as shopping malls,
	entry halls of theaters, and concourses of airports or railway stations,
	where tens or hundreds of people and objects are moving around. This
	function was not only acknowledged as being very useful but also
	very entertaining, because MAid often had to work very hard to find
	its way through a crowd of people. MAidâ€™s performance was tested
	in the central station of Ulm during rush-hour, and in the exhibition
	halls of the Hannover Messe â€™98, the biggest industrial fair worldwide.
	Altogether, MAid has survived more than 36 hours of testing in public,
	crowded environments with heavy passenger traffic. To our knowledge
	this is the first system among robotic wheelchairs and mobile robots
	to have achieved a similar performance.},
  affiliation = {Research Institute for Applied Knowledge Processing (FAW), P.O. Box
	2 060, D-89010 Ulm, Germany},
  owner = {Radhika},
  timestamp = {2011.08.13},
  url = {http://dx.doi.org/10.1007/10705474_5}
}

@ARTICLE{Rebsamen2010,
  author = {Rebsamen, B. and Cuntai Guan and Haihong Zhang and Chuanchu Wang
	and Cheeleong Teo and Ang, M.H. and Burdet, E.},
  title = {A Brain Controlled Wheelchair to Navigate in Familiar Environments},
  journal = {Neural Systems and Rehabilitation Engineering, {IEEE} Transactions
	on},
  year = {2010},
  volume = {18},
  pages = {590 -598},
  number = {6},
  abstract = {While brain-computer interfaces (BCIs) can provide communication to
	people who are locked-in, they suffer from a very low information
	transfer rate. Further, using a BCI requires a concentration effort
	and using it continuously can be tiring. The brain controlled wheelchair
	(BCW) described in this paper aims at providing mobility to BCI users
	despite these limitations, in a safe and efficient way. Using a slow
	but reliable P300 based BCI, the user selects a destination amongst
	a list of predefined locations. While the wheelchair moves on virtual
	guiding paths ensuring smooth, safe, and predictable trajectories,
	the user can stop the wheelchair by using a faster BCI. Experiments
	with nondisabled subjects demonstrated the efficiency of this strategy.
	Brain control was not affected when the wheelchair was in motion,
	and the BCW enabled the users to move to various locations in less
	time and with significantly less control effort than other control
	strategies proposed in the literature.},
  doi = {10.1109/TNSRE.2010.2049862},
  issn = {1534-4320},
  keywords = {P300 based BCI;brain controlled wheelchair;brain-computer interfaces;concentration
	effort;familiar environment navigation;information transfer rate;predefined
	locations;virtual guiding paths;brain-computer interfaces;handicapped
	aids;medical control systems;motion control;navigation;wheelchairs;},
  owner = {Radhika},
  timestamp = {2011.02.27}
}

@INCOLLECTION{Sie2003,
  author = {Sie, I. and Waters, R.L},
  title = {Outcomes following spinal cord injury},
  booktitle = {Spinal cord medicine: principles and practice},
  publisher = {Demos Medical Publishing, Inc.},
  year = {2003},
  editor = {V.W. Lin},
  pages = {87-103},
  address = {New York},
  owner = {Radhika},
  timestamp = {2011.08.13}
}

@ARTICLE{Simpson2005,
  author = {Richard Simpson},
  title = {Smart wheelchairs: A literature review},
  journal = {Journal of Rehabilitation Research and Development},
  year = {2005},
  volume = {42},
  pages = {423-436},
  number = {4},
  owner = {Radhika},
  timestamp = {2011.08.13}
}

@INPROCEEDINGS{Simpson1999,
  author = {Simpson, R and Poirot, CD and Baxter, MF},
  title = {Evaluation of the Hephaestus smart wheelchair system},
  booktitle = {Proceedings of the 6th International Conference on Rehabilitation
	Robotics ({ICORR})},
  year = {1999},
  owner = {Radhika},
  timestamp = {2011.08.15},
  url = {http://rehabrobotics.org/icorr1999/papers/papers/simpson.pdf}
}

