Motion-tracking skill assist and power assist for sinusoidal motions with a semi-active assist mechanism using energy control

This paper describes a skill assist method for sinusoidal motions using a semi-active assist mechanism through an energy control method. In a previous study, we had developed and verified the effectiveness of a power assist device with a semi-active assist mechanism and a control method for reducing loads during periodic motion. Here, we have developed a skill assist method as an extension of our power assist device for periodic motion. The skill of performing sinusoidal motions is defined in this study as an operator’s ability to track such motions. Therefore, our skill assist method attempts to improve the operator’s tracking ability. The proposed skill assist method is implemented using our previous power assist device; therefore, the device provides not only a power assist effect but also a skill assist effect to correct the motion. Hence, an operator obtains both the power and the skill assist effects simultaneously

SLAM algorithm applied to robotics assistance for navigation in unknown environments

<p>Abstract</p> <p>Background</p> <p>The combination of robotic tools with assistance technology determines a slightly explored area of applications and advantages for disability or elder people in their daily tasks. Autonomous motorized wheelchair navigation inside an environment, behaviour based control of orthopaedic arms or user's preference learning from a friendly interface are some examples of this new field. In this paper, a Simultaneous Localization and Mapping (SLAM) algorithm is implemented to allow the environmental learning by a mobile robot while its navigation is governed by electromyographic signals. The entire system is part autonomous and part user-decision dependent (semi-autonomous). The environmental learning executed by the SLAM algorithm and the low level behaviour-based reactions of the mobile robot are robotic autonomous tasks, whereas the mobile robot navigation inside an environment is commanded by a Muscle-Computer Interface (MCI).</p> <p>Methods</p> <p>In this paper, a sequential Extended Kalman Filter (EKF) feature-based SLAM algorithm is implemented. The features correspond to lines and corners -concave and convex- of the environment. From the SLAM architecture, a global metric map of the environment is derived. The electromyographic signals that command the robot's movements can be adapted to the patient's disabilities. For mobile robot navigation purposes, five commands were obtained from the MCI: turn to the left, turn to the right, stop, start and exit. A kinematic controller to control the mobile robot was implemented. A low level behavior strategy was also implemented to avoid robot's collisions with the environment and moving agents.</p> <p>Results</p> <p>The entire system was tested in a population of seven volunteers: three elder, two below-elbow amputees and two young normally limbed patients. The experiments were performed within a closed low dynamic environment. Subjects took an average time of 35 minutes to navigate the environment and to learn how to use the MCI. The SLAM results have shown a consistent reconstruction of the environment. The obtained map was stored inside the Muscle-Computer Interface.</p> <p>Conclusions</p> <p>The integration of a highly demanding processing algorithm (SLAM) with a MCI and the communication between both in real time have shown to be consistent and successful. The metric map generated by the mobile robot would allow possible future autonomous navigation without direct control of the user, whose function could be relegated to choose robot destinations. Also, the mobile robot shares the same kinematic model of a motorized wheelchair. This advantage can be exploited for wheelchair autonomous navigation.</p

Instrumentation and validation of a robotic cane for transportation and fall prevention in patients with affected mobility

