Efficacy of a hybrid assistive limb in post-stroke hemiplegic patients: a preliminary report

<p>Abstract</p> <p>Background</p> <p>Robotic devices are expected to be widely used in various applications including support for the independent mobility of the elderly with muscle weakness and people with impaired motor function as well as support for nursing care that involves heavy laborious work. We evaluated the effects of a hybrid assistive limb robot suit on the gait of stroke patients undergoing rehabilitation.</p> <p>Methods</p> <p>The study group comprised 16 stroke patients with severe hemiplegia. All patients underwent gait training. Four patients required assistance, and 12 needed supervision while walking. The stride length, walking speed and physiological cost index on wearing the hybrid assistive limb suit and a knee-ankle-foot orthosis were compared.</p> <p>Results</p> <p>The hybrid assistive limb suit increased the stride length and walking speed in 4 of 16 patients. The patients whose walking speed decreased on wearing the hybrid assistive limb suit either had not received sufficient gait training or had an established gait pattern with a knee-ankle-foot orthosis using a quad cane. The physiological cost index increased after wearing the hybrid assistive limb suit in 12 patients, but removal of the suit led to a decrease in the physiological cost index values to equivalent levels prior to the use of the suit.</p> <p>Conclusions</p> <p>Although the hybrid assistive limb suit is not useful for all hemiplegic patients, it may increase the walking speed and affect the walking ability. Further investigation would clarify its indication for the possibility of gait training.</p

Fall Prediction and Prevention Systems: Recent Trends, Challenges, and Future Research Directions.

Fall prediction is a multifaceted problem that involves complex interactions between physiological, behavioral, and environmental factors. Existing fall detection and prediction systems mainly focus on physiological factors such as gait, vision, and cognition, and do not address the multifactorial nature of falls. In addition, these systems lack efficient user interfaces and feedback for preventing future falls. Recent advances in internet of things (IoT) and mobile technologies offer ample opportunities for integrating contextual information about patient behavior and environment along with physiological health data for predicting falls. This article reviews the state-of-the-art in fall detection and prediction systems. It also describes the challenges, limitations, and future directions in the design and implementation of effective fall prediction and prevention systems

Online estimation of rollator user condition using spatiotemporal gait parameters

Assistance to people during rehabilitation has to be adapted to their needs. Too little help can lead to frustration and stress in the user; an excess of help may lead to low participation and loss of residual skills. Robotic rollators may adapt assistance. The main challenge to cope with this issue is to estimate how much help is needed on the fly, because it depends not only on the person condition, but also on the specific situation that they are negotiating. Clinical scales provide a global condition based estimation, but no local estimator based on punctual needs. Condition also changes in time, so clinical scales need to be recalculated again and again. In this paper we propose a novel approach to estimate users’ condition in a continuous way via a robotic rollator. Our work focuses on predicting the value of the well known Tinetti Mobility test from spatiotemporal gait parameters obtained from our platform while users walk. This prediction provides continuous insight on the condition of the user and could be used to modify the amount of help provided. The proposed method has been validated with 19 volunteers at a local hospital that use a rollator for rehabilitation. All volunteers presented some physical or mental disabilities. Our results sucessfully show a high correlation of spatiotemporal gait parameters with Tinetti Mobility test gait (R2 = 0.7) and Tinetti Mobility test balance (R2 = 0.6).Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech

A Survey of Applications and Human Motion Recognition with Microsoft Kinect

Microsoft Kinect, a low-cost motion sensing device, enables users to interact with computers or game consoles naturally through gestures and spoken commands without any other peripheral equipment. As such, it has commanded intense interests in research and development on the Kinect technology. In this paper, we present, a comprehensive survey on Kinect applications, and the latest research and development on motion recognition using data captured by the Kinect sensor. On the applications front, we review the applications of the Kinect technology in a variety of areas, including healthcare, education and performing arts, robotics, sign language recognition, retail services, workplace safety training, as well as 3D reconstructions. On the technology front, we provide an overview of the main features of both versions of the Kinect sensor together with the depth sensing technologies used, and review literatures on human motion recognition techniques used in Kinect applications. We provide a classification of motion recognition techniques to highlight the different approaches used in human motion recognition. Furthermore, we compile a list of publicly available Kinect datasets. These datasets are valuable resources for researchers to investigate better methods for human motion recognition and lower-level computer vision tasks such as segmentation, object detection and human pose estimation