@ARTICLE{Simpson2002,
  author = {Simpson, R.C. and Poirot, D. and Baxter, F.},
  title = {The {H}ephaestus Smart Wheelchair system},
  journal = {Neural Systems and Rehabilitation Engineering, {IEEE} Transactions
	on},
  year = {2002},
  volume = {10},
  pages = {118 -122},
  number = {2},
  abstract = {The Hephaestus Smart Wheelchair System is envisioned as a series of
	components that clinicians and wheelchair manufacturers will be able
	to attach to standard power wheelchairs to convert them into "smart
	wheelchairs." A prototype of the system has been developed and mounted
	on an Everest and Jennings Lancer2000 wheelchair. The prototype bases
	its navigation assistance behavior on the behavior developed for
	the NavChair Assistive Wheelchair Navigation System, but the underlying
	hardware and software are being designed to facilitate commercialization.
	This paper describes our design goals for the Hephaestus system and
	discusses the current status of the system prototype as well as plans
	for future work.},
  doi = {10.1109/TNSRE.2002.1031980},
  issn = {1534-4320},
  keywords = {Everest and Jennings Lancer2000 wheelchair;Hephaestus smart wheelchair
	system;NavChair Assistive Wheelchair Navigation System;commercialization;navigation
	assistance behavior;standard power wheelchairs;computerised instrumentation;handicapped
	aids;medical computing;navigation;Acoustics;Algorithms;Equipment
	Design;Goals;Humans;Pattern Recognition, Automated;Pilot Projects;Robotics;Ultrasonics;User-Computer
	Interface;Wheelchairs;}
}

@ARTICLE{RichardC.Simpson1998,
  author = {Richard C. Simpson and Simon P. Levine and David A. Bell and Lincoln
	A. Jaros and Yoram Koren and Johann Borenstein},
  title = {Navchair: An Assistive Wheelchair Navigation System with Automatic
	Adaptation},
  journal = {Lecture Notes in Artificial Intelligence},
  year = {1998},
  volume = {1458},
  pages = {235-255},
  abstract = {(No Abstract)},
  owner = {Radhika},
  timestamp = {2011.02.13},
  url = {http://www.springerlink.com/content/t7421488v8m2053p/fulltext.pdf}
}

@BOOK{Somers2010,
  title = {Spinal cord injury: Functional rehabilitation},
  publisher = {Pearson Education Inc.},
  year = {2010},
  author = {Somers, M.F},
  address = {New Jersey},
  edition = {3rd},
  owner = {Radhika},
  timestamp = {2011.08.13}
}

@ARTICLE{Urdiales2010,
  author = {Urdiales, C. and Fernandez-Espejo, B. and Annicchiaricco, R. and
	Sandoval, F. and Caltagirone, C.},
  title = {Biometrically Modulated Collaborative Control for an Assistive Wheelchair},
  journal = {Neural Systems and Rehabilitation Engineering, {IEEE} Transactions
	on},
  year = {2010},
  volume = {18},
  pages = {398 -408},
  number = {4},
  abstract = {To operate a wheelchair, people with severe physical disabilities
	may require assistance, which can be provided by robotization. However,
	medical experts report that an excess of assistance may lead to loss
	of residual skills, so that it is important to provide just the right
	amount of assistance. This work proposes a collaborative control
	system based on weighting the robot's and the user's commands by
	their respective efficiency to reactively obtain an emergent controller.
	Thus, the better the person operates, the more control he/she gains.
	Tests with volunteers have proven, though, that some users may require
	extra assistance when they become stressed. Hence, we propose a controller
	that can change the amount of support taking into account supplementary
	biometric data. In this work, we use an off-the-shelf wearable pulse
	oximeter. Experiments have demonstrated that volunteers could use
	our wheelchair in a more efficient way due to the proposed biometric
	modulated collaborative control.},
  doi = {10.1109/TNSRE.2010.2056391},
  issn = {1534-4320},
  keywords = {assistive wheelchair;biometric data;biometrically modulated collaborative
	control;emergent controller;physical disabilities;pulse oximeter;robotization;electric
	vehicles;handicapped aids;medical control systems;robots;Algorithms;Disabled
	Persons;Environment Design;Exercise;Female;Heart Rate;Humans;Middle
	Aged;Monitoring, Physiologic;Neuropsychological Tests;Oximetry;Robotics;Safety;User-Computer
	Interface;Wheelchairs;},
  owner = {Radhika},
  timestamp = {2011.02.27}
}