Dissertação de mestrado integrado em Engenharia Física, (especialização em Dispositivos, Microssistemas e Nanotecnologias)O ato de andar é conhecido por ser a forma primitiva de locomoção do ser humano, sendo que este traz muitos benefícios que motivam um estilo de vida saudável e ativo. No entanto, há condições de saúde que dificultam a realização da marcha, o que por consequência pode resultar num agravamento da saúde, e adicionalmente, levar a um maior risco de quedas. Nesse sentido, o desenvolvimento de um sistema de deteção e prevenção de quedas, integrado num dispositivo auxiliar de marcha, seria essencial para reduzir estes eventos de quedas e melhorar a qualidade de vida das pessoas. Para ultrapassar estas necessidades e limitações, esta dissertação tem como objetivo validar e instrumentar uma bengala robótica, denominada Anti-fall Robotic Cane (ARCane), concebida para incorporar um sistema de deteção de quedas e um mecanismo de atuação que possibilite a prevenção de quedas, ao mesmo tempo que assiste a marcha. Para esse fim, foi realizada uma revisão do estado da arte em bengalas robóticas para adquirir um conhecimento amplo e aprofundado dos componentes, mecanismos e estratégias utilizadas, bem como os protocolos experimentais, principais resultados, limitações e desafios em dispositivos existentes. Numa primeira fase, foi estipulado o objetivo de: (i) adaptar a missão do produto; (ii) estudar as necessidades do consumidor; e (iii) atualizar as especificações alvo da ARCane, continuação do trabalho de equipa, para obter um produto com design e engenharia compatível com o mercado. Foi depois estabelecida a arquitetura de hardware e discutidos os componentes a ser instrumentados na ARCane. Em seguida foram realizados testes de interoperabilidade a fim de validar o funcionamento singular e coletivo dos componentes. Relativamente ao controlo de movimento, foi desenvolvido um sistema inovador, de baixo custo e intuitivo, capaz de detetar a intenção do movimento e de reconhecer as fases da marcha do utilizador. Esta implementação foi validada com seis voluntários saudáveis que realizaram testes de marcha com a ARCane para testar sua operabilidade num ambiente de contexto real. Obteve-se uma precisão de 97% e de 90% em relação à deteção da intenção de movimento e ao reconhecimento da fase da marcha do utilizador. Por fim, foi projetado um método de deteção de quedas e mecanismo de prevenção de quedas para futura implementação na ARCane. Foi ainda proposta uma melhoria do método de deteção de quedas, de modo a superar as limitações associadas, bem como a proposta de dispositivos de deteção a serem implementados na ARCane para obter um sistema completo de deteção de quedas.The act of walking is known to be the primitive form of the human being, and it brings many benefits that motivate a healthy and active lifestyle. However, there are health conditions that make walking difficult, which, consequently, can result in worse health and, in addition, lead to a greater risk of falls. Thus, the development of a fall detection and prevention system integrated with a walking aid would be essential to reduce these fall events and improve people quality of life. To overcome these needs and limitations, this dissertation aims to validate and instrument a cane-type robot, called Anti-fall Robotic Cane (ARCane), designed to incorporate a fall detection system and an actuation mechanism that allow the prevention of falls, while assisting the gait. Therefore, a State-of-the-Art review concerning robotic canes was carried out to acquire a broad and in-depth knowledge of the used components, mechanisms and strategies, as well as the experimental protocols, main results, limitations and challenges on existing devices. On a first stage, it was set an objective to (i) enhance the product's mission statement; (ii) study the consumer needs; and (iii) update the target specifications of the ARCane, extending teamwork, to obtain a product with a market-compatible design and engineering that meets the needs and desires of the ARCane users. It was then established the hardware architecture of the ARCane and discussed the electronic components that will instrument the control, sensory, actuator and power units, being afterwards subjected to interoperability tests to validate the singular and collective functioning of cane components altogether. Regarding the motion control of robotic canes, an innovative, cost-effective and intuitive motion control system was developed, providing user movement intention recognition, and identification of the user's gait phases. This implementation was validated with six healthy volunteers who carried out gait trials with the ARCane, in order to test its operability in a real context environment. An accuracy of 97% was achieved for user motion intention recognition and 90% for user gait phase recognition, using the proposed motion control system. Finally, it was idealized a fall detection method and fall prevention mechanism for a future implementation in the ARCane, based on methods applied to robotic canes in the literature. It was also proposed an improvement of the fall detection method in order to overcome its associated limitations, as well as detection devices to be implemented into the ARCane to achieve a complete fall detection system