Human Activity Recognition and Control of Wearable Robots

abstract: Wearable robotics has gained huge popularity in recent years due to its wide applications in rehabilitation, military, and industrial fields. The weakness of the skeletal muscles in the aging population and neurological injuries such as stroke and spinal cord injuries seriously limit the abilities of these individuals to perform daily activities. Therefore, there is an increasing attention in the development of wearable robots to assist the elderly and patients with disabilities for motion assistance and rehabilitation. In military and industrial sectors, wearable robots can increase the productivity of workers and soldiers. It is important for the wearable robots to maintain smooth interaction with the user while evolving in complex environments with minimum effort from the user. Therefore, the recognition of the user's activities such as walking or jogging in real time becomes essential to provide appropriate assistance based on the activity. This dissertation proposes two real-time human activity recognition algorithms intelligent fuzzy inference (IFI) algorithm and Amplitude omega ($A \omega$) algorithm to identify the human activities, i.e., stationary and locomotion activities. The IFI algorithm uses knee angle and ground contact forces (GCFs) measurements from four inertial measurement units (IMUs) and a pair of smart shoes. Whereas, the $A \omega$ algorithm is based on thigh angle measurements from a single IMU. This dissertation also attempts to address the problem of online tuning of virtual impedance for an assistive robot based on real-time gait and activity measurement data to personalize the assistance for different users. An automatic impedance tuning (AIT) approach is presented for a knee assistive device (KAD) in which the IFI algorithm is used for real-time activity measurements. This dissertation also proposes an adaptive oscillator method known as amplitude omega adaptive oscillator ($A\omega AO$) method for HeSA (hip exoskeleton for superior augmentation) to provide bilateral hip assistance during human locomotion activities. The $A \omega$ algorithm is integrated into the adaptive oscillator method to make the approach robust for different locomotion activities. Experiments are performed on healthy subjects to validate the efficacy of the human activities recognition algorithms and control strategies proposed in this dissertation. Both the activity recognition algorithms exhibited higher classification accuracy with less update time. The results of AIT demonstrated that the KAD assistive torque was smoother and EMG signal of Vastus Medialis is reduced, compared to constant impedance and finite state machine approaches. The $A\omega AO$ method showed real-time learning of the locomotion activities signals for three healthy subjects while wearing HeSA. To understand the influence of the assistive devices on the inherent dynamic gait stability of the human, stability analysis is performed. For this, the stability metrics derived from dynamical systems theory are used to evaluate unilateral knee assistance applied to the healthy participants.Dissertation/ThesisDoctoral Dissertation Aerospace Engineering 201

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

Assistive mobility devices focusing on smart walkers : classification and review

In an aging society it is extremely important to develop devices, which can support and aid the elderly in their daily life. This demands means and tools that extend independent living and promote improved health. Thus, the goal of this article is to review the state of the art in the robotic technology for mobility assistive devices for people with mobility disabilities. The important role that robotics can play in mobility assistive devices is presented, as well as the identification and survey of mobility assistive devices subsystems with a particular focus on the walkers technology. The advances in the walkers’ field have been enormous and have shown a great potential on helping people with mobility disabilities. Thus it is presented a review of the available literature of walkers and are discussed major advances that have been made and limitations to be overcome

An optimal procedure for stride length estimation using foot-mounted magneto-inertial measurement units

Stride length is often used to quantitatively evaluate human locomotion performance. Stride by stride estimation can be conveniently obtained from the signals recorded using miniaturized inertial sensors attached to the feet and appropriate algorithms for data fusion and integration. To reduce the detrimental drift effect, different algorithmic solutions can be implemented. However, the overall method accuracy is supposed to depend on the optimal selection of the parameters which are required to be set. This study aimed at evaluating the influence of the main parameters involved in well-established methods for stride length estimation. An optimization process was conducted to improve methods' performance and preferable values for the considered parameters according to different walking speed ranges are suggested. A parametric solution is also proposed to target the methods on specific subjects' gait characteristics. The stride length estimates were obtained from straight walking trials of five healthy volunteers and were compared with those obtained from a stereo-photogrammetric system. After parameters tuning, percentage errors for stride length were 1.9%, 2.5% and 2.6% for comfortable, slow, and fast walking conditions, respectively