@INPROCEEDINGS{Valsan2009,
  author = {Valsan, G. and Grychtol, B. and Lakany, H. and Conway, B.A.},
  title = {The strathclyde brain computer interface},
  booktitle = {Engineering in Medicine and Biology Society, 2009. {EMBC} 2009. {A}nnual
	International Conference of the {IEEE}},
  year = {2009},
  pages = {606 -609},
  abstract = {Brain-computer interfaces (BCI) offer potential for individuals with
	a variety of motor and sensory disabilities to control their environment,
	communicate, and control mobility aids. However, the key to BCI usability
	rests in being able to extract relevant time varying signals that
	can be classified into usable commands in real time. This paper reports
	the first success of the Strathclyde BCI controlling a wheelchair
	on-line in Virtual Reality. Surface EEG recorded during wrist movement
	in two different directions were classified and used to control a
	wheelchair within a virtual reality environment. While principal
	component analysis was used for feature vector quantiser distances
	were used for classification. Classification success rates between
	68% and 77% were obtained using these relatively simple methods.},
  doi = {10.1109/IEMBS.2009.5333506},
  issn = {1557-170X},
  keywords = {Strathclyde brain computer interface;feature vector quantiser;motor
	disabilities;principal component analysis;sensory disabilities;signal
	classificaiton;surface EEG;virtual reality;wheelchair control;wrist
	movement;brain-computer interfaces;electroencephalography;handicapped
	aids;medical control systems;medical signal processing;principal
	component analysis;signal classification;virtual reality;Algorithms;Brain;Electroencephalography;Evoked
	Potentials;Humans;Man-Machine Systems;Pattern Recognition, Automated;User-Computer
	Interface;Wheelchairs;}
}

@ARTICLE{Vanhooydonck2010963,
  author = {Dirk Vanhooydonck and Eric Demeester and Alexander Hüntemann and
	Johan Philips and Gerolf Vanacker and Hendrik Van Brussel and Marnix
	Nuttin},
  title = {Adaptable navigational assistance for intelligent wheelchairs by
	means of an implicit personalized user model},
  journal = {Robotics and Autonomous Systems},
  year = {2010},
  volume = {58},
  pages = {963 - 977},
  number = {8},
  abstract = {Elderly and disabled people can experience considerable difficulties
	when driving a powered wheelchair, especially if they do not possess
	the fine steering capacities that are required to perform certain
	manoeuvres, like avoiding obstacles or docking at tables. In order
	to help these people, several #intelligent# wheelchairs have been
	developed in the past, meaning that a powered wheelchair was endowed
	with the abilities to provide navigational assistance to its user.
	In such a scenario, control over the wheelchair is shared between
	the user and the intelligent assistance. The problem of the existing
	intelligent wheelchairs is, however, that the rules for assistance
	are hard-coded and by consequence not adaptable to the personal handicap
	and needs of a specific user. Therefore, this paper proposes a new,
	more user-centered approach to shared wheelchair control. The presented
	framework executes two tasks: it continuously estimates the user's
	intention and it determines whether the user needs assistance to
	achieve that intention. An implicit user model is introduced and
	incorporated in the framework, in order to make the execution of
	both tasks adaptable to a specific user. This paper presents the
	proposed framework, along with experimental results in simulation
	and on a real wheelchair.},
  doi = {DOI: 10.1016/j.robot.2010.04.002},
  issn = {0921-8890},
  keywords = {Shared control},
  owner = {Radhika},
  timestamp = {2011.08.15},
  url = {http://www.sciencedirect.com/science/article/pii/S0921889010000837}
}

@INPROCEEDINGS{Velazquez2010,
  author = {Velázquez, R.},
  title = {On the Dynamics and Control of Robotic Wheelchairs},
  booktitle = {{IFToMM} Symposium on Mechanism Design for Robotics},
  year = {2010},
  address = {Mexico City, Mexico},
  owner = {Radhika},
  timestamp = {2011.08.13}
}

@MISC{Wang2007,
  author = {Jijun Wang and Stephen Balakirsky},
  title = {{USARSim} V.3.1.3 {M}anual - A game-based simulation of mobile robots},
  year = {2007},
  owner = {Radhika},
  timestamp = {2011.08.15}
}