Nutzerorientierte Evaluation zweier altersgerechter Assistenzroboter zur Unterstützung von Alltagsaktivitäten („Ambient Assisted Living-Roboter“) bei älteren Menschen mit funktionellen Einschränkungen: MOBOT-Rollator und I-SUPPORT-Duschroboter

Ziel der vorliegenden Arbeit ist die nutzerorientierte Evaluation zweier Prototypen für altersgerechte Assistenzroboter zur Unterstützung von Alltagsaktivitäten („Ambient Assisted Living“ [AAL]-Roboter) bei älteren Menschen mit funktionellen Einschränkungen. Bei den Prototypen handelt es sich dabei um (1) einen robotergestützten Rollator zur Unterstützung der Mobilität (MOBOT) und (2) einen Assistenzroboter zur Unterstützung von Duschaktivitäten (I-SUPPORT). Manuskript I dokumentiert eine systematische Literaturanalyse des methodischen Vorgehens bisheriger Studien zur Evaluation robotergestützter Rollatoren aus der Nutzerperspektive. Die meisten Studien zeigen erhebliche methodische Mängel, wie unzureichende Stichprobengrößen/-beschreibungen; Teilnehmer nicht repräsentativ für die Nutzergruppe der robotergestützten Rollatoren; keine geeigneten, standardisierten und validierten Assessmentmethoden und/oder keine Inferenzstatistik. Ein generisches methodisches Vorgehen für die Evaluation robotergestützter Rollatoren konnte nicht identifiziert werden. Für die Konzeption und Durchführung zukünftiger Studien zur Evaluation robotergestützter Rollatoren, aber auch anderer AAL-Systeme werden in Manuskript I abschließend Handlungsempfehlungen formuliert. Manuskript II analysiert die Untersuchungsergebnisse der in Manuskript I identifizierten Studien. Es zeigen sich sehr heterogene Ergebnisse hinsichtlich des Mehrwerts der innovativen Assistenzfunktionen von robotergestützten Rollatoren. Im Allgemeinen werden sie jedoch als positiv von den Nutzern wahrgenommen. Die große Heterogenität und methodischen Mängel der Studien schränken die Interpretierbarkeit ihre Untersuchungsergebnisse stark ein. Insgesamt verdeutlicht Manuskript II, dass die Evidenz zur Effektivität und positiven Wahrnehmung robotergestützter Rollatoren aus der Nutzerperspektive noch unzureichend ist. Basierend auf den Erkenntnissen und Handlungsempfehlungen der systematischen Literaturanalysen aus Manuskript I und II wurden die nutzerorientierten Evaluationsstudien des MOBOT-Rollators konzipiert und durchgeführt (Manuskript III-VI). Manuskript III überprüft die Effektivität des in den MOBOT-Rollator integrierten Navigationssystems bei potentiellen Nutzern (= ältere Personen mit Gangstörungen bzw. Rollator als Gehhilfe im Alltag). Es liefert erstmals einen statistischen Nachweis dafür, dass eine solche Assistenzfunktion effektiv ist, um die Navigationsleistung der Nutzer (z. B. geringer Stoppzeit, kürzere Wegstrecke) – insbesondere derjenigen mit kognitiven Einschränkungen – in einem realitätsnahen Anwendungsszenario zu verbessern. Manuskript IV untersucht die konkurrente Validität des MOBOT-integrierten Ganganalysesystems bei potentiellen Nutzern. Im Vergleich zu einem etablierten Referenzstandard (GAITRite®-System) zeigt es eine hohe konkurrente Validität für die Erfassung zeitlicher, nicht jedoch raumbezogener Gangparameter. Diese können zwar ebenfalls mit hoher Konsistenz gemessen werden, aber lediglich mit einer begrenzten absoluten Genauigkeit. Manuskript V umfasst die nutzerorientierte Evaluation der im MOBOT-Rollator integrierten Assistenzfunktion zur Hindernisvermeidung und belegt erstmals die Effektivität einer solchen Funktionen bei potentiellen Nutzern. Unter Verwendung des für den MOBOT-Rollator neu entwickelten technischen Ansatzes für die Hindernisvermeidung zeigten die Teilnehmer