Posts Tagged biomechanics

[Abstract] An extended kinematic model for arm rehabilitation training and assessment

Abstract

In the rehabilitation training and assessment of upper limbs, the conventional kinematic model treats the arm as a serial manipulator and maps the rotations in the joint space to movements in the Cartesian space. While this model brings simplicity and convenience, and thus has been overwhelming used, its accuracy is limited, especially for the distal parts of the upper limb that execute dexterous movements.

In this paper, a novel kinematic model of the arm has been proposed, which has been inspired by the biomechanical analysis of the forearm and wrist anatomy. One additional parameter is introduced into the conventional arm model, and then both the forward and inverse kinematic models of five parameters are derived for the motion of upper arm medial/lateral rotation, elbow flexion/extension, forearm pronation/supination, wrist flexion/extension and ulnar/radial deviation. Then, experiments with an advanced haptic interface have been designed and performed to examine the presented arm kinematic model. Data analysis revealed that accuracy and robustness can be significantly improved with the new model.

This extended arm kinematic model will help device development, movement training and assessment of upper limb rehabilitation.

Published in: Advanced Robotics and Mechatronics (ICARM), International Conference on

Source: An extended kinematic model for arm rehabilitation training and assessment – IEEE Xplore Document

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[Abstract] Robotic Devices to Enhance Human Movement Performance.

Abstract

Robotic exoskeletons and bionic prostheses have moved from science fiction to science reality in the last decade. These robotic devices for assisting human movement are now technically feasible given recent advancements in robotic actuators, sensors, and computer processors. However, despite the ability to build robotic hardware that is wearable by humans, we still do not have optimal controllers to allow humans to move with coordination and grace in synergy with the robotic devices. We consider the history of robotic exoskeletons and bionic limb prostheses to provide a better assessment of the roadblocks that have been overcome and to gauge the roadblocks that still remain. There is a strong need for kinesiologists to work with engineers to better assess the performance of robotic movement assistance devices. In addition, the identification of new performance metrics that can objectively assess multiple dimensions of human performance with robotic exoskeletons and bionic prostheses would aid in moving the field forward. We discuss potential control approaches for these robotic devices, with a preference for incorporating feedforward neural signals from human users to provide a wider repertoire of discrete and adaptive rhythmic movements.

Source: Robotic Devices to Enhance Human Movement Performance: Kinesiology Review: Vol 6, No 1

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[Abstract] Combining a hybrid robotic system with a bain-machine interface for the rehabilitation of reaching movements: A case study with a stroke patient

Abstract:

Reaching and grasping are two of the most affected functions after stroke. Hybrid rehabilitation systems combining Functional Electrical Stimulation with Robotic devices have been proposed in the literature to improve rehabilitation outcomes. In this work, we present the combined use of a hybrid robotic system with an EEG-based Brain-Machine Interface to detect the user’s movement intentions to trigger the assistance. The platform has been tested in a single session with a stroke patient. The results show how the patient could successfully interact with the BMI and command the assistance of the hybrid system with low latencies. Also, the Feedback Error Learning controller implemented in this system could adjust the required FES intensity to perform the task.

I. Introduction

Stroke is a leading cause of adult disability around the world. A large number of stroke survivors are left with a unilateral arm or leg paralysis. After completing conventional rehabilitation therapy, a significant number of stroke survivors are left with limited reaching and grasping capabilities [1].

Source: Combining a hybrid robotic system with a bain-machine interface for the rehabilitation of reaching movements: A case study with a stroke patient – IEEE Xplore Document

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[Abstract] Gait Biomechanics in the Era of Data Science – Journal of Biomechanics

Abstract

Data science has transformed fields such as computer vision and economics. The ability of modern data science methods to extract insights from large, complex, heterogeneous, and noisy datasets is beginning to provide a powerful complement to the traditional approaches of experimental motion capture and biomechanical modeling. The purpose of this article is to provide a perspective on how data science methods can be incorporated into our field to advance our understanding of gait biomechanics and improve treatment planning procedures. We provide examples of how data science approaches have been applied to biomechanical data. We then discuss the challenges that remain for effectively using data science approaches in clinical gait analysis and gait biomechanics research, including the need for new tools, better infrastructure and incentives for sharing data, and education across the disciplines of biomechanics and data science. By addressing these challenges, we can revolutionize treatment planning and biomechanics research by capitalizing on the wealth of knowledge gained by gait researchers over the past decades and the vast, but often siloed, data that are collected in clinical and research laboratories around the world.

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[REVIEW] Hand synergies: Integration of robotics and neuroscience for understanding the control of biological and artificial hands

Highlights

  • Synergies have been extensively studied by neuroscientists to understand the control of multi-joint movements.
  • Synergies are thought to emerge from the interaction of neural and biomechanical factors.
  • The field of robotics has recently exploited the concept of synergies to design and build artificial hands.
  • Neuroscience has leveraged recent advances in robotics research by using novel tools and approaches to study hand control.

