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"Robotic exoskeletons."
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EMG patterns during assisted walking in the exoskeleton
Neuroprosthetic technology and robotic exoskeletons are being developed to facilitate stepping, reduce muscle efforts, and promote motor recovery. Nevertheless, the guidance forces of an exoskeleton may influence the sensory inputs, sensorimotor interactions and resulting muscle activity patterns during stepping. The aim of this study was to report the muscle activation patterns in a sample of intact and injured subjects while walking with a robotic exoskeleton and, in particular, to quantify the level of muscle activity during assisted gait. We recorded electromyographic (EMG) activity of different leg and arm muscles during overground walking in an exoskeleton in six healthy individuals and four spinal cord injury (SCI) participants. In SCI patients, EMG activity of the upper limb muscles was augmented while activation of leg muscles was typically small. Contrary to our expectations, however, in neurologically intact subjects, EMG activity of leg muscles was similar or even larger during exoskeleton-assisted walking compared to normal overground walking. In addition, significant variations in the EMG waveforms were found across different walking conditions. The most variable pattern was observed in the hamstring muscles. Overall, the results are consistent with a non-linear reorganization of the locomotor output when using the robotic stepping devices. The findings may contribute to our understanding of human-machine interactions and adaptation of locomotor activity patterns.
Journal Article
Elysium
\"In a future in which the privileged reside on an Earth-orbiting space station named Elysium and the less fortunate live on the surface of the blighted, overpopulated planet below, one man dares to defy the strict anti-immigration laws that separate the two disparate worlds in order to save all of mankind in this visceral sci-fi action thriller from District 9 director Neill Blomkamp. The year is 2154, and the division between social classes has grown wider than ever before. As the rich enjoy a life of luxury and access to cutting-edge medical technology on Elysium, the rest of the human race contend with poverty, crime, and disease on the surface of planet Earth. Meanwhile, hard-line immigration laws ensure that only those who have been explicitly approved will ever set foot on the elusive paradise in the stars. 36-year-old Max (Matt Damon) lives in an L.A. shantytown and earns his living by working on an Armadyne assembly line. He's had a rough past, but he's struggling to stay on the right side of the law when he realizes that his only hope for survival after being exposed to deadly radiation is to reach Elysium. Should Max succeed, he will strike a major blow for equality in the eyes of his fellow surface dwellers; should he fail, it will mean certain death. In his quest to become the hero who can restore the balance between the rich and the poor, however, Max must first do battle with Elysium's hawkish Secretary of Defense Delacourt (Jodie Foster), who has devoted her entire career to maintaining that division, and whose key enforcer Kruger (Sharlto Copley) is notorious for his brutal tactics in driving out illegals. With the fates of millions hanging in the balance, Max sets his sights on Elysium and never looks back. Alice Braga, Diego Luna, William Fichtner, and Faran Tahir co-star\"--Allmovie.com, viewed April 25, 2018.
DVD
Human hand compatible underactuated exoskeleton robotic system
A novel direct-driven and portable exoskeleton robotic system for the hand is proposed. The system design is based on the multi-parametric optimisation procedure, which considers isotropy, dexterity and exertion of perpendicular forces on the finger phalanges. Actuators for the proposed device were selected based on results of experiments with users having different hand sizes. These experiments measured various parameters including average and maximum force exertion levels of a human hand. The experimental results were used to realise the mechanical design and to develop a prototype. The device can exert force levels (of 45 N) beyond any existing hand exoskeleton. Preliminary trials carried out on the fabricated prototype dictate efficacy and potential of the proposed system.
Journal Article
Artificial Intelligence-Based Wearable Robotic Exoskeletons for Upper Limb Rehabilitation: A Review
Processing and control systems based on artificial intelligence (AI) have progressively improved mobile robotic exoskeletons used in upper-limb motor rehabilitation. This systematic review presents the advances and trends of those technologies. A literature search was performed in Scopus, IEEE Xplore, Web of Science, and PubMed using the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) methodology with three main inclusion criteria: (a) motor or neuromotor rehabilitation for upper limbs, (b) mobile robotic exoskeletons, and (c) AI. The period under investigation spanned from 2016 to 2020, resulting in 30 articles that met the criteria. The literature showed the use of artificial neural networks (40%), adaptive algorithms (20%), and other mixed AI techniques (40%). Additionally, it was found that in only 16% of the articles, developments focused on neuromotor rehabilitation. The main trend in the research is the development of wearable robotic exoskeletons (53%) and the fusion of data collected from multiple sensors that enrich the training of intelligent algorithms. There is a latent need to develop more reliable systems through clinical validation and improvement of technical characteristics, such as weight/dimensions of devices, in order to have positive impacts on the rehabilitation process and improve the interactions among patients, teams of health professionals, and technology.
Journal Article
Systematic Review on Wearable Lower Extremity Robotic Exoskeletons for Assisted Locomotion
Lower extremity robotic exoskeletons (LEEX) can not only improve the ability of the human body but also provide healing treatment for people with lower extremity dysfunction. There are a wide range of application needs and development prospects in the military, industry, medical treatment, consumption and other fields, which has aroused widespread concern in society. This paper attempts to review LEEX technical development. First, the history of LEEX is briefly traced. Second, based on existing research, LEEX is classified according to auxiliary body parts, structural forms, functions and fields, and typical LEEX prototypes and products are introduced. Then, the latest key technologies are analyzed and summarized, and the research contents, such as bionic structure and driving characteristics, human–robot interaction (HRI) and intent-awareness, intelligent control strategy, and evaluation method of power-assisted walking efficiency, are described in detail. Finally, existing LEEX problems and challenges are analyzed, a future development trend is proposed, and a multidisciplinary development direction of the key technology is provided.
Journal Article
Review of electromyography onset detection methods for real-time control of robotic exoskeletons
Background
Electromyography (EMG) is a classical technique used to record electrical activity associated with muscle contraction and is widely applied in Biomechanics, Biomedical Engineering, Neuroscience and Rehabilitation Robotics. Determining muscle activation onset timing, which can be used to infer movement intention and trigger prostheses and robotic exoskeletons, is still a big challenge. The main goal of this paper was to perform a review of the state-of-the-art of EMG onset detection methods. Moreover, we compared the performance of the most commonly used methods on experimental EMG data.
Methods
A total of 156 papers published until March 2022 were included in the review. The papers were analyzed in terms of application domain, pre-processing method and EMG onset detection method. The three most commonly used methods [Single (ST), Double (DT) and Adaptive Threshold (AT)] were applied offline on experimental intramuscular and surface EMG signals obtained during contractions of ankle and knee joint muscles.
Results
Threshold-based methods are still the most commonly used to detect EMG onset. Compared to ST and AT, DT required more processing time and, therefore, increased onset timing detection, when applied on experimental data. The accuracy of these three methods was high (maximum error detection rate of 7.3%), demonstrating their ability to automatically detect the onset of muscle activity. Recently, other studies have tested different methods (especially Machine Learning based) to determine muscle activation onset offline, reporting promising results.
Conclusions
This study organized and classified the existing EMG onset detection methods to create consensus towards a possible standardized method for EMG onset detection, which would also allow more reproducibility across studies. The three most commonly used methods (ST, DT and AT) proved to be accurate, while ST and AT were faster in terms of EMG onset detection time, especially when applied on intramuscular EMG data. These are important features towards movement intention identification, especially in real-time applications. Machine Learning methods have received increased attention as an alternative to detect muscle activation onset. However, although several methods have shown their capability offline, more research is required to address their full potential towards real-time applications, namely to infer movement intention.
Journal Article
A pilot study on the design and validation of a hybrid exoskeleton robotic device for hand rehabilitation
An iterative design process was used to obtain design parameters that satisfy both kinematic and dynamic requirements for the hand exoskeleton. This design was validated through experimental studies.
The success of hand rehabilitation after impairments depends on the timing, intensity, repetition, and frequency, as well as task-specific training. Considering the continuing constraints placed on therapist-led rehabilitation and need for better outcomes, robot-assisted rehabilitation has been explored. Soft robotic approaches have been implemented for a hand rehabilitation exoskeleton as they have more tolerance for alignment with biological joints than those of hard exoskeletons.
The purpose of the study was to design, develop, and validate a soft robotic exoskeleton for hand rehabilitation.
