Human-machine-centered design and actuation of lower limb prosthetic systems

People with lower limb loss or congenital limb absence require a technical substitute that restores biomechanical function and body integrity. In the last decades, mechatronic prostheses emerged and especially actuated ones increased the biomechanical functionality of their users. Yet, various open issues regarding the energy efficiency of powered systems and the impact of user-experience of the prosthesis on technical design remain. As tackeling the latter aspect urgently requires the consideration of user demands, this thesis proposes a novel human-machine-centered design (HMCD) approach for lower limb prosthetics. Further, it contributes to the design and control of elastic (prosthetic) actuation. The HMCD approach describes a framework that equally considers technical and human factors. Therefore, seven human factors influencing lower limb prosthetic design are determined, analyzed, and modeled using human survey data: Satisfaction, Feeling of Security, Body Schema Integration, Support, Socket, Mobility, and Outer Appearance. Based on the application of quality function deployment (QFD), those factors can be considered as a HMCD focus in systems engineering. As an exemplary application, a powered prosthetic knee concept is elaborated with the HMCD approach. The comparison of the HMCD focus with a purely technical one, which is determined with a control group, reveals distinct differences in the weighting of requirements. Hence, the proposed method should lead to different prosthetic designs that might improve the subjective user-experience. To support this by integrating users throughout the systems engineering process, two concepts for human-in-the-loop experiments are suggested. As an enabling technology of powered lower limb prostheses, variable (series) elastic actuation and especially such with variable torsion stiffness (VTS) is investigated. Inverse dynamics simulations with synthetic and human trajectories as well as experiments show that the consideration of the actuator inertia is crucial: Only by including it in advanced models, the whole range of natural dynamics and antiresonance can be exploited to minimize power consumption. A corresponding control strategy adapts the actuator to achieve energy efficiency over a wide range of operational states using these models. The exemplary design of the powered prosthetic knee with respect to the HMCD prioritization of requirements confirms the fundamental suitability of VTS for integration in prosthetic components. In this, considering actuator inertia enables the determination of an optimal stiffness for serial elastic actuation of the human knee during walking that is not found in previous studies. A first simulation considering the changed dynamics of prosthetic gait indicates the potential to reveal lower design requirements. The designed knee concept combines promising biomechanical functionality and long operating time due to elastic actuation and energy recuperation. Beyond lower limb prosthetics, the proposed HMCD framework can be used in other applications with distinct human-machine interrelations by adjusting the human and technical factors. Likewise, the insights into variable elastic actuation design and control can be transferred to other systems demanding energy-efficient performance of cyclic tasks

Low-cost Sensor Glove with Force Feedback for Learning from Demonstrations using Probabilistic Trajectory Representations

Sensor gloves are popular input devices for a large variety of applications including health monitoring, control of music instruments, learning sign language, dexterous computer interfaces, and tele-operating robot hands. Many commercial products as well as low-cost open source projects have been developed. We discuss here how low-cost (approx. 250 EUROs) sensor gloves with force feedback can be build, provide an open source software interface for Matlab and present first results in learning object manipulation skills through imitation learning on the humanoid robot iCub.Comment: 3 pages, 3 figures. Workshop paper of the International Conference on Robotics and Automation (ICRA 2015

How Cognitive Models of Human Body Experience Might Push Robotics

In the last decades, cognitive models of multisensory integration in human beings have been developed and applied to model human body experience. Recent research indicates that Bayesian and connectionist models might push developments in various branches of robotics: assistive robotic devices might adapt to their human users aiming at increased device embodiment, e.g., in prosthetics, and humanoid robots could be endowed with human-like capabilities regarding their surrounding space, e.g., by keeping safe or socially appropriate distances to other agents. In this perspective paper, we review cognitive models that aim to approximate the process of human sensorimotor behavior generation, discuss their challenges and potentials in robotics, and give an overview of existing approaches. While model accuracy is still subject to improvement, human-inspired cognitive models support the understanding of how the modulating factors of human body experience are blended. Implementing the resulting insights in adaptive and learning control algorithms could help to taylor assistive devices to their user's individual body experience. Humanoid robots who develop their own body schema could consider this body knowledge in control and learn to optimize their physical interaction with humans and their environment. Cognitive body experience models should be improved in accuracy and online capabilities to achieve these ambitious goals, which would foster human-centered directions in various fields of robotics

Peripheral neuroergonomics - An elegant way to improve Human-Robot Interaction?

