Wheelchair users often face architectural barriers such as curbs, limiting their accessibility, mobility, and participation in their communities. The mobility enhancement robotic (MEBot) wheelchair was developed to navigate over such architectural barriers. Its application allows wheelchair users to negotiate curbs automatically while the user remains in control. The application was optimized from a manual to a semiautomated process based on wheelchair users' feedback. The optimized application was evaluated by experienced wheelchair users who navigated over curbs of different heights. Participants evaluated MEBot in terms of effectiveness, workload demand, and usability. Ten participants successfully ascended and descended curbs of different heights at an average completion time of 55.7 ± 19.5 and 30.3 ± 9.1 s, respectively. MEBot maintained stability during the process, while participants reported low levels of effort, frustration, and overall cognitive demand to operate MEBot. Furthermore, participants were satisfied with the ease of learning and using the MEBot curb negotiation application to overcome the curbs but suggested less wheel adjustment for comfort and a faster pace to overcome curbs during real-world conditions.

Most wheelchairs have low directional stability due to their wheel-drive system configurations. Hence, when a wheelchair experiences excessive slip, it will create an uncontrollable moment that changes its heading direction, endangering the safety of the wheelchair user. This paper presents an approach to longitudinal slip reduction (or traction control) for an Electric Powered Wheelchair that uses a variable reference model, which is a mass-damper system. The position of a joystick is mapped to force and torque values, which are the input to this model. The output is the desired trajectory, which is fed to a trajectory tracking controller. The key idea is that if slip occurs, the applied torque to the wheels is reduced by decreasing the desired acceleration, which is achieved by changing the parameters of the reference model. In this study, the mass of the reference model is changed. The proposed slip reduction approach is validated via experiments.

The ability to perform activities of daily living and mobility-related activities of daily living are substantial indicators of one's ability to live at home and to participate in one's community. Technologies to assist with mobility and manipulation are among the most important tools that clinicians can provide to people with disabilities to promote independence and community participation. For people with severe disabilities involving both the upper and lower extremities, there are few systems that provide practical and coordinated assistance with mobility and manipulation tasks. The personal mobility and manipulation appliance (PerMMA) was created in response to goals set forth by a team of clinicians and people with disabilities.

In this paper, we investigate the enhanced ability of manipulation with the newly developed Personal Mobility and Manipulation Appliance (PerMMA). PerMMA is a new assistive device that integrates bimanual manipulation with smart mobility to assist people with severe physical disabilities and enhance their quality of lives. Different from the fixed mounting method used in most existing systems, a novel mounting system was designed on PerMMA to enhance its capability of manipulation assistance. With a workspace characterized by essential daily living tasks, we evaluated PerMMA's performance of manipulation using a comparative study between PerMMA and classic design, such as single arm and fixed mounting, used in most existing systems. Simulation results demonstrate significant improvements with PerMMA in both of its reachability and manipulability.

No abstract available.

We present an investigation into modeling of athetoid motion and prediction of user intent, for use in assistive computer interfaces during icon-clicking tasks. Data were recorded from three athetoid patients during unassisted icon-clicking trials with an isometric joystick. In order to facilitate development and testing of filter designs without the difficulty of repeated testing with human subjects, a quantitative model of the recorded patient data was developed using pseudoinverse methods. Using this model within the visuomotor control loop for the icon-clicking task, a prediction filter was then developed to reduce the target acquisition time. The filter is based on a novel "autoregressive stretching window" model which selects five data points evenly distributed across the input and output histories to predict the intended target, together with a second-order system that smoothes the movement of the cursor. On average, the filter demonstrated a reduction of target acquisition time by a factor of 2.7 in experiments with the patient models.

The potential of modern telecommunications and computing technologies as tools in the delivery and evaluation of assistive technology (AT) has been discussed and has been termed telerehabilitation. The problems of providing AT in rural areas parallels the delivery of health care to rural areas where the proportion of people with chronic illnesses is higher and the means to pay for them is reduced. Large distances mean long travel times, increasing costs associated with any service delivery, and consuming valuable time skilled professionals could be using to provide services elsewhere. The technology available for practising telerehabilitation is significant and expanding at a rapid rate. Currently, plain old telephone systems (POTS) and broad-band videoconferencing equipment, Internet and World Wide Web, and embedded processor systems are most widely available. These technologies continue to evolve as well as emerging technologies such as wearable sensors that will have telehabilitation applications. Issues of payment, safety liability, and licensure need to be resolved, as legislation lags the development of new technologies.

The results of an investigation into the application of parametric system identification procedures to human performance are presented. Stationary and adaptive techniques as well as linear and nonlinear models are discussed. A case study is presented for wheelchair racing that is used to develop multi-input/single-output models. The need for model order reduction and methods for quantizing training data are also discussed. The results suggest that nonlinear autoregressive moving average with exogenous models are better predictors of performance than the other models investigated. The model developed for wheelchair racing suggests that motivation may play a more important role than aerobic or strength training in predicting uncharacteristic performance in elite athletes.>

Wheelchair athletic performance is posed as an optimal control problem. A solution to the optimal control problem using force as the control variable and energy as the constraint is presented, along with the results of an experiment on the dynamics of racing wheelchair propulsion. The parameters derived from results of this experiment and appropriate results from previous investigations are applied to the force/energy model to predict possible US wheelchair athletics records. The predicted results were found to be within 5% of actual US records. This result reflects the belief that performances in wheelchair athletics are beginning to level out. The model represents a possible means for predicting a priori the performance of a wheelchair athlete.>