signifikante Verbesserungen bei der Bewältigung eines Hindernisparcours (weniger Kollisionen und geringere Annäherungsgeschwindigkeit an die Hindernisse). Manuskript VI dokumentiert die Effektivität und Zufriedenheit mit der Aufstehhilfe des MOBOT-Rollators von potentiellen Nutzern. Es wird gezeigt, dass die Erfolgsrate für den Sitzen-Stehen-Transfer älterer Personen mit motorischen Einschränkungen durch die Aufstehhilfe signifikant verbessert werden kann. Die Ergebnisse belegen zudem eine hohe Nutzerzufriedenheit mit dieser Assistenzfunktion, insbesondere bei Personen mit höherem Body-Mass-Index. Manuskript VII untersucht die Mensch-Roboter-Interaktion zwischen dem I-SUPPORT-Duschroboter und seiner potentiellen Nutzer (= ältere Personen mit Problemen bei Baden/Duschen) und überprüft deren Effektivität sowie Zufriedenheit mit drei unterschiedlich autonomen Betriebsmodi. Die Studienergebnisse dokumentieren, dass sich mit zunehmender Kontrolle des Nutzers (= abnehmende Autonomie des Duschroboters) nicht nur die Effektivität für das Abduschen eines definierten Körperbereichs verringert, sondern auch die Nutzerzufriedenheit sinkt. Manuskript VIII umfasst die Evaluation eines spezifischen Nutzertrainings auf die gestenbasierte Mensch-Roboter-Interaktion mit dem I-SUPPORT-Duschroboter. Es wird gezeigt, dass ein solches Training die Ausführung der Gesten potentieller Nutzer und sowie die Gestenerkennungsrate des Duschroboters signifikant verbessern, was insgesamt auf eine optimierte Mensch-Roboter-Interaktion in Folge des Trainings schließen lässt. Teilnehmer mit der schlechtesten Ausgangsleistung in der Ausführung der Gesten und mit der größten Angst vor Technologien profitierten am meisten vom Nutzertraining. Insgesamt belegen die Studienergebnisse zur nutzerorientierten Evaluation des MOBOT-Rollators die Effektivität und Gültigkeit seiner innovativen Teilfunktionen. Sie weisen auf ein hohes Potential der Assistenzfunktionen (Navigationssystem, Hindernisvermeidung, Aufstehhilfe) zur Verbesserung der Mobilität älterer Menschen mit motorischen Einschränkungen hin. Vor dem Hintergrund der methodischen Mängel und unzureichenden evidenzbasierten Datenlage hierzu, liefert diese Dissertationsschrift erstmals statistische Belege für den Mehrwert solcher Teilfunktionen bei potentiellen Nutzern und leistet somit einen wichtigen Beitrag zur Schließung der bisherigen Forschungslücke hinsichtlich des nutzerorientierten Wirksamkeits- und Gültigkeitsnachweises robotergestützter Rollatoren und ihrer innovativen Teilfunktionen. Die Ergebnisse der Studien des I-SUPPORT-Duschroboters liefern wichtige Erkenntnisse hinsichtlich der Mensch-Roboter-Interaktion im höheren Alter. Sie zeigen, dass bei älteren Nutzern für eine effektive Interaktion Betriebsmodi mit einem hohen Maß an Autonomie des Duschroboters notwendig sind. Trotz ihrer eingeschränkten Kontrolle über den Roboter, waren die Nutzer mit dem autonomsten Betriebsmodus sogar am zufriedensten. Darüber hinaus unterstreichen die Ergebnisse hinsichtlich der gestenbasierten Interaktion mit dem I-SUPPORT-Duschroboter, dass zukünftige Entwicklungen von altersgerechten Assistenzrobotern mit gestenbasierter Interaktion nicht nur die Verbesserungen technischer Aspekte, sondern auch die Sicherstellung und Verbesserungen der Qualität der Nutzergesten für die Mensch-Roboter-Interaktion durch geeignete Trainings- oder Schulungsmaßnahmen berücksichtigen sollten. Das vorgestellte Nutzertraining könnte hierfür ein mögliches Modell darstellen

Design, evaluation, and control of nexus: a multiscale additive manufacturing platform with integrated 3D printing and robotic assembly.