Abstract

The term ‘synergy’ – from the Greek synergia – means ‘working together’. The concept of multiple elements working together towards a common goal has been extensively used in neuroscience to develop theoretical frameworks, experimental approaches, and analytical techniques to understand neural control of movement, and for applications for neuro-rehabilitation. In the past decade, roboticists have successfully applied the framework of synergies to create novel design and control concepts for artificial hands, i.e., robotic hands and prostheses. At the same time, robotic research on the sensorimotor integration underlying the control and sensing of artificial hands has inspired new research approaches in neuroscience, and has provided useful instruments for novel experiments.

The ambitious goal of integrating expertise and research approaches in robotics and neuroscience to study the properties and applications of the concept of synergies is generating a number of multidisciplinary cooperative projects, among which the recently finished 4-year European project “The Hand Embodied” (THE). This paper reviews the main insights provided by this framework. Specifically, we provide an overview of neuroscientific bases of hand synergies and introduce how robotics has leveraged the insights from neuroscience for innovative design in hardware and controllers for biomedical engineering applications, including myoelectric hand prostheses, devices for haptics research, and wearable sensing of human hand kinematics. The review also emphasizes how this multidisciplinary collaboration has generated new ways to conceptualize a synergy-based approach for robotics, and provides guidelines and principles for analyzing human behavior and synthesizing artificial robotic systems based on a theory of synergies.

Source: Hand synergies: Integration of robotics and neuroscience for understanding the control of biological and artificial hands

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[Abstract] Hand synergies: Integration of robotics and neuroscience for understanding the control of biological and artificial hands

Highlights

Cover imageSynergies have been extensively studied by neuroscientists to understand the control of movements involving multiple muscles and joints.

The overarching theoretical framework underlying the concept of synergies is that they emerge from the interaction of neural and biomechanical factors. This interaction leads to a reduction in the number of independent degrees of freedom to be controlled.

The field of robotics has recently exploited the concept of synergies to design and build artificial systems, in particular artificial hands, and reduce the complexity associated with controlling a large number of degrees of freedom.

Neuroscience has leveraged recent advances in robotics research by using novel tools and methodological approaches to study how the central nervous system integrates sensory feedback with motor commands for hand control.


Abstract

The term ‘synergy’ – from the Greek synergia – means ‘working together’. The concept of multiple elements working together towards a common goal has been extensively used in neuroscience to develop theoretical frameworks, experimental approaches, and analytical techniques to understand neural control of movement, and for applications for neuro-rehabilitation. In the past decade, roboticists have successfully applied the framework of synergies to create novel design and control concepts for artificial hands, i.e., robotic hands and prostheses. At the same time, robotic research on the sensorimotor integration underlying the control and sensing of artificial hands has inspired new research approaches in neuroscience, and has provided useful instruments for novel experiments.

The ambitious goal of integrating expertise and research approaches in robotics and neuroscience to study the properties and applications of the concept of synergies is generating a number of multidisciplinary cooperative projects, among which the recently finished 4-year European project “The Hand Embodied” (THE). This paper reviews the main insights provided by this framework. Specifically, we provide an overview of neuroscientific bases of hand synergies and introduce how robotics has leveraged the insights from neuroscience for innovative design in hardware and controllers for biomedical engineering applications, including myoelectric hand prostheses, devices for haptics research, and wearable sensing of human hand kinematics. The review also emphasizes how this multidisciplinary collaboration has generated new ways to conceptualize a synergy-based approach for robotics, and provides guidelines and principles for analyzing human behavior and synthesizing artificial robotic systems based on a theory of synergies.

 

Source: Hand synergies: Integration of robotics and neuroscience for understanding the control of biological and artificial hands

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[ARTICLE] Biomechanical walking mechanisms underlying the metabolic reduction caused by an autonomous exoskeleton – Full Text HTML/PDF

Abstract

Background

Ankle exoskeletons can now reduce the metabolic cost of walking in humans without leg disability, but the biomechanical mechanisms that underlie this augmentation are not fully understood. In this study, we analyze the energetics and lower limb mechanics of human study participants walking with and without an active autonomous ankle exoskeleton previously shown to reduce the metabolic cost of walking.

Methods

We measured the metabolic, kinetic and kinematic effects of wearing a battery powered bilateral ankle exoskeleton. Six participants walked on a level treadmill at 1.4 m/s under three conditions: exoskeleton not worn, exoskeleton worn in a powered-on state, and exoskeleton worn in a powered-off state. Metabolic rates were measured with a portable pulmonary gas exchange unit, body marker positions with a motion capture system, and ground reaction forces with a force-plate instrumented treadmill. Inverse dynamics were then used to estimate ankle, knee and hip torques and mechanical powers.

