Lean synthesis and application to lower-limb exoskeletons

Mobility impairments are the most prevalent of all disabilities, affecting the life of nearly one in 20 individuals in developed countries. In the most severe cases, they can have dramatic consequences for the social, mental and physical well-being of those impacted.

Wearable robots, also known as exoskeletons, are devices that can physically help humans achieve certain tasks by compensating a disability or augmenting their capacity. Such devices have already proven to temporarily restore some physical function such as the ability to walk for individuals who had suffered a spinal cord injury (SCI). As of today, their limited performance has however prevented them from being widely accepted and used in community. Their high cost, bulkiness, weight, poor usability and limited intelligence are often regarded as a cause.

Exoskeleton research and development faces several challenges which have so far limited adoption, whether in the medical field or not. These challenges include the unpredictable and complex nature of human users; the important diversity of their pathologies and needs; the long cycles inherent to hardware development and patient testing; together with the difficulty to compare devices' design and mode of action.

In an attempt to cope with these challenges, this thesis introduces the lean synthesis framework. It draws on modularity and digital manufacturing to accelerate and reduce the costs of exoskeleton development process. A collection of modules is presented, along with "DualSKin fabrication", a digital fabrication method particularly adapted to the case of wearable robotics, both used by the framework.

We tested the framework by developing four lower-limb exoskeletons with different use cases. TWIICE, enabling individuals with a motor-complete SCI to walk again; SPRIINT, for running assistance of individuals with transfemoral amputation; INSPIIRE, for the study of gait and postural control; WIITE, enabling individuals with SCI to perform ski-touring.

TWIICE was found to be the lightest exoskeleton capable of climbing stairs and among the fastest of its category. SPRIINT was the first exoskeleton able to assist running in individuals with transfemoral amputation and the fastest exoskeleton for running ever reported. WIITE was the first reported exoskeleton allowing SCI patients to practice ski-touring. INSPIIRE provided important and translatable insights on human gait and postural control. These findings enabled the implementation of a self-balancing controller on TWIICE.

The important variety of these use cases exemplifies the diversity addressable by lean synthesis. New device development and fabrication cycles as short as five weeks were possible thanks to a high degree of reusability. Development and manufacturing costs could also be reduced by leveraging on standard components sharing and recycling. The presented DualSkin fabrication method was found to reduce the production costs of prototype structural parts by 93% with respect to CNC machining while remaining competitive for small series up to 500 parts with respect to low-volume injection molding.

These findings suggest that the proposed implementation of lean synthesis contributed positively to addressing all of the considered challenges without deteriorating performance. Together, these contributions advocate for lean synthesis as a new tool for both wearable robotics research and product development.

Neuroprosthetics to support impaired hand functions: A multidisciplinary approach combining brain-machine interfaces and wearable exoskeletons

Luca Randazzo

Neuroprosthetics, the discipline that aims at interfacing neural systems to artificially engineered devices, has witnessed in recent years important advancements towards the ultimate goal of augmenting and restoring human functions through technology and artificial systems. Research in this field covers a wide range of efforts, from advancing our basic understanding of the neural processes involved into human sensory, motor and cognitive functions, to developing artificial intelligence algorithms for their decoding, to the physical interfacing between artificial devices and the human nervous system and biomechanics. Ultimately, this discipline aims at fusing these systems in order to restore, replace and rehabilitate lost and impaired functions due to motor disabling conditions or traumatic accidents. In this thesis, I present a multidisciplinary approach that aimed at developing a neuroprosthesis for the assistance and restoration of hand functions impaired by neurological disorders or traumatic accidents, such as cerebrovascular accidents and spinal cord injuries. These efforts encompassed the conceptualization and development of a robotic hand exoskeleton and brain-machine interface (BMI) algorithms for its control. Specifically, this thesis focused on the design, development and testing of (i) a novel mechatronic hand exoskeleton to assist hand motions within domestic and clinical settings, (ii) non-invasive BMI approaches based on electroencephalography (EEG) to decode neural correlates of intended hand movements, and on (iii) the closed-loop integration of the proposed exoskeleton and BMI for the sake of providing continuous feedback about ongoing neural modulations through hand motions and to trigger sensorimotor rehabilitation within clinical scenarios. Results showed that the proposed mechatronic system can successfully control hand opening and closing within a fully wearable, portable and lightweight package. The system was tested with users who suffered from motor disabling impairments, showing that it could help them in performing several activities of daily living for the first time since their accidents. From a brain-machine interfacing perspective, this work shows how imagined hand movements can be decoded, through EEG, in parallel with exoskeleton-induced motions, with important implications for the development of more embodied human-machine interaction protocols. Finally, this work shows how the closed-loop control of exoskeleton motions by means of the decoded ongoing neural activity enhances the discriminability of sensorimotor neural patterns and improves the performance of the brain-machine control channel. Overall, the results presented here represent important advancements within the field of neuroprosthetics, with interesting implications for the development of assistive exoskeletal technologies and non-invasive brain-machine interfaces aimed at controlling such systems in clinical or domestic settings, for both assistive and neurorehabilitative purposes.

