RESUMEN
Lower-limb prostheses aim to restore ambulatory function for individuals with lower-limb amputations. While the design of lower-limb prostheses is important, this paper focuses on the complementary challenge - the control of lower-limb prostheses. Specifically, we focus on powered prostheses, a subset of lower-limb prostheses, which utilize actuators to inject mechanical power into the walking gait of a human user. In this paper, we present a review of existing control strategies for lower-limb powered prostheses, including the control objectives, sensing capabilities, and control methodologies. We separate the various control methods into three main tiers of prosthesis control: high-level control for task and gait phase estimation, mid-level control for desired torque computation (both with and without the use of reference trajectories), and low-level control for enforcing the computed torque commands on the prosthesis. In particular, we focus on the high- and mid-level control approaches in this review. Additionally, we outline existing methods for customizing the prosthetic behavior for individual human users. Finally, we conclude with a discussion on future research directions for powered lower-limb prostheses based on the potential of current control methods and open problems in the field.
RESUMEN
Lower-limb exoskeletons are a promising option to increase the mobility of persons with leg impairments in a near future. However, it is still challenging for them to ensure the necessary stability and agility to face obstacles, particularly the variety that makes the urban environment. That is why most of the lower-limb exoskeletons must be used with crutches: the stability and agility features are deferred to the patient. Clinical experience shows that the use of crutches not only leads to shoulder pain and exhaustion, but also fully occupies the hands for daily tasks. In November 2020, Wandercraft presented Atalante Evolution, the first self-stabilized and crutch-less exoskeleton, to the powered exoskeleton race of the Cybathlon 2020 Global Edition. The Cybathlon aims at promoting research and development in the field of powered assistive technology to the public, contrary to the Paralympics where only participants with unpowered assistive technology are allowed. The race is designed to represent the challenges that a person could face every day in their environment: climbing stairs, walking through rough terrain, or descending ramps. Atalante Evolution is a 12 degree-of-freedom exoskeleton capable of moving dynamically with a complete paraplegic person. The challenge of this competition is to generate and execute new dynamic motions in a short time, to achieve different tasks. In this paper, an overview of Atalante Evolution system and of our framework for dynamic trajectory generation based on the direct collocation method will be presented. Next, the flexibility and efficiency of the dynamic motion generation framework are demonstrated by our tools developed for generating the important variety of stable motions required by the competition. A smartphone application has been developed to allow the pilot to choose between different modes and to control the motion direction according to the real situation to reach a destination. The advanced mechatronic design and the active cooperation of the pilot with the device will also be highlighted. As a result, Atalante Evolution allowed the pilot to complete four out of six obstacles, without crutches. Our developments lead to stable dynamic movements of the exoskeleton, hands-free walking, more natural stand-up and turning moves, and consequently a better physical condition of the pilot after the race compared to the challengers. The versatility and good results of these developments give hope that exoskeletons will soon be able to evolve in challenging everyday-life environments, allowing patients to live a normal life in complete autonomy.
RESUMEN
We introduce a methodology to guarantee safety against the spread of infectious diseases by viewing epidemiological models as control systems and human interventions (such as quarantining or social distancing) as control input. We consider a generalized compartmental model that represents the form of the most popular epidemiological models and we design safety-critical controllers that formally guarantee safe evolution with respect to keeping certain populations of interest under prescribed safe limits. Furthermore, we discuss how measurement delays originated from incubation period and testing delays affect safety and how delays can be compensated via predictor feedback. We demonstrate our results by synthesizing active intervention policies that bound the number of infections, hospitalizations and deaths for epidemiological models capturing the spread of COVID-19 in the USA.
RESUMEN
Existing electronic skin (e-skin) sensing platforms are equipped to monitor physical parameters using power from batteries or near-field communication. For e-skins to be applied in the next generation of robotics and medical devices, they must operate wirelessly and be self-powered. However, despite recent efforts to harvest energy from the human body, self-powered e-skin with the ability to perform biosensing with Bluetooth communication are limited because of lack of a continuous energy source and limited power efficiency. Here, we report a flexible and fully perspiration-powered integrated electronic skin (PPES) for multiplexed metabolic sensing in situ. The battery-free e-skin contains multimodal sensors and highly efficient lactate biofuel cells that use a unique integration of zero- to three-dimensional nanomaterials to achieve high power intensity and long-term stability. The PPES delivered a record-breaking power density of 3.5 milliwatt-centimeter-2 for biofuel cells in untreated human body fluids (human sweat) and displayed a very stable performance during a 60-hour continuous operation. It selectively monitored key metabolic analytes (e.g., urea, NH4 +, glucose, and pH) and the skin temperature during prolonged physical activities and wirelessly transmitted the data to the user interface using Bluetooth. The PPES was also able to monitor muscle contraction and work as a human-machine interface for human- prosthesis walking.
Asunto(s)
Fuentes de Energía Bioeléctrica , Técnicas Biosensibles , Dispositivos Electrónicos Vestibles , Tecnología Inalámbrica , Técnicas Biosensibles/instrumentación , Técnicas Biosensibles/métodos , Humanos , Contracción Muscular , Nanopartículas , Robótica/instrumentación , Robótica/métodos , Temperatura Cutánea , SudorRESUMEN
The world has recently undergone the most ambitious mitigation effort in a century, consisting of wide-spread quarantines aimed at preventing the spread of COVID-19. The use of influential epidemiological models of COVID-19 helped to encourage decision makers to take drastic non-pharmaceutical interventions. Yet, inherent in these models are often assumptions that the active interventions are static, e.g., that social distancing is enforced until infections are minimized, which can lead to inaccurate predictions that are ever evolving as new data is assimilated. We present a methodology to dynamically guide the active intervention by shifting the focus from viewing epidemiological models as systems that evolve in autonomous fashion to control systems with an "input" that can be varied in time in order to change the evolution of the system. We show that a safety-critical control approach to COVID-19 mitigation gives active intervention policies that formally guarantee the safe evolution of compartmental epidemiological models. This perspective is applied to current US data on cases while taking into account reduction of mobility, and we find that it accurately describes the current trends when time delays associated with incubation and testing are incorporated. Optimal active intervention policies are synthesized to determine future mitigations necessary to bound infections, hospitalizations, and death, both at national and state levels. We therefore provide means in which to model and modulate active interventions with a view toward the phased reopenings that are currently beginning across the US and the world in a decentralized fashion. This framework can be converted into public policies, accounting for the fractured landscape of COVID-19 mitigation in a safety-critical fashion.