SpasticMyoElbow: Physical Human-Robot Interaction Simulation Framework for Modelling Elbow Spasticity.

Robotic devices hold great potential for efficient and reliable assessment of spasticity in post-stroke patients. However, the limited experimental data from patients with variable conditions has long posed a major barrier to quantitatively modelling spasticity with robotic measurements and fully validating robotic assessment techniques. As a result, spasticity is still assessed manually in current clinical settings.

Can Learning From Demonstration Approaches Encode and Generalise Human Movements for Neurorehabilitation?

The use of robotic systems in Upper-Limb (UL) neurorehabilitation typically involves semi-standardised, simple movement exercises controlled by the robot. However, alternative approaches aim to support more complex movements that align with Activities of Daily Living (ADLs) and offer greater customisation of interactions tailored to individual patients by clinicians. These approaches, however, require increased therapist involvement, which underscores the need for methods that allow clinicians to teach a set of exercises to the robot.

Robotic task specific training for upper limb neurorehabilitation: a mixed methods feasibility trial reporting achievable dose.

Purpose: Robotic devices for upper-limb neurorehabilitation allow an increase in intensity of practice, often relying on video game-based training strategies with limited capacity to individualise training and integrate functional training. This study shows the development of a robotic Task Specific Training (TST) protocol and evaluate the achieved dose.

Materials And Methods: Mixed-method study.

Using sEMG Signal Frequency to Evaluate Post-Stroke Elbow Spasticity.

Spasticity is a motor disorder with high prevalence and critical consequences following a stroke. Reliable and sensitive measurements are important to guide the selection and evaluation of treatment strategies. Technology-assisted methods, such as the surface electromyography (sEMG) technique, have been developed to measure spasticity as sensitive and accurate alternatives to commonly used clinical scales.

Technology-assisted assessment of spasticity: a systematic review.

Background: Spasticity is defined as "a motor disorder characterised by a velocity dependent increase in tonic stretch reflexes (muscle tone) with exaggerated tendon jerks". It is a highly prevalent condition following stroke and other neurological conditions. Clinical assessment of spasticity relies predominantly on manual, non-instrumented, clinical scales.

A Practical Post-Stroke Elbow Spasticity Assessment Using an Upper Limb Rehabilitation Robot: