Personal Mobility With Synchronous Trunk-Knee Passive Exoskeleton: Optimizing Human-Robot Energy Transfer

We present a personal mobility device for lower-body impaired users through a light-weighted exoskeleton on wheels. On its core, a novel passive exoskeleton provides postural transition leveraging natural body postures with support to the trunk on sit-to-stand and stand-to-sit (STS) transitions by a single gas spring as an energy storage unit. We propose a direction-dependent coupling of knees and hip joints through a double-pulley wire system, transferring energy from the torso motion towards balancing the moment load at the knee joint actuator. Herewith, the exoskeleton maximizes energy transfer and the naturalness of the user's movement. We introduce an embodied user interface for hands-free navigation through a torso pressure sensing with minimal trunk rotations, resulting on average $19^{\circ} \pm 13^{\circ}$ on six unimpaired users. We evaluated the design for STS assistance on 11 unimpaired users observing motions and muscle activity during the transitions. Results comparing assisted and unassisted STS transitions validated a significant reduction (up to $68\%$ $p<0.01$) at the involved muscle groups. Moreover, we showed it feasible through natural torso leaning movements of $+12^{\circ}\pm 6.5^{\circ}$ and $- 13.7^{\circ} \pm 6.1^{\circ}$ for standing and sitting, respectively. Passive postural transition assistance warrants further work on increasing its applicability and broadening the user population.Comment: IEEE/ASME Transactions on Mechatronics. 2022. 11 pages. doi: 10.1109/TMECH.2021.313545

Human sit-to-stand transfer modeling towards intuitive and biologically-inspired robot assistance

© 2016, Springer Science+Business Media New York. Sit-to-stand (STS) transfers are a common human task which involves complex sensorimotor processes to control the highly nonlinear musculoskeletal system. In this paper, typical unassisted and assisted human STS transfers are formulated as optimal feedback control problem that finds a compromise between task end-point accuracy, human balance, energy consumption, smoothness of motion and control and takes further human biomechanical control constraints into account. Differential dynamic programming is employed, which allows taking the full, nonlinear human dynamics into consideration. The biomechanical dynamics of the human is modeled by a six link rigid body including leg, trunk and arm segments. Accuracy of the proposed modelling approach is evaluated for different human healthy and patient/elderly subjects by comparing simulations and experimentally collected data. Acceptable model accuracy is achieved with a generic set of constant weights that prioritize the different criteria. Finally, the proposed STS model is used to determine optimal assistive strategies suitable for either a person with specific body segment weakness or a more general weakness. These strategies are implemented on a robotic mobility assistant and are intensively evaluated by 33 elderlies, mostly not able to perform unassisted STS transfers. The validation results show a promising STS transfer success rate and overall user satisfaction

Design and control of a sit-to-stand assistive device based on analysis of kinematics and dynamics

Sit-to-stand is a common activity in daily life. It is difficult for the elderly and patients with lower limb disorders to complete this motion due to limb pain, muscle weakness, partial loss of motor control function, and physical defects in joints. An STS assistive device is a piece of automated medical equipment that can facilitate rehabilitation training for patients with lower limb disorders and improve their lower limb function. In this paper, we introduce a 3-DOF series type STS assistive device. First, we selected 26 healthy adults to carry out an STS transfer experiment, and we obtained the trajectory and velocity of each joint and the law of plantar pressure during STS motion. Second, based on the above kinematics and dynamics law, a 3-DOF series mechanism was designed. Through forward and inverse kinematics analysis, the relationship between the end-effector and the linear actuator was established. The trajectory planning of the end-effector was carried out according to the natural STS transfer trajectory, and the law of the linear actuator was obtained. The trajectory planning was verified by ADAMS. Finally, the Arduino controller was used to build the control system of the STS assistive device, and the prototype experiment was carried out

Human-robot interaction for assistive robotics

This dissertation presents an in-depth study of human-robot interaction (HRI) withapplication to assistive robotics. In various studies, dexterous in-hand manipulation is included, assistive robots for Sit-To-stand (STS) assistance along with the human intention estimation. In Chapter 1, the background and issues of HRI are explicitly discussed. In Chapter 2, the literature review introduces the recent state-of-the-art research on HRI, such as physical Human-Robot Interaction (HRI), robot STS assistance, dexterous in hand manipulation and human intention estimation. In Chapter 3, various models and control algorithms are described in detail. Chapter 4 introduces the research equipment. Chapter 5 presents innovative theories and implementations of HRI in assistive robotics, including a general methodology of robotic assistance from the human perspective, novel hardware design, robotic sit-to-stand (STS) assistance, human intention estimation, and control