@ARTICLE{Wolpaw2002,
  author = {Jonathan R. Wolpaw and Niels Birbaumer and Dennis J. McFarland and
	Gert Pfurtscheller and Theresa M. Vaughan},
  title = {Brain-computer interfaces for communication and control},
  journal = {Clinical Neurophysiology},
  year = {2002},
  volume = {113},
  pages = {767 - 791},
  number = {6},
  abstract = {For many years people have speculated that electroencephalographic
	activity or other electrophysiological measures of brain function
	might provide a new non-muscular channel for sending messages and
	commands to the external world - a brain-computer interface (BCI).
	Over the past 15 years, productive BCI research programs have arisen.
	Encouraged by new understanding of brain function, by the advent
	of powerful low-cost computer equipment, and by growing recognition
	of the needs and potentials of people with disabilities, these programs
	concentrate on developing new augmentative communication and control
	technology for those with severe neuromuscular disorders, such as
	amyotrophic lateral sclerosis, brainstem stroke, and spinal cord
	injury. The immediate goal is to provide these users, who may be
	completely paralyzed, or [`]locked in', with basic communication
	capabilities so that they can express their wishes to caregivers
	or even operate word processing programs or neuroprostheses. Present-day
	BCIs determine the intent of the user from a variety of different
	electrophysiological signals. These signals include slow cortical
	potentials, P300 potentials, and mu or beta rhythms recorded from
	the scalp, and cortical neuronal activity recorded by implanted electrodes.
	They are translated in real-time into commands that operate a computer
	display or other device. Successful operation requires that the user
	encode commands in these signals and that the BCI derive the commands
	from the signals. Thus, the user and the BCI system need to adapt
	to each other both initially and continually so as to ensure stable
	performance. Current BCIs have maximum information transfer rates
	up to 10-25 bits/min. This limited capacity can be valuable for people
	whose severe disabilities prevent them from using conventional augmentative
	communication methods. At the same time, many possible applications
	of BCI technology, such as neuroprosthesis control, may require higher
	information transfer rates. Future progress will depend on: recognition
	that BCI research and development is an interdisciplinary problem,
	involving neurobiology, psychology, engineering, mathematics, and
	computer science; identification of those signals, whether evoked
	potentials, spontaneous rhythms, or neuronal firing rates, that users
	are best able to control independent of activity in conventional
	motor output pathways; development of training methods for helping
	users to gain and maintain that control; delineation of the best
	algorithms for translating these signals into device commands; attention
	to the identification and elimination of artifacts such as electromyographic
	and electro-oculographic activity; adoption of precise and objective
	procedures for evaluating BCI performance; recognition of the need
	for long-term as well as short-term assessment of BCI performance;
	identification of appropriate BCI applications and appropriate matching
	of applications and users; and attention to factors that affect user
	acceptance of augmentative technology, including ease of use, cosmesis,
	and provision of those communication and control capacities that
	are most important to the user. Development of BCI technology will
	also benefit from greater emphasis on peer-reviewed research publications
	and avoidance of the hyperbolic and often misleading media attention
	that tends to generate unrealistic expectations in the public and
	skepticism in other researchers. With adequate recognition and effective
	engagement of all these issues, BCI systems could eventually provide
	an important new communication and control option for those with
	motor disabilities and might also give those without disabilities
	a supplementary control channel or a control channel useful in special
	circumstances.},
  doi = {DOI: 10.1016/S1388-2457(02)00057-3},
  issn = {1388-2457},
  keywords = {Brain-computer interface},
  url = {http://www.sciencedirect.com/science/article/pii/S1388245702000573}
}

@INCOLLECTION{Woolsey2003,
  author = {Woolsey, R.M. and Martin, D.S.},
  title = {Acute Nontraumatic Myelopathies},
  booktitle = {Spinal cord medicine: Principles and practice},
  publisher = {Demos Medical Publishing, Inc.},
  year = {2003},
  editor = {V.W. Lin},
  pages = {407-417},
  owner = {Radhika},
  timestamp = {2011.08.13}
}

@INCOLLECTION{Woolsey2003a,
  author = {Woolsey, R.M. and Martin, D.S.},
  title = {Chronic Nontraumatic Myelopathies},
  booktitle = {Spinal cord medicine: Principles and practice},
  publisher = {Demos Medical Publishing, Inc.},
  year = {2003},
  editor = {V.W. Lin},
  pages = {419-428},
  owner = {Radhika},
  timestamp = {2011.08.13}
}

