No abstract

Human-worn rehabilitation exoskeletons have the potential to make therapeutic exercises increasingly accessible to disabled individuals while reducing the cost and labor involved in rehabilitation therapy. In this work, we propose a novel human-model-in-the-loop framework for virtual prototyping (design, control and experimentation) of rehabilitation exoskeletons by merging computational musculoskeletal analysis with simulation-based design techniques. The framework allows to iteratively optimize design and control algorithm of an exoskeleton using simulation. We introduce biomechanical, morphological, and controller measures to quantify the performance of the device for optimization study. Furthermore, the framework allows one to carry out virtual experiments for testing specific "what-if" scenarios to quantify device performance and recovery progress. To illustrate the application of the framework, we present a case study wherein the design and analysis of an index-finger exoskeleton is carried out using the proposed framework.

Our long term goal is to develop a new generation of robotic-prosthetic hands that will incorporate key anatomical features of the human hand, especially, the passive dynamics defined by the joint stifftness and damping properties. This paper presents a design of a mechanism that can measure the passive moment of the human hand joint. We designed a motor-driven system, integrating a noninvasive and infrared motion capture system, that can control and record the angle, angular velocity and passive forces of the metacarpophalangeal (MCP) joint in the index finger. A total of 19 subjects participated in the experiments. We conducted two experiments to estimate the total passive moments of the MCP joint from the human subjects. The results showed that the novel design of the mechanism collected the precise passive moments and kinematic data, thus allowing us to develop a comprehensive understanding of the passive properties of the human hand joints.

No abstract

We present a piezoelectric energy harvester that is assembled on a soft robot and converts its mechanical locomotion to electricity. The piezoelectric transducers are used in various applications because of their durability, flexibility, and self-powering characteristics. In this study, we demonstrate a piezoelectric transducer that converts the soft robot’s motion to electricity to provide power for the soft robot sensors such as strain sensors. The system consists of a piezoelectric strip that is placed on the soft robot. External stimuli provided by pneumatic pressurization actuates the soft robot and moves it forward. The inflation and deflation of the soft robot cause mechanical deformation which results in a voltage generated at the piezoelectric layer. We consider the piezoelectric harvester elongator type mechanism that works by mechanical extension and compression. An AC-DC conversion circuit is used to obtain 1.5–2 V DC output voltage from the piezoelectric harvester to charge a capacitor for use of sensors. AC-DC conversion circuit consists of a resistance in series with the piezoelectric, a full-bridge rectification circuit, and an LM317T voltage regulator. The energy harvesting mechanism offers an alternative power source that reduces the external electrical power requirements of the robot and extends the lifetime of onboard batteries.

Passive properties of the human hands, defined by the joint stiffness and damping, play an important role in hand biomechanics and neuromuscular control. Introduction of mechanical element that generates humanlike passive properties in a robotic form may lead to improved grasping and manipulation abilities of the next generation of robotic hands. This paper presents a novel mechanism, which is designed to conduct experiments with the human subjects in order to develop mathematical models of the passive properties at the metacarpophalangeal (MCP) joint. We designed a motor-driven system that integrates with a noninvasive and infrared motion capture system, and can control and record the MCP joint angle, angular velocity, and passive forces of the MCP joint in the index finger. A total of 19 subjects participated in the experiments. The modular and adjustable design was suitable for variant sizes of the human hands. Sample results of the viscoelastic moment, hysteresis loop, and complex module are presented in the paper. We also carried out an error analysis and a statistical test to validate the reliability and repeatability of the mechanism. The results show that the mechanism can precisely collect kinematic and kinetic data during static and dynamic tests, thus allowing us to further understand the insights of passive properties of the human hand joints. The viscoelastic behavior of the MCP joint showed a nonlinear dependency on the frequency. It implies that the elastic and viscous component of the hand joint coordinate to adapt to the external loading based on the applied frequency. The findings derived from the experiments with the mechanism can provide important guidelines for design of humanlike compliance of the robotic hands.

The passive joint behavior in the human hand is the result of passive properties of the muscle-tendon units (MTUs) and the elasticity of the soft tissues across the joint. The purpose of the study was to investigate the relative contribution of the MTUs to the net passive torque of the index finger metacarpophalangeal (MCP) joint in flexion and extension. We developed mathematical models to explicitly determine the passive contributions of the seven MTUs to the MCP joint torque. We then compared the computed MTU passive torque to the net passive torque derived from data collected from human subjects. The results show that the MTU properties did not produce the greatest contribution to the the total passive joint torque, especially, at the extremities of the range of motion are dues to factors such as the soft joint tissues. Also, the extrinsic MTUs produced much higher passive joint torques compared to the intrinsic MTUs, and the intrinsic MTUs presented small counterbalance to the net MTU torque in extension. The revelation that most of the net passive joint torque is due to the joint tissue and not due to the MTU elasticity is important for understanding the human hand controls, and also for designing the next generation of robotic hands.978-1-4244-7709-8/10/$26.00 ©2010 IEEE