Mechanical Design Improvement of a Passive Device to Assist Eating in People Living with Movement Disorders

Many people living with neurological disorders, such as cerebral palsy, stroke, muscular dystrophy or dystonia experience upper limb impairments (muscle spasticity, loss of selective motor control, muscle weakness or tremors) and have difficulty to eat independently. The general goal of this project is to develop a new device to assist with eating, aimed at stabilizing the movement of people who have movement disorders. A first iteration of the device was validated with children living with cerebral palsy and showed promising results. This validation however pointed out important drawbacks. This paper presents an iteration of the design which includes a new mechanism reducing the required arm elevation, improving safety through a compliant utensil attachment, and improving damping and other static balancing factors.

Assistive robotic device: evaluation of intelligent algorithms

Assistive robotic devices can be used to help people with upper body disabilities gaining more autonomy in their daily life. Although basic motions such as positioning and orienting an assistive robot gripper in space allow performance of many tasks, it might be time consuming and tedious to perform more complex tasks. To overcome these difficulties, improvements can be implemented at different levels, such as mechanical design, control interfaces and intelligent control algorithms. In order to guide the design of solutions, it is important to assess the impact and potential of different innovations. This paper thus presents the evaluation of three intelligent algorithms aiming to improve the performance of the JACO robotic arm (Kinova Robotics). The evaluated algorithms are 'preset position', 'fluidity filter' and 'drinking mode'. The algorithm evaluation was performed with 14 motorized wheelchair's users and showed a statistically significant improvement of the robot's performance.