Additive manufacturing (AM) technology is an emerging approach to creating three-dimensional (3D) objects and has seen numerous applications in medical implants, transportation, aerospace, energy, consumer products, etc. Compared with manufacturing by forming and machining, additive manufacturing techniques provide more rapid, economical, efficient, reliable, and complex manufacturing processes. However, additive manufacturing also has limitations on print strength and dimensional tolerance, while traditional additive manufacturing hardware platforms for 3D printing have limited flexibility. In particular, part geometry and materials are limited to most 3D printing hardware. In addition, for multiscale and complex products, samples must be printed, fabricated, and transferred among different additive manufacturing platforms in different locations, which leads to high cost, long process time, and low yield of products. This thesis investigates methods to design, evaluate, and control the NeXus, which is a novel custom robotic platform for multiscale additive manufacturing with integrated 3D printing and robotic assembly. NeXus can be used to prototype miniature devices and systems, such as wearable MEMS sensor fabrics, microrobots for wafer-scale microfactories, tactile robot skins, next generation energy storage (solar cells), nanostructure plasmonic devices, and biosensors. The NeXus has the flexibility to fixture, position, transport, and assemble components across a wide spectrum of length scales (Macro-Meso-Micro-Nano, 1m to 100nm) and provides unparalleled additive process capabilities such as 3D printing through both aerosol jetting and ultrasonic bonding and forming, thin-film photonic sintering, fiber loom weaving, and in-situ Micro-Electro-Mechanical System (MEMS) packaging and interconnect formation. The NeXus system has a footprint of around 4m x 3.5m x 2.4m (X-Y-Z) and includes two industrial robotic arms, precision positioners, multiple manipulation tools, and additive manufacturing processes and packaging capabilities. The design of the NeXus platform adopted the Lean Robotic Micromanufacturing (LRM) design principles and simulation tools to mitigate development risks. The NeXus has more than 50 degrees of freedom (DOF) from different instruments, precise evaluation of the custom robots and positioners is indispensable before employing them in complex and multiscale applications. The integration and control of multi-functional instruments is also a challenge in the NeXus system due to different communication protocols and compatibility. Thus, the NeXus system is controlled by National Instruments (NI) LabVIEW real-time operating system (RTOS) with NI PXI controller and a LabVIEW State Machine User Interface (SMUI) and was programmed considering the synchronization of various instruments and sequencing of additive manufacturing processes for different tasks. The operation sequences of each robot along with relevant tools must be organized in safe mode to avoid crashes and damage to tools during robots’ motions. This thesis also describes two demonstrators that are realized by the NeXus system in detail: skin tactile sensor arrays and electronic textiles. The fabrication process of the skin tactile sensor uses the automated manufacturing line in the NeXus with pattern design, precise calibration, synchronization of an Aerosol Jet printer, and a custom positioner. The fabrication process for electronic textiles is a combination of MEMS fabrication techniques in the cleanroom and the collaboration of multiple NeXus robots including two industrial robotic arms and a custom high-precision positioner for the deterministic alignment process

Towards a Legal end Ethical Framework for Personal Care Robots. Analysis of Person Carrier, Physical Assistant and Mobile Servant Robots.

