Driving interface based on tactile sensors for electric wheelchairs or trolleys

Control and Evaluation of a Motorized Attendant Wheelchair With Haptic Interface

Attendant wheelchairs provide a means to transport patients or mobility to people with walking disability. They can be attendant propelled, which are highly maneuverable in confined spaces, but offer no power assistance. Also, they can be electric powered with joystick control interface, which provides power assistance, but not as maneuverable as the attendant propelled wheelchair. With the objective of providing power assistance and having excellent maneuverability, this paper presents a motorized attendant wheelchair with haptic interface. Its control approach is based on virtual/desired dynamics, which is not the true dynamics of the wheelchair, but a mathematical model describing the motion behavior of a desired system. The desired dynamics takes the user's applied force/torque and yields desired velocities of the wheelchair. In the evaluation, tasks in confined spaces that require a lot of maneuvers were given and performed using the motorized wheelchair with haptic and joystick control interfaces. The results in terms of task completion times showed that motorized wheelchair with haptic significantly outperformed the motorized wheelchair with joystick interface. In addition, the performance of the motorized with haptic interface and attendant propelled wheelchairs were evaluated at two different loads. At heavy load, the task completion times of motorized wheelchair with haptic interface were comparable to the attendant propelled wheelchair.

Assistive Handlebar Based on Tactile Sensors: Control Inputs and Human Factors

Tactile sensors can be used to build human-machine interfaces, for instance in isometric joysticks or handlebars. When used as input sensor device for control, questions arise related to the contact with the human, which involve ergonomic aspects. This paper focuses on the example application of driving a powered wheelchair as attendant. Since other proposals use force and torque sensors as control input variables, this paper explores the relationship between these variables and others obtained from the tactile sensor. For this purpose, a handlebar is instrumented with tactile sensors and a 6-axis force torque sensor. Several experiments are carried out with this handlebar mounted on a wheelchair and also fixed to a table. It is seen that it is possible to obtain variables well correlated with those provided by force and torque sensors. However, it is necessary to contemplate the influence of issues such as the gripping force of the human hand on the sensor or the different kinds of grasps due to different physical constitutions of humans and to the inherent random nature of the grasp. Moreover, it is seen that a first step is necessary where the contact with the hands has to stabilize, and its characteristics and settle time are obtained.

Tactile Sensor-Based Steering as a Substitute of the Attendant Joystick in Powered Wheelchairs

Attendant joysticks of powered wheelchairs are devices oriented to help caregivers. Diseases and disabilities such as dementia, spinal cord injuries or blindness make the user unable to drive the chair by his or her own. However, this device is not intuitive to use, especially for old people. Proper processing of the information provided by two tactile sensors in the handlebar achieves control signals that allow an easy and intuitive driving. This is done in this paper, where the performance of this approach is evaluated in comparison with that of the joystick by means of objective measurements as well as questionnaires to obtain the subjective perception of the participants in the experiments. The results show a better performance of the handlebar in terms of error in following a trajectory, collisions with the surrounding furniture, and user feeling related to ease of use, comfort, required training, usefulness, safety, and fatigue.

A Study of a Handrim-Activated Power-Assist Wheelchair Based on a Non-Contact Torque Sensor

Demand for wheelchairs is increasing with growing numbers of aged and disabled persons. Manual wheelchairs are the most commonly used assistive device for mobility because they are convenient to transport. Manual wheelchairs have several advantages but are not easy to use for the elderly or those who lack muscular strength. Therefore, handrim-activated power-assist wheelchairs (HAPAW) that can aid driving power with a motor by detecting user driving intentions through the handrim are being researched. This research will be on HAPAW that judge user driving intentions by using non-contact torque sensors. To deliver the desired motion, which is sensed from handrim rotation relative to a fixed controller, a new driving wheel mechanism is designed by applying a non-contact torque sensor, and corresponding torques are simulated. Torques are measured by a driving wheel prototype and compared with simulation results. The HAPAW prototype was developed using the wheels and a driving control algorithm that uses left and right input torques and time differences are used to check if the non-contact torque sensor can distinguish users' driving intentions. Through this procedure, it was confirmed that the proposed sensor can be used effectively in HAPAW.

A Driving Behaviour Model of Electrical Wheelchair Users

In spite of the presence of powered wheelchairs, some of the users still experience steering challenges and manoeuvring difficulties that limit their capacity of navigating effectively. For such users, steering support and assistive systems may be very necessary. To appreciate the assistance, there is need that the assistive control is adaptable to the user's steering behaviour. This paper contributes to wheelchair steering improvement by modelling the steering behaviour of powered wheelchair users, for integration into the control system. More precisely, the modelling is based on the improved Directed Potential Field (DPF) method for trajectory planning. The method has facilitated the formulation of a simple behaviour model that is also linear in parameters. To obtain the steering data for parameter identification, seven individuals participated in driving the wheelchair in different virtual worlds on the augmented platform. The obtained data facilitated the estimation of user parameters, using the ordinary least square method, with satisfactory regression analysis results.