Results

The active ankle exoskeleton provided a mean positive power of 0.105 ± 0.008 W/kg per leg during the push-off region of stance phase. The net metabolic cost of walking with the active exoskeleton (3.28 ± 0.10 W/kg) was an 11 ± 4 % (p = 0.019) reduction compared to the cost of walking without the exoskeleton (3.71 ± 0.14 W/kg). Wearing the ankle exoskeleton significantly reduced the mean positive power of the ankle joint by 0.033 ± 0.006 W/kg (p = 0.007), the knee joint by 0.042 ± 0.015 W/kg (p = 0.020), and the hip joint by 0.034 ± 0.009 W/kg (p = 0.006).

Conclusions

This study shows that the ankle exoskeleton does not exclusively reduce positive mechanical power at the ankle joint, but also mitigates positive power at the knee and hip. Furthermore, the active ankle exoskeleton did not simply replace biological ankle function in walking, but rather augmented the total (biological + exoskeletal) ankle moment and power. This study underscores the need for comprehensive models of human-exoskeleton interaction and global optimization methods for the discovery of new control strategies that optimize the physiological impact of leg exoskeletons.

Continue —> Biomechanical walking mechanisms underlying the metabolic reduction caused by an autonomous exoskeleton | Journal of NeuroEngineering and Rehabilitation | Full Text

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[ARTICLE] Neuroplasticity in action post-stroke: Challenges for physiotherapists

Knowledge regarding neuroplasticity post-stroke is increasingly expanding. In spite of this, only a few physiotherapy interventions have been able to demonstrate effectiveness in achieving recovery of lost sensorimotor control.

The aims of this review article are to highlight and discuss challenges for physiotherapists working with patients post-stroke, to question some current assessment methods and treatment approaches, and to pose critical questions indicating a possible new direction for physiotherapists in stroke rehabilitation.

Differentiation between recovery and compensation post-stroke is increasingly being emphasized. Implementation of this goal in the clinic is insufficient, with a lack of assessment tools with potential to discriminate between the concepts. Large-scale reviews are performed without considering whether functional gains are achieved through “more effective” compensatory strategies or through recovery. Cortical plasticity in neurorehabilitation research and voluntary control in contemporary treatment methods are in focus.

Challenges for physiotherapists in stroke rehabilitation consist of rethinking, including looking upon the body under the influence of gravity, focusing on implicit factors that impact movement control and developing new assessment tools. The introduction of a new assessment and treatment concept aiming at expanding the boundaries of center of mass movements towards the paretic side is proposed. In conclusion, we need to assume our responsibilities and step forward as the experts in movement science that we have the potential to be.

via Neuroplasticity in action post-stroke: Challenges for physiotherapists, European Journal of Physiotherapy, Informa Healthcare.

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[ARTICLE] The extent of altered digit force direction correlates with clinical upper extremity impairment in chronic stroke survivors

Abstract

Many stroke survivors suffer from impaired hand function. Biomechanics of hand grip suggests that abnormally directed grip force can hamper gripping abilities and hand function.

This study examined the relation between the ability to precisely direct fingertip force and clinical hand function scores among individuals affected by stroke. Specifically, clinical hand function tests of the Fugl-Meyer, Chedoke McMaster, and Box and Block Test were used, since they involve various hand movements required for activities of daily living. Digit force direction during static grip was recorded using multiaxial load cells. Data for 59 chronic stroke survivors were analyzed.

We found that larger angular deviation of digit force from the normal direction was significantly associated with lower hand functional levels (p<.001 for all three clinical tests). Particularly, stroke survivors whose digit force deviated more than 21° from the normal direction could not achieve the normal level of Fugl-Meyer or Chedoke or move more than 4 blocks in a minute. The biomechanics of the way digit force direction affects hand grip function is described. In addition, underlying mechanisms for altered digit force direction post stroke are postulated, including impaired somatosensation and abnormal neural input to muscles.

In summary, this study identifies a new biomechanical marker for hand functional level and recovery. Future interventions may focus on correcting digit force direction to improve hand functional outcome.

via The extent of altered digit force direction correlates with clinical upper extremity impairment in chronic stroke survivors.

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[ARTICLE] A Novel Hybrid Rehabilitation Robot for Upper and Lower Limbs Rehabilitation Training

Abstract

Stroke is the leading cause of severe disability worldwide, with up to 15 million of people suffer stroke every year. Survivors of stroke can recover their physical strength, provided they undergo proper rehabilitation. However, most of the rehabilitation centres provide only basic tools as they can rarely afford the expensive and advanced rehabilitation devices. Besides that, training with therapists is limited to few hours per week due to the large number of patients and the stroke patients are generally sent home once they are mobile, although their upper limbs functions are not recovered.

Stroke patients need to continue training after stroke to avoid muscle contraction, but due to large number of patients, they are not able to train frequently in the hospital. Therefore, the goal of this project is to develop a low-cost, simple yet compact rehabilitation robot for stroke patient to train both upper and lower limbs reaching movement. Compact Rehabilitation Robot (CR2) is expected to help the stroke patients training reaching movement in an enhanced virtual reality environment with haptic feedback and to provide the stroke patients with a faster track towards recovery.

via A Novel Hybrid Rehabilitation Robot for Upper and Lower Limbs Rehabilitation Training.

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