Abstract
Humans typically fixate on objects before moving their arm to grasp the object. Patients with ALS disorder can also select the object with their intact eye movement, but are unable to move their limb due to the loss of voluntary muscle control. Though several research works have already achieved success in generating the correct grasp type from their brain measurement, we are still searching for fine controll over an object with a grasp assistive device (orthosis/exoskeleton/robotic arm). Object orientation and object width are two important parameters for controlling the wrist angle and the grasp aperture of the assistive device to replicate a human-like stable grasp. Vision systems are already evolved to measure the geometrical attributes of the object to control the grasp with a prosthetic hand. However, most of the existing vision systems are integrated with electromyography and require some amount of voluntary muscle movement to control the vision system. Due to that reason, those systems are not beneficial for the users with brain-controlled assistive devices. Here, we implemented a vision system which can be controlled through the human gaze. We measured the vertical and horizontal electrooculogram signals and controlled the pan and tilt of a cap-mounted webcam to keep the object of interest in focus and at the centre of the picture. A simple ‘signature’ extraction procedure was also utilized to reduce the algorithmic complexity and system storage capacity. The developed device has been tested with ten healthy participants. We approximated the object orientation and the size of the object and determined an appropriate wrist orientation angle and the grasp aperture size within 22 ms. The combined accuracy exceeded 75%. The integration of the proposed system with the brain-controlled grasp assistive device and increasing the number of grasps can offer more natural manoeuvring in grasp for ALS patients.
Highlights
Prior to initializing the hand movement for grasping the target object, we first visually assess the object to determine its shape, size, and orientation [1,2] which will be further used for manipulating the grasp type, grasp aperture and wrist orientation .The sensory information is processed by the Central Nervous System (CNS) for motor planning in the cortex and implementation using the muscular system [3,4]
An external vision system is required in addition to the grasp assistive device for those patients to identify and process that information to achieve a stable grasp with the grasp assistive devices
In a real-time implementation with a grasp assistive device, these decisions would be transferred to the device and the control will be returned to the user who controls the device with their brain signals
Summary
Prior to initializing the hand movement for grasping the target object, we first visually assess the object to determine its shape, size, and orientation [1,2] which will be further used for manipulating the grasp type, grasp aperture and wrist orientation .The sensory information is processed by the Central Nervous System (CNS) for motor planning in the cortex and implementation using the muscular system [3,4]. Prior to initializing the hand movement for grasping the target object, we first visually assess the object to determine its shape, size, and orientation [1,2] which will be further used for manipulating the grasp type, grasp aperture and wrist orientation . Due to the high amount of GABAergic transmission in oculomotor nuclei [10] Those people can recognize the target object and its shape and size with the visual assessment but not able to convey that information to the assistive device for actual grasp implementation. We have proposed a vision system that can be integrated with the brain-controlled grasp assistive device for the use of ALS patients to restore their grasp activities in future
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