Several studies have shown that both children and adults benefit substantially from access to a means of independent mobility. While the needs of many individuals with disabilities can be satisfied with traditional manual or powered wheelchairs, a segment of the disabled community finds it difficult or impossible to use wheelchairs independently. To accommodate this population, researchers have used technologies originally developed for mobile robots to create "smart wheelchairs." Smart wheelchairs have been the subject of research since the early 1980s and have been developed on four continents. This article presents a summary of the current state of the art and directions for future research. Abbreviations: ADL = activities of daily living, CALL = Communication Aids for Language and Learning, EOG = electrooculographic, IR = infrared, LRF = laser range finder, MAid = Mobility Aid for elderly and disabled people, NLPR = National Laboratory of Pattern Recognition, OMNI = Office wheelchair with high Maneuverability and Navigational Intelligence, SPAM = Smart Power Assistance Module, SWCS = Smart Wheelchair Component System, VAHM = Véhicule Autonome pour Handicapé Moteur.

The NavChair Assistive Wheelchair Navigation System [19] is being developed to reduce the cognitive and physical requirements of operating a power wheelchair for people with wide ranging impairments that limit their access to powered mobility. The NavChair is based on a commercial wheelchair system with the addition of a DOS-based computer system, ultrasonic sensors, and an interface module interposed between the joystick and power module of the wheelchair. The obstacle avoidance routines used by the NavChair in conjunction with the ultrasonic sensors are modifications of methods originally used in mobile robotics research. The NavChair currently employs three operating modes: general obstacle avoidance, door passage, and automatic wall following. Results from performance testing of these three operating modes demonstrate their functionality. In additional to advancing the technology of smart wheelchairs, the NavChair has application to the development and testing of "shared control" systems where a human and machine share control of a system and the machine can automatically adapt to human behaviors.

TPA023, a GABA(A) alpha2,3 alphasubtype-selective partial agonist, is expected to have comparable anxiolytic efficacy as benzodiazepines with reduced sedating effects. The compound lacks efficacy at the alpha1 subtype, which is believed to mediate these effects. This study investigated the effects of 0.5 and 1.5 mg TPA023 and compared them with placebo and lorazepam 2 mg (therapeutic anxiolytic dose). Twelve healthy male volunteers participated in this placebo-controlled, double-blind, double-dummy, four-way, cross-over study. Saccadic eye movements and visual analogue scales (VAS) were used to assess the sedative properties of TPA023. The effects on posturaL stability and cognition were assessed using body sway and a standardized battery of neurophysiological memory tests. Lorazepam caused a significant reduction in saccadic peak velocity, the VAS alertness score and impairment of memory and body sway. TPA023 had significant dose dependent effects on saccadic peak velocity (85 deg/sec maximum reduction at the higher dose) that approximated the effects of lorazepam. In contrast to lorazepam, TPA023 had no detectabLe effects on saccadic latency or inaccuracy. Also unlike lorazepam, TPA023 did not affect VAS alertness, memory or body sway. These results show that the effect profile of TPA023 differs markedly from that of lorazepam, at doses that were equipotent with regard to effects on saccadic peak veLocity. Contrary to lorazepam, TPA023 caused no detectable memory impairment or postural imbalance. These differences reflect the selectivity of TPA023 for different GABA(A) receptor subtypes.

Abstract-Independent mobility is important, but some wheelchair users find operating existing manual or powered wheelchairs difficult or impossible. Challenges to safe, independent wheelchair use can result from various overlapping physical, perceptual, or cognitive symptoms of diagnoses such as spinal cord injury, cerebrovascular accident, multiple sclerosis, amyotrophic lateral sclerosis, and cerebral palsy. Persons with different symptom combinations can benefit from different types of assistance from a smart wheelchair and different wheelchair form factors. The sizes of these user populations have been estimated based on published estimates of the number of individuals with each of several diseases who (1) also need a wheeled mobility device and (2) have specific symptoms that could interfere with mobility device use.

Research on intelligent walkers aims at helping elderly individuals to maintain their independence in familiar and unfamiliar environments. Several walkers have been developed by researchers at Carnegie Mellon University and the University of Pittsburgh. This article contributes to this research venue by describing the design and initial evaluations of iWalker, a multi-sensor rollator-mounted wayfinding system for the elderly. The primary difference of the proposed navigation aid from other intelligent walkers is that iWalker is assumed to operate in a smart world (SW), a physical space equipped with embedded sensors. By integrating inexpensive sensors into the environment, the cost and complexity of the walker can be reduced.