Predictive Dynamic Simulation of Healthy Sit-to-Stand Movement

This thesis situates itself at the intersection of biomedical modelling and predictive simulation to synthesize healthy human sit-to-stand movement. While the importance of sit-to-stand to physical and social well-being is known, the reasons for why and how people come to perform sit-to-stand the way we do is largely unknown. This thesis establishes the determinants of sit-to-stand in healthy people so that future researchers may investigate the effects of compromised health on sit-to-stand and then explore means of intervening to preserve and restore this motion. Previous researchers have predicted how a person rises from seated. However aspects of their models, most commonly contact and muscle models, are biomechanically inconsistent and restrict their application. These researchers also have not validated their prediction results. To address these limitations and further the study of sit-to-stand prediction, the underlying themes of this thesis are in biomechanical modelling, predictive simulation, and validation. The goal of predicting sit-to-stand inspired the creation of three new models: a model of biomechanics, a model of motion, and performance criteria as a model of preference. First, the human is represented as three rigid links in the sagittal plane. As buttocks are kinetically important to sit-to-stand, a new constitutive model of buttocks is made from experimental force-deformation data. Ten muscles responsible for flexion and extension of the hips, knees, and ankles are defined in the model. Second, candidate sit-to-stand trajectories are described geometrically by a set of Bézier curves, for the first time. Third, with the assumption that healthy people naturally prioritize mechanical efficiency, disinclination to a motion is described as a cost function of joint torques, muscle stresses, and physical infeasibility including slipping and falling. This new dynamic optimization routine allows for motions of gradually increasing complexity, by adding control points to the Bézier curves, while the model's performance is improving. By comparing the predictive simulation results to normative sit-to-stand as described in the literature, for the first time, it is possible to say that the use of these models and optimal control strategy together has produced motions characteristic of healthy sit-to-stand. This work bridges the gap between predictive simulation results and experimental human results and in doing so establishes a benchmark in sit-to-stand prediction. In predicting healthy sit-to-stand, it makes a necessary step toward predicting pathological sit-to-stand, and then to predicting the results of intervention to inform medical design and planning

The Development of an assistive chair for elderly with sit to stand problems

A thesis submitted to the University of Bedfordshire in partial fulfilment of the requirements for the degree of Doctor of PhilosophyStanding up from a seated position, known as sit-to-stand (STS) movement, is one of the most frequently performed activities of daily living (ADLs). However, the aging generation are often encountered with STS issues owning to their declined motor functions and sensory capacity for postural control. The motivated is rooted from the contemporary market available STS assistive devices that are lack of genuine interaction with elderly users. Prior to the software implementation, the robot chair platform with integrated sensing footmat is developed with STS biomechanical concerns for the elderly. The work has its main emphasis on recognising the personalised behavioural patterns from the elderly users’ STS movements, namely the STS intentions and personalised STS feature prediction. The former is known as intention recognition while the latter is defined as assistance prediction, both achieved by innovative machine learning techniques. The proposed intention recognition performs well in multiple subjects scenarios with different postures involved thanks to its competence of handling these uncertainties. To the provision of providing the assistance needed by the elderly user, a time series prediction model is presented, aiming to configure the personalised ground reaction force (GRF) curve over time which suggests successful movement. This enables the computation of deficits between the predicted oncoming GRF curve and the personalised one. A multiple steps ahead prediction into the future is also implemented so that the completion time of actuation in reality is taken into account

Model-Based Optimization for the Analysis of Human Movement and the Design of Rehabilitation Devices

Human motions result from a complex and well-coordinated interaction between the body segments. Walking and the sit-to-stand transfer are amongst the most challenging human motion in terms of coordination and internal loads, respectively. We propose model-based nonlinear optimal control methods to reconstruct and synthesize these motions while considering the dynamics of the motion over the whole time horizon. The redundant and highly nonlinear character of the computed motions encourages to discretize the optimization problem according to direct multiple-shooting methods. The goal is to identify principles which enable us to describe the patterns of these motions. We approach human walking from the perspective of unimpaired subjects and subjects walking with unilateral transfemoral prostheses. Their walking motion is reconstructed from motion capture data using subject-specific threedimensional multibody models. The motion of the models is fitted to the recorded data for a whole stride in a least-squares sense in multi-stage optimal control problems. Analyzing the reconstructed motion for the individual foot placement of the subjects suggests that it relates with the Capturability concept: foot locations are chosen by the subjects which enable a balance between the inherently conflicting goals of effortless progression and quick response to perturbations. In addition, the modulation of the ground collision impact forces at heel strike is found to play a major role in the step-by-step stability strategy. Based on these findings, we propose Capturability as a complementary criterion to the established clinical stability assessment methods. The sit-to-stand motion is particularly demanding for humans with mobility impairments, due to the high joint loads required to lift the body into the standing pose. We synthesize optimal sit-to-stand by solving two-stage optimal control problems. We presume that the sit-to-stand motion is substantially characterized by a preparation phase prior to the actual lift-off. Full body models are established with dynamic model parameters which specifically represent elderly humans from different levels of mobility. For impaired subjects, mobility support is assumed to be provided by generic support actions. The optimization computations result in different patterns which include significant arm motion in both phases. Therefore, the results support our approach to choose a full body representation of the human as well as to consider two stages in the optimal control problem. The computation of optimal assisted sit-to-stand motions of impaired humans offers the opportunity to optimize design parameters for mobility assistance devices providing adequate support. Based on the support actions for the sit-to-stand motions computed for two different levels of impairment, optimal mechanical design parameters for two different sit-to-stand assistance devices are generated. Our approach to separate the human-device interaction at their interface ensures that the optimal support provided to the human by the device is not compromised by any dynamic coupling between them. Solving large-scale nonlinear optimal control problems with multiple stages, we obtain design parameters for the devices which are optimal in terms of the workspace and the mechanical effort required