EPFL2018

From bio-inspired locomotion models To controllers for lower-limb exoskeletons

Florin Dzeladini

Human locomotion shows fascinating abilities which are the results of the interplay between the environment, the biomechanics, the spinal cord, and modulation from higher control centers. How the different structures interact to generate meaningful behavior is an active field of research, and understanding the key principles underlying bipedal locomotion could have a strong impact and important implications in several fields related to both medicine and robotics, such as improved rehabilitation procedures, predicting surgery outcome or facilitated human-robot interaction. In this context, the development of biologically relevant bipedal models that faithfully recapitulate human locomotion are urgently needed. Existing such bio-inspired models usually rely on one of the two following principles: the Central Pattern Generators (CPGs) and the reflexes. In the first part of the thesis, we present a method to introduce a CPGs as feedforward components in a feedback based (i.e. reflex) model of human walking, named neuromuscular model (NMM). The proposed strategy is based on the idea that, in a feedback driven system, the feedforward component can be viewed as a feedback predictor. We implement the feedback predictors using morph oscillators as abstract models of biological CPGs. Thanks to the intrinsic robustness inherited from the feedback pathways, modulation of CPGs network's frequency and amplitudes becomes possible, over a broad range, without affecting the overall walking stability. Furthermore, the modulation of the CPGs network's parameters allowed smooth and stable gait modulation (such as changes in speed and adaptation to increasing slope) suggesting that the idea of using feedback predictor as gait modulator can be extended to a large range of applications, highlighting the role biological CPGs could play on top of a reflex-based rhythmic movement. Building on the NMM, we present, in the second part of the thesis, the implementations of the models as controllers on different ortheses and exoskeletons. Wearable devices designed to assist abnormal gaits require controllers that interact with the user in an intuitive and unobtrusive manner. Here, we rationalized that such a neuromuscular controller could be implemented based on the NMM models. The implementation of NMM model on a controller (NMC) was demonstrated for human healthy subject and was confirmed with experiment on SCI subjects with different devices. Overall, the bio-inspired NMCs successfully demonstrated remarkable versatility in generating gait patterns tuned to the subjects' dynamics and producing near-physiological gait at near-normative speeds. The positive SCI subject-machine interaction stemmed from replacing the subject's impaired function with dynamical virtual muscles that require few sensors. These preliminary but auspicious results have important implications towards the exploitation of natural walking dynamics through understanding human biological behavior in the design of controllers for wearable devices that are amenable to various environmental conditions and promote intuitive and unobtrusive human-machine interaction.

EPFL2019

Socio-Economic Assessment of Fusion Energy Research, Development, Demonstration and Deployment Programme