@MISC{Yanco2000,
  author = {Holly Yanco},
  title = {Shared User-Computer Control of a Robotic Wheelchair System},
  howpublished = {Massachusetts Institute of Technology},
  year = {2000},
  abstract = {An assistive robotic wheelchair system should allow its user to travel
	more efficiently and with greater ease. The robotic wheelchair system
	described in this thesis, Wheelesley, performs semi-autonomous navigation
	for its user, taking high-level directional commands and performing
	the low-level navigation required to avoid obstacles and stay on
	a safe path. The system consists of a standard electric wheelchair
	with an on-board computer for motor control, a vision system running
	on an off-the-shelf notebook computer, sensors, and a graphical user
	interface running on a tray mounted notebook computer. Most other
	research on robotic wheelchairs only addresses indoor navigation.
	The Wheelesley system can travel both indoors and outdoors using
	specialized navigation modes; there is a control algorithm for indoor
	navigation and a control algorithm for outdoor navigation. User tests
	have been conducted for both control modes to compare robotic assisted
	control against manual control. Robotic assisted control requires
	71% less effort for indoor navigation and 88% less effort for outdoor
	navigation. In addition, the total time needed to travel between
	two points is reduced since less time is spent waiting to scan to
	the desired commands. The system switches automatically between navigation
	modes through the use of a novel indoor/outdoor detector. The detector
	is comprised of an ultrasonic transducer, three light-to-voltage
	optical sensors and a thermistor. A decision tree learned by C4.5
	using data collected in a variety of indoor and outdoor conditions
	classified a test set correctly 98.3% of the time. The system can
	be easily customized for the access method(s) required by each user.
	This thesis describes customization of the user interface for two
	different access methods: eye tracking, an uncommon access method
	for a wheelchair, and single switch scanning, which is considered
	the driving method of last resort on standard powered wheelchairs.
	The wheelchair system and its interface was evaluated by a group
	of physical therapists.},
  owner = {Radhika},
  school = {Massachusetts Institute of Technology},
  timestamp = {2011.02.13},
  url = {http://www.cs.uml.edu/~holly/papers/yanco-phd.pdf}
}

@INPROCEEDINGS{Zeng2007,
  author = {Qiang Zeng and Burdet, E. and Rebsamen, B. and Chee Leong Teo},
  title = {Evaluation of the Collaborative Wheelchair Assistant System},
  booktitle = {Rehabilitation Robotics, 2007. {ICORR 2007}. {IEEE} 10th International
	Conference on},
  year = {2007},
  pages = {601 -608},
  abstract = {The collaborative wheelchair assistant (CWA) is a robotic wheelchair
	which makes full use of human skills, by involving the user into
	the navigation control. The user gives the high-level commands and
	directly controls the speed, while the low-level control is taken
	over by the machine, which is tracking a software defined guide path.
	This paper presents an evaluation of the CWA system, consisting of
	experiments performed with human subjects. We investigated the performance
	of the system in terms of its interaction with healthy subjects and
	motion efficiency. Initial experiments with a cerebral palsy subject
	were also performed. The results show that path guidance brings safe
	motion and drastically simplifies the control. The wheelchair user
	adopts a driving behavior which is optimal from the first trial and
	requires little intervention.},
  doi = {10.1109/ICORR.2007.4428486},
  keywords = {cerebral palsy subject;collaborative wheelchair assistant system;robotic
	wheelchair;handicapped aids;medical robotics;}
}

@INPROCEEDINGS{Zeng2006,
  author = {Qiang Zeng and Chee Leong Teo and Rebsamen, B. and Burdet, E.},
  title = {Design of a collaborative wheelchair with path guidance assistance},
  booktitle = {Robotics and Automation, 2006. {ICRA 2006}. {P}roceedings 2006 {IEEE}
	International Conference on},
  year = {2006},
  pages = {877 -882},
  abstract = {This paper describes the development and assessment of a collaborative
	wheelchair assistant (CWA). The concept at the heart of the CWA is
	to rely on the user's motion planning skills and assist the maneuvering
	with path guidance. The user decides where to go and controls the
	speed (including start and stop), while the system guides the wheelchair
	along software-defined paths. An intuitive path editor allows the
	user to modify the path on-line and so avoid dangers or obstacles.
	By using the human sensory and planning systems, complex sensor processing
	and artificial decision systems are not needed, making the system
	safe, simple and low-cost. Experimental results demonstrate this
	concept},
  doi = {10.1109/ROBOT.2006.1641820},
  issn = {1050-4729},
  keywords = {artificial decision systems;collaborative wheelchair assistant;complex
	sensor processing;motion planning;obstacle avoidance;path guidance
	assistance;software-defined paths;collision avoidance;handicapped
	aids;medical robotics;mobile robots;},
  owner = {Radhika},
  timestamp = {2011.02.27},
  url = {http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=1641820}
}

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