Technology is rapidly developing, and regulators and robot creators inevitably have to come to terms with new and unexpected scenarios. A thorough analysis of this new and continuosuly evolving reality could be useful to better understand the current situation and pave the way to the future creation of a legal and ethical framework. This is clearly a wide and complex goal, considering the variety of new technologies available today and those under development. Therefore, this thesis focuses on the evaluation of the impacts of personal care robots. In particular, it analyzes how roboticists adjust their creations to the existing regulatory framework for legal compliance purposes. By carrying out an impact assessment analysis, existing regulatory gaps and lack of regulatory clarity can be highlighted. These gaps should of course be considered further on by lawmakers for a future legal framework for personal care robot. This assessment should be made first against regulations. If the creators of the robot do not encounter any limitations, they can then proceed with its development. On the contrary, if there are some limitations, robot creators will either (1) adjust the robot to comply with the existing regulatory framework; (2) start a negotiation with the regulators to change the law; or (3) carry out the original plan and risk to be non-compliant. The regulator can discuss existing (or lacking) regulations with robot developers and give a legal response accordingly. In an ideal world, robots are clear of impacts and therefore threats can be responded in terms of prevention and opportunities in form of facilitation. In reality, the impacts of robots are often uncertain and less clear, especially when they are inserted in care applications. Therefore, regulators will have to address uncertain risks, ambiguous impacts and yet unkown effects

Design and control methodology of a lower extremity assistive device

Ph.DDOCTOR OF PHILOSOPH

Adaptive wake and sleep detection for wearable systems

Sleep problems and disorders have a serious impact on human health and wellbeing. The rising costs for treating sleep-related chronic diseases in industrialized countries demands efficient prevention. Low-cost, wearable sleep / wake detection systems which give feedback on the wearer's "sleep performance" are a promising approach to reduce the risk of developing serious sleep disorders and fatigue. Not all bio-medical signals that are useful for sleep / wake discrimination can be easily recorded with wearable systems. Sensors often need to be placed in an obtrusive location on the body or cannot be efficiently embedded into a wearable frame. Furthermore, wearable systems have limited computational and energetic resources, which restrict the choice of sensors and algorithms for online processing and classification. Since wearable systems are used outside the laboratory, the recorded signals tend to be corrupted with additional noise that influences the precision of classification algorithms. In this thesis we present the research on a wearable sleep / wake classifier system that relies on cardiorespiratory (ECG and respiratory effort) and activity recordings and that works autonomously with minimal user interaction. This research included the selection of optimal signals and sensors, the development of a custom-tailored hardware demonstrator with embedded classification algorithms, and the realization of experiments in real-world environments for the customization and validation of the system. The processing and classification of the signals were based on Fourier transformations and artificial neural networks that are efficiently implementable into digital signal controllers. Literature analysis and empiric measurements revealed that cardiorespiratory signals are more promising for a wearable sleep / wake classification than clinically used signals such as brain potentials. The experiments conducted during this thesis showed that inter-subject differences within the recorded physiological signals make it difficult to design a sleep / wake classification model that can generalize to a group of subjects. This problem was addressed in two ways: First by adding features from another signal to the classifier, that is, measuring the behavioral quiescence during sleep using accelerometers. Conducted research on different feature extraction methods from accelerometer data showed that this data generalizes well for distinct subjects in the study group. In addition, research on user-adaptation methods was conducted. Behavioral sleep and wake measures, notably the measurement of reactivity and activity, were developed to build up a priori knowledge that was used to adapt the classification algorithm automatically to new situations. This thesis demonstrates the design and development of a low-cost, wearable hardware and embedded software for on-line sleep / wake discrimination. The proposed automatic user-adaptive classifier is advantageous compared to previously suggested classification methods that generalize over multiple subjects, because it can take changes in the wearer's physiology and sleep / wake behavior into account without adjustment from a human expert. The results of this thesis contribute to the development of smart, wearable, bio-physiological monitoring systems which require a high degree of autonomy and have only low computational resources available. We believe that the proposed sleep / wake classification system is a first promising step toward a context-aware system for sleep management, sleep disorder prevention, and reduction of fatigue