Human Machine Interaction Force Research Articles

Human hip joint center analysis for biomechanical design of a hip joint exoskeleton

We propose a new method for the customized design of hip exoskeletons based on the optimization of the humanmachine physical interface to improve user comfort. The approach is based on mechanisms designed to follow the natural trajectories of the human hip as the flexion angle varies during motion. The motions of the hip joint center with variation of the flexion angle were measured and the resulting trajectory was modeled. An exoskeleton mechanism capable to follow the hip center’s movement was designed to cover the full motion ranges of flexion and abduction angles, and was adopted in a lower extremity assistive exoskeleton. The resulting design can reduce human-machine interaction forces by 24.1% and 76.0% during hip flexion and abduction, respectively, leading to a more ergonomic and comfortable-to-wear exoskeleton system. The human-exoskeleton model was analyzed to further validate the decrease of the hip joint internal force during hip joint flexion or abduction by applying the resulting design.

Human–machine force interaction design and control for the HIT load-carrying exoskeleton

The HIT load-carrying exoskeleton is designed for enhancing the operator’s load-carrying capability. Human walking has the characteristics of diversity and randomness. It requires that the sensing system of exoskeleton could detect and identify the random motion of human body. In this article, a human–machine force interaction designing architecture is proposed for HIT load-carrying exoskeleton. The human–machine interactive forces at the kinematic terminals (the back and feet) are detected for the human movement identification. Four basic body modalities during the movement process are proposed, which could be automatically identified by the sensing system. The kinematic models for the swing leg and supporting leg are established, respectively. A positional deviation feedback control method based on the interaction force detection is designed. The experiments show that the human–machine interaction force detection at the back and feet and the identification of different body modalities and movement intention are feasible. The interactive forces on the back are far less than the payload, indicating that the exoskeleton has good power-assisted effect.

Adaptive Robust Backstepping Force Control of 1-DOF Joint Exoskeleton for Human Performance Augmentation

The exoskeleton for human performance augmentation is a human-machine interaction system whose control goal is to minimize the human machine interaction force while carrying external loads and following human motion. This paper addresses the dynamics and the interaction force control of a 1-DOF joint exoskeleton. A backstepping control method based on the whole dynamics is proposed to overcome the bandwidth restriction of the commonly used cascade control. Lager bandwidth can be achieved by considering the coupling effect between different layers of dynamics. Moreover, a backstepping adaptive robust control(ARC) algorithm is developed to deal with the effect of parametric uncertainties and uncertain nonlinearities of the system. It is theoretically shown that the proposed adaptive robust backstepping force controller not only achieves good robust performance to model uncertainty, but also faster closed-loop responses and smaller interaction forces. All these theoretical results have been validated by simulation.

Design and Validation of a Compatible 3-Degrees of Freedom Shoulder Exoskeleton With an Adaptive Center of Rotation

This paper outlines an experimentally based design method for a compatible 3-DOF shoulder exoskeleton with an adaptive center of rotation (CoR) by matching the mechanical CoR with the anatomical CoR to reduce human–machine interaction forces and improve comfort during dynamic humeral motion. The spatial–temporal description for anatomical CoR motion is obtained via a specific experimental task conducted on six healthy subjects. The task is comprised of a static section and a dynamic section, both of which are recorded with an infrared motion capture system using body-attached markers. To reduce the influence of human soft tissues, a custom-made four-marker group block was placed on the upper arm instead of using discrete markers. In the static section, the position of anatomical CoR is kept stationary and calculated using a well-known functional method. Based on the static results, the dynamic section determines the statistical relationship between the dynamic CoR position and the humeral orientation using an optimization method when subjects move their upper arm freely in the sagittal and coronal planes. Based on the resolved anatomical CoR motion, a new mechanical CoR model derived from a traditional ball-and-socket joint is applied to match the experimental results as closely as possible. In this mechanical model, the CoR motion in three-dimensional space is adjusted by translating two of the three intersecting joint axes, including the shoulder abduction/adduction and flexion/extension. A set of optimal translation parameters is obtained through proper matching criterion for the two CoRs. Based on the translation parameters, a compatible shoulder exoskeleton was manufactured and compared with a traditional shoulder exoskeleton with a fixed CoR. An experimental test was conducted to validate the CoR motion adaptation ability by measuring the human–machine interaction force during passive shoulder joint motion. The results provide a promising direction for future anthropomorphic shoulder exoskeleton design.

Human-machine interaction force control: using a model-referenced adaptive impedance device to control an index finger exoskeleton

Exoskeleton robots and their control methods have been extensively developed to aid post-stroke rehabilitation. Most of the existing methods using linear controllers are designed for position control and are not suitable for human-machine interaction (HMI) force control, as the interaction system between the human body and exoskeleton is uncertain and nonlinear. We present an approach for HMI force control via model reference adaptive impedance control (MRAIC) to solve this problem in case of index finger exoskeleton control. First, a dynamic HMI model, which is based on a position control inner loop, is formulated. Second, the theoretical MRAC framework is implemented in the control system. Then, the adaptive controllers are designed according to the Lyapunov stability theory. To verify the performance of the proposed method, we compare it with a proportional-integral-derivative (PID) method in the time domain with real experiments and in the frequency domain with simulations. The results illustrate the effectiveness and robustness of the proposed method in solving the nonlinear HMI force control problem in hand exoskeleton.

Empowering and Assisting Natural Human Mobility: The Simbiosis Walker

This paper presents the complete development of the Simbiosis Smart Walker. The device is equipped with a set of sensor subsystems to acquire user-machine interaction forces and the temporal evolution of user's feet during gait. The authors present an adaptive filtering technique used for the identification and separation of different components found on the human-machine interaction forces. This technique allowed isolating the components related with the navigational commands and developing a Fuzzy logic controller to guide the device. The Smart Walker was clinically validated at the Spinal Cord Injury Hospital of Toledo - Spain, presenting great acceptability by spinal chord injury patients and clinical staff.