ABSTRACT
Soft wearable robotic hand can assist with hand function for the performance of activities of daily living (ADL). However, existing robotic hands lack a mathematical way to quantify the grip force generated for better controlling the grasp of objects during the performance of ADL. To address this issue, this article presents a soft wearable robotic hand with active control of finger flexion and extension through an elastomeric-based bi-directional soft actuator. This actuator bends and extends by pneumatic actuation at lower air pressure, and a flex sensor embedded inside the actuator measures the angles of the fingers in real-time. Analytical models are established to quantify the kinematic and tip force for gripping of the actuator in terms of the relationship between the input pressure and the bending angle, as well as the output force, and are validated experimentally and by the finite element method. Furthermore, the ability of the soft robotic hand to grasp objects is validated with and without being worn on a human hand. The robotic hand facilitates hand opening and closing by the wearer and successfully assists with grasping objects with sufficient force for ADL-related tasks, and the grip force provided by the actuator is further estimated by the analytical models on two healthy subjects. Results suggest the possibility of the soft robotic hand in providing controllable grip strength in rehabilitation and ADL assistance.
ABSTRACT
In this paper, we present the new personalized 3D printed soft robotic hand for providing rehabilitation training and daily activities assistance to stroke survivors. The Soft-Elastic Composite Actuator (SECA) on the robotic hand is direct 3D printed to accommodate with different finger sizes. Flexion and extension can be actively facilitated on the SECA using the same pressurizing source. Iterative learning model predictive control (ILMPC) method is used to be the control algorithm of SECA. At 160 kPa of maximum input pressure, results show that the actuator bending angles can reach to 137 °, and tip output force can also reach to 2.45 N. Multiple 3D printed SECAs are integrated to a 3D printed hand base and then to be worn on stroke survivors. Two stroke survivors are recruited to evaluate the intention-based rehabilitation training with the 3D printed soft robotic hand, which improvement of their hand function can be observed on performing some daily tasks such as grasping a coin.
Subject(s)
Hand/physiology , Robotics/instrumentation , Stroke Rehabilitation/instrumentation , Algorithms , Equipment Design , Exoskeleton Device , Hand Strength , Humans , Printing, Three-Dimensional , Range of Motion, ArticularABSTRACT
Soft robotic hand/gloves for hand rehabilitation can aid the performance of activities of daily living (ADL). Although existing soft robotic hands can assist with finger flexion, few have addressed finger extension, which is a challenging task for stroke patients due to poststroke spasticity. In this article, we describe the design of a composite actuator, the soft-elastic composite actuator (SECA), to facilitate both finger flexion and extension. A double-segmented SECA comprising two serially connected fiber-reinforced actuators with two bottom torque-compensating layers was fabricated. The SECA bends and extends by pneumatic actuation, and the torque-compensating layers offer an assistive bending moment to configure the bending moment inside the SECA. The principles associated with selection of the torque-compensating layer are described. Analytical models were established to quantify the input pressure and the bending angle of SECA with free bending and when placed on a model compromised hand. The analytical models were validated experimentally and by the finite element method. Moreover, a stroke survivor was recruited to test the new robotic glove integrated with the multiple double-segmented SECA. The robotic glove facilitated hand opening and closing by the patient, and successfully assisted with grasp of a Chinese chess piece and twisting of a towel.