Denis Bednyagin

Providing safe, clean and affordable energy supply is essential for meeting the basic needs of human society and for supporting economic growth. From the historical perspective, the constantly growing energy use was one of the main factors, which drove the industrialised countries to the current level of prosperity. Meanwhile, in recent decades, the issue of global energy security became a topic of increasing concern in the international policy agenda. On the one hand, the world is facing the problem of exhaustion of most convenient and cheep fuel reserves. The situation is becoming worse, because of the constantly growing demand in developing countries, and the oligopolistic behaviour of major energy exporting countries. On the other hand, the society is becoming more and more sensitive to the environmental pollution problems, caused by the excessive consumption of fossil fuels. In the face of energy security challenge, national governments ought to implement adequate strategies aimed at liberalisation of energy markets, diversification of energy supply mix, enhancement of energy efficiency, encouragement of investments in energy infrastructures, and promotion of innovation in energy sector. In a longer term perspective, the latter point becomes increasingly important, because the world is relying currently on the consumption of non-renewable fossil fuels, and the development of new safe, clean and resource unconstraint energy technologies is vitally needed. In line with this strategy, the major world economies pursue the joint R&D programme on thermonuclear Fusion technology, which represents numerous advantages due to its inherent safety, avoidance of CO2 emissions, relatively small environmental impact, abundance and world-wide uniform distribution of fuel resources. Considering the importance of the projected environmental and economic benefits of Fusion, the questions are raised whether the current level of financial support is sufficient, and what could be the optimal strategy to proceed with the demonstration of Fusion technology, given the time span and potential risks of Fusion RDDD programme. To put these questions into the context, one has to consider the current trends in energy R&D funding, which has seen a drastic decline ( ~50%) over the last three decades. The liberalisation of energy sector poses additional problem due to the fact that free markets partially failure to provide public goods, such as basic science and R&D, because of the so-called spillover effects meaning that the firms are not able to appropriate the integral results of their R&D investments. Regarding the thermonuclear Fusion technology, the decision makers responsible for national energy policies and allocation of public R&D funds may face the following specific questions: What is the expected net socio-economic payoff (social rate of return) of Fusion R&D programme, including both internal and external costs and benefits? What are the reasonable economic arguments that could justify the increase in public funding of the ongoing and future Fusion R&D activities and would stimulate greater involvement of the private sector? What additional value can be obtained through undertaking a more ambitious Fusion R&D programme (accelerated development path), which requires bigger number of experimental facilities, increased funding, and more intense overall efforts of international scientific and industrial community? In order to provide sound arguments for policymakers seeking to optimise public R&D funding, a robust socio-economic evaluation of the whole Fusion research, development, demonstration and deployment (RDDD) programme is needed. At the present stage, prospective analyses of Fusion technology have been emphasised mainly on the investigation of technological issues, estimation of the direct costs of Fusion power and analysis of its potential role in future energy systems. Meanwhile, methodological tools and practical studies aiming at a more comprehensive socio-economic assessment of global long-term energy R&D programmes, such as Fusion, are still incomplete. The primary difficulty concerns the evaluation of positive externalities that may reveal through different types of spillover effects, including but not limited to knowledge, network and market spillovers. While the presence of these effects has been identified in the economic theory and confirmed by empirical studies, their quantitative analysis in the specific case of large scale energy R&D programmes represents some methodological lacuna and deserves further investigation. Another problem relates to the methodology of cost-benefit analysis, which oftentimes ignores the hidden value of R&D projects arising due to the possible flexibility in managerial decisions. In fact, throughout the course of any R&D project, its prospective cash-flows can be significantly improved by pro-active management of different implementation stages, e.g. expanding the production, if market conditions are favourable, or abandoning, if R&D process appears to be unproductive. As a result, the strategic value of any R&D project normally exceeds its net present value (NPV) calculated with the traditional discounted cash flow (DCF) method. Although this strategic approach to capital budgeting, known as Real Options, has been propagated recently in several publications dealing with appraisal of lumpy irreversible investments, its practical application in the context of Fusion RDDD programme has not been mastered yet to the required extent. A particular challenge consists in the need for adequate treatment of different types of uncertainty in the model structure, parameters and input data. Accordingly, the main objective of this thesis consists in complementing the existing studies with an in-depth analysis of the positive externalities (spillover benefits) of Fusion RDDD programme and calculation of its strategic real options value subject to different managerial strategies throughout demonstration and deployment stages. Net social present value of Fusion RDDD programme and potential impact of Fusion R&D activities on the economic performance of the involved private companies are estimated using an integrated modelling framework, which includes the following components: (1) assessment of technological potential for deployment of Fusion power plants based on the simulation of multi-regional long term electricity supply scenarios with PLANELEC model; (2) economic evaluation of Fusion RDDD programme and analysis of different implementation strategies using Real Options model; (3) estimation of the economic value of spillover benefits from participation in Fusion R&D projects at the microeconomic level with the help of financial evaluation model; (4) strategic evaluation of Fusion RDDD programme, taking into account both spillover benefits and real options value, and policy recommendations.

EPFL2010