The day seems not too far away, in which robots will be an active part of our daily life, just like electric appliances already are. Hence, there is an increasing need for paradigms, tools, and techniques to design proper human-robot interaction in a human-centered fashion (Beckerle et al., 2017). To this end, appropriate Human-Machine Interfaces (HMIs) are required, and there is a growing body of research showing how the Peripheral Nervous System (PNS) might be the ideal channel through which this interaction could proficiently happen

Impact of friction and gait parameters on the optimization of series elastic actuators for gait assistance

Elastic actuators feature increased energy efficiency and improved human-robot interaction compared to directly driven concepts for active orthoses and prostheses. Structure and parameters of the elastic actuation system are often designed via a model-based minimization of energy consumption based on gait data gained from healthy individuals. However, natural motion exhibits variability among individuals and may not consider requirements of persons using assistive devices. A parametric study is performed examining the impact of varying gait characteristics on the energy consumption and constraints of an optimized (clutchable) series elastic actuator of the knee joint. Furthermore, friction parameters are varied to analyze the impact on actuator constraints. Results of the parametric study indicate increased energy consumption for a slower cadence compared to the healthy gait data for both systems. The clutchable series elastic actuator is less impacted by constraints than the series elastic actuator. The utilized models are evaluated experimentally at a test bench, indicating good accordance to the measured energy consumption. The results highlight the interrelation of friction and gait parameters with energy consumption and actuator constraints and indicate that the optimization procedure for the actuator design requires detailed models of component efficiency as well as subject-specific gait characteristics.Postprint (author's final draft

A Human−Computer Interface Replacing Mouse and Keyboard for Individuals with Limited Upper Limb Mobility

People with physical disabilities in their upper extremities face serious issues in using classical input devices due to lacking movement possibilities and precision. This article suggests an alternative input concept and presents corresponding input devices. The proposed interface combines an inertial measurement unit and force sensing resistors, which can replace mouse and keyboard. Head motions are mapped to mouse pointer positions, while mouse button actions are triggered by contracting mastication muscles. The contact pressures of each fingertip are acquired to replace the conventional keyboard. To allow for complex text entry, the sensory concept is complemented by an ambiguous keyboard layout with ten keys. The related word prediction function provides disambiguation at word level. Haptic feedback is provided to users corresponding to their virtual keystrokes for enhanced closed-loop interactions. This alternative input system enables text input as well as the emulation of a two-button mouse

Mechatronic designs for a robotic hand to explore human body experience and sensory-motor skills: a Delphi study

To bridge the gap between users' expectations and technological solutions, a better understanding of human body experience and sensory-motor skills is mandatory. This could pave the way towards a novel generation of robotic hands, which can be successfully employed in everyday life e.g. in prosthetics and assistive robotics. Available robotic hands are still far from matching the requirements of the corresponding experimental and real-world applications, e.g. fast motions might be achieved at the expense of accuracy. Knowledge of the users' sensory-motor skills can guide technical developments, e.g. prosthetic design processes. This paper presents design solutions developed in a Delphi study. Explorative questionnaires are prepared to acquire and elaborate expert opinions to improve the design of previously developed robotic anthropomorphic hands. By gathering and fusing expert opinions, novel robotic hand and wrist concepts specifically optimized regarding body experience and sensory-motor skill research are developed. In three rounds, experts with experience in robotic hand design and/or control analyze, develop, and rank solutions for mechanisms, actuators, and control, which result in overall design concepts. The technical concepts and implications resulting from the study are discussed considering psychological and biomechanical aspects

Feel-good robotics: requirements on touch for embodiment in assistive robotics

The feeling of embodiment, i.e., experiencing the body as belonging to oneself and being able to integrate objects into one’s bodily self-representation, is a key aspect of human self-consciousness and has been shown to importantly shape human cognition. An extension of such feelings toward robots has been argued as being crucial for assistive technologies aiming at restoring, extending, or simulating sensorimotor functions. Empirical and theoretical work illustrates the importance of sensory feedback for the feeling of embodiment and also immersion; we focus on the the perceptual level of touch and the role of tactile feedback in various assistive robotic devices. We critically review how different facets of tactile perception in humans, i.e., affective, social, and self-touch, might influence embodiment. This is particularly important as current assistive robotic devices – such as prostheses, orthoses, exoskeletons, and devices for teleoperation–often limit touch low-density and spatially constrained haptic feedback, i.e., the mere touch sensation linked to an action. Here, we analyze, discuss, and propose how and to what degree tactile feedback might increase the embodiment of certain robotic devices, e.g., prostheses, and the feeling of immersion in human-robot interaction, e.g., in teleoperation. Based on recent findings from cognitive psychology on interactive processes between touch and embodiment, we discuss technical solutions for specific applications, which might be used to enhance embodiment, and facilitate the study of how embodiment might alter human-robot interactions. We postulate that high-density and large surface sensing and stimulation are required to foster embodiment of such assistive devices