Towards a human-in-the-loop control for a smart orthotic system

Dissertação de mestrado integrado em Engenharia Biomédica (área de especialização em Eletrónica Médica)Stroke is the main cause of paralysis. This pathology has provoked a considerable increase of persons with motor impairments. With a therapy focused on each clinical case, the total or partial recovery can be achieved. Powered orthoses have been developed to promote an effective recover, based on repetitive gait training and user’s active participation. Many control approaches have been developed to control these devices, but none of them promotes an user-oriented strategy focused to the user’s needs. In an attempt of solving this issue, a new approach named Human-in-the-loop is emerging. This strategy allows the adaptation of some assistive parameters based on the user’s energetic cost, promoting a therapy tailored to each end-user needs. However, to estimate the energy expenditure, the use of non-ergonomic sensors, not suitable for clinical context, is required. Thus, it is necessary to find new ways of estimating energy expenditure using wearable and comfortable sensors. In this dissertation, the first steps to introduce the Human-in-the-loop strategy into a powered orthosis are presented. For this purpose, two strategies were developed: a strategy that allows the angular trajectory adaptation in real-time and other that promotes a stiffness adaptation all over the gait cycle. Both strategies were validated with healthy subjects. In the first strategy, the orthosis was able to modify its assistance in a fraction of microseconds, and the end-users were able to follow her with a median error below 10%. Regarding the second strategy, the results show that the orthosis allowed an effective change in the systems’ interaction stiffness, promoting an active participation of each user during its assistance. The energetic impact of using the robotic assistive device is also presented. As it promotes an energy expenditure augmentation in more than 30% in comparison to walk without the device, the necessity of implementing the Human-in-the-loop strategy was highlighted. In an attempt of finding an ergonomic technique to estimate the energetic cost, the use of machine learning algorithms was tested. The results, obtained with a MLP and a LSTM, prove that it is possible to estimate the energy expenditure with a mean error close to 11%. Future work consists in the implementation of the model in real-time and the collection of more data with the aforementioned control approaches, in a way of constructing a more robust model.O AVC é uma das maiores causas de paralisia. Esta patologia, cada vez mais com maior incidência nos jovens, tem provocado um aumento considerável de pessoas com problemas de mobilidade. Com uma terapia focada a cada caso clínico, a recuperação total ou parcial pode ser conseguida. As ortóteses ativas têm vindo a ser desenvolvidas com o propósito de promover uma recuperação eficaz, baseada em treinos repetitivos e numa participação ativa dos utilizadores. Várias abordagens de controlo têm vindo a ser desenvolvidas para controlar estes dispositivos, mas nenhuma delas promove uma estratégia orientada às necessidades do utilizador. Na tentativa de solucionar este problema, uma nova abordagem, designada por Human-in-the-loop está a emergir. Baseada no custo energético, esta estratégia permite adaptar parâmetros da assistência, promovendo uma terapia focada e direcionada a cada utilizador. No entanto, para estimar o custo energético, recorre-se ao uso de sensores que não são adequados para contexto clínico. Assim, torna-se necessário estudar novas formas de estimar o custo energético. Nesta dissertação são apresentados os primeiros passos para introduzir o controlo Human-in-the-loop numa ortótese ativa. Para isso, duas estratégias foram apresentadas: uma estratégia que permite adaptar a trajetória angular da ortótese, em tempo real, e outra que promove a adaptação da complacência do sistema ao longo do ciclo da marcha. Ambas foram validadas com sujeitos saudáveis. Relativamente à primeira abordagem, a ortótese foi capaz de modificar a sua assistência em microssegundos, e os utilizadores foram capazes de a seguir com um erro mediano inferior a 10%. No que diz respeito à segunda abordagem, os resultados mostram que a ortótese promoveu uma alteração eficaz da complacência de interação, promovendo uma participação ativa do utilizador durante a sua assistência. O impacto energético do uso do sistema robótico é, também, apresentado. Promovendo um aumento do custo energético em mais de 30%, a necessidade da estratégia Human-in-the-loop foi realçada. Na tentativa de encontrar uma técnica para estimar o custo energético, recorreu-se ao uso de machine learning. Os resultados, obtidos com uma MLP e uma LSTM, provam que é possível estimar o custo energético com um erro médio próximo dos 11%. Trabalho futuro passa pela implementação do modelo em tempo real e a recolha de mais dados com as abordagens de controlo apresentadas, de forma a construir um modelo mais robusto