Normal gait needs both proprioceptive and visual feedback to the nervous system to effectively control the rhythmicity of motor movement. Current preprogrammed exoskeletons provide only visual feedback with no user control over the foot trajectory. We propose an intuitive controller where hand trajectories are mapped to control contralateral foot movement. Our study shows that proprioceptive feedback provided to the users hand in addition to visual feedback result in better control during virtual ambulation than visual feedback alone. Hand trajectories resembled normal foot trajectories when both proprioceptive and visual feedback was present. Our study concludes that haptic feedback is essential for both temporal and spatial aspects of motor control in rhythmic movements.

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Human gait requires both haptic and visual feedback to generate and control rhythmic movements, and navigate environmental obstacles. Current lower extremity wearable exoskeletons that restore gait to individuals with paraplegia due to spinal cord injury rely completely on visual feedback to generate limited pre-programmed gait variations, and generally provide little control by the user over the gait cycle. As an alternative to this limitation, we propose user control of gait in real time using healthy upper extremities. This paper evaluates the feedback conditions required for the hands to generate complex rhythmic trajectories that resemble gait trajectories. This paper involved 18 subjects who performed a virtual locomotor task, where contralateral hand movements were mapped to control virtual feet in three feedback conditions: haptic only, visual only, and haptic and visual. The results indicate that haptic feedback in addition to visual feedback is required to produce rhythmic hand trajectories similar to gait trajectories.

Lower extremity exoskeletons offer the potential to restore ambulation to individuals with paraplegia due to spinal cord injury. However, they often rely on preprogrammed gait, initiated by switches, sensors, and/or EEG triggers. Users can exercise only limited independent control over the trajectory of the feet, the speed of walking, and the placement of feet to avoid obstacles. In this paper, we introduce and evaluate a novel approach that naturally decodes a neuromuscular surrogate for a user's neutrally planned foot control, uses the exoskeleton's motors to move the user's legs in real-time, and provides sensory feedback to the user allowing real-time sensation and path correction resulting in gait similar to biological ambulation. Users express their desired gait by applying Cartesian forces via their hands to rigid trekking poles that are connected to the exoskeleton feet through multi-axis force sensors. Using admittance control, the forces applied by the hands are converted into desired foot positions, every 10 milliseconds (ms), to which the exoskeleton is moved by its motors. As the trekking poles reflect the resulting foot movement, users receive sensory feedback of foot kinematics and ground contact that allows on-the-fly force corrections to maintain the desired foot behavior. We present preliminary results showing that our novel control can allow users to produce biologically similar exoskeleton gait.

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The "3-DOF Admittance Control Robotic Arm with a 3D Virtual Game" is a senior capstone design project for the New Jersey Institute of Technology. This robotic arm is designed for facilitated training of the hemiparetic hand i.e. for patients in need for rehabilitation of their upper extremities. The virtual 3D game is an interactive environment that will track the movements of the robotic arm. In this paper, the software architecture and robot platform is presented. A basic overview of system flow is as follows: a user positions their finger into the end effector of the robotic arm and presses on a strain gauge to input a force; this force is feed into the admittance control paradigm to produce a coordinate position; this position is relayed to the game to move the game cursor accordingly and into an inverse kinematics algorithm that calculates the angles for this position; finally these angles are feed into motors that make up the 3degrees of freedom for the robotic arm to move the links to this position.

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