A motion capture system validated the kinematics of the soft robotic digit attached on top of a human index finger. A pneumatic control system and algorithms were developed to operate the exoskeleton based on three therapeutic modes: continuous passive, active assistive, and active resistive motion. Pilot studies were carried out on one healthy and one poststroke participant using continuous passive motion and bilateral/bimanual therapy modes.
The soft robotic digits were able to produce required range of motion and accommodate for dorsal lengthening, with trajectories of the center of rotation of the soft robotic joints in close agreement with the center of rotation of the human finger joints.
The exoskeleton showed the robust performance of the robot in applying continuous passive motion and bilateral/bimanual therapy.
This soft robotic exoskeleton is promising for assisting in the rehabilitation of the hand.
•Soft robotic exoskeleton is promising for hand rehabilitation.•The kinematic compatibility of the exoskeleton design was experimentally validated.•Robot showed robust performance in continuous passive motion and bimanual therapy.
Journal Article
Evidence of neuroplasticity with robotic hand exoskeleton for post-stroke rehabilitation: a randomized controlled trial
Background
A novel electromechanical robotic-exoskeleton was designed in-house for the rehabilitation of wrist joint and Metacarpophalangeal (MCP) joint.
Objective
The objective was to compare the rehabilitation effectiveness (clinical-scales and neurophysiological-measures) of robotic-therapy training sessions with dose-matched conventional therapy in patients with stroke.
Methods
A pilot prospective parallel randomized controlled study at clinical settings was designed for patients with stroke within 2 years of chronicity. Patients were randomly assigned to receive an intervention of 20 sessions of 45 min each, five days a week for four weeks, in Robotic-therapy Group (RG) (n = 12) and conventional upper-limb rehabilitation in Control-Group (CG) (n = 11). We intended to evaluate the effects of a novel exoskeleton based therapy on the functional rehabilitation outcomes of upper-limb and cortical-excitability in patients with stroke as compared to the conventional-rehabilitation. Clinical-scales– Modified Ashworth Scale, Active Range of Motion, Barthel-Index, Brunnstrom-stage and Fugl-Meyer (FM) scale and neurophysiological measures of cortical-excitability (using Transcranial Magnetic Stimulation) –Motor Evoked Potential and Resting Motor threshold, were acquired pre- and post-therapy.
Results
No side effects were noticed in any of the patients. Both RG and CG showed significant (
p
< 0.05) improvement in all clinical motor-outcomes except Modified Ashworth Scale in CG. RG showed significantly (
p
< 0.05) higher improvement over CG in Modified Ashworth Scale, Active Range of Motion and Fugl-Meyer scale and FM Wrist-/Hand component. An increase in cortical-excitability in ipsilesional-hemisphere was found to be statistically significant (
p
< 0.05) in RG over CG, as indexed by a decrease in Resting Motor Threshold and increase in the amplitude of Motor Evoked Potential. No significant changes were shown by the contralesional-hemisphere. Interhemispheric RMT-asymmetry evidenced significant (
p
< 0.05) changes in RG over CG indicating increased cortical-excitability in ipsilesional-hemisphere along with interhemispheric changes.
Conclusion
Robotic-exoskeleton training showed improvement in motor outcomes and cortical-excitability in patients with stroke. Neurophysiological changes in RG could most likely be a consequence of plastic reorganization and use-dependent plasticity.
Trial registry number
: ISRCTN95291802
Journal Article
A survey on the state of the art of force myography technique (FMG): analysis and assessment
Precise feedback assures precise control commands especially for assistive or rehabilitation devices. Biofeedback systems integrated with assistive or rehabilitative robotic exoskeletons tend to increase its performance and effectiveness. Therefore, there has been plenty of research in the field of biofeedback covering different aspects such as signal acquisition, conditioning, feature extraction and integration with the control system. Among several types of biofeedback systems, Force myography (FMG) technique is a promising one in terms of affordability, high classification accuracies, ease to use, and low computational cost. Compared to traditional biofeedback systems such as electromyography (EMG) which offers some invasive techniques, FMG offers a completely non-invasive solution with much less effort for preprocessing with high accuracies. This work covers the whole aspects of FMG technique in terms of signal acquisition, feature extraction, signal processing, developing the machine learning model, evaluating tools for the performance of the model. Stating the difference between real-time and offline assessment, also highlighting the main uncovered points for further study, and thus enhancing the development of this technique.
Graphical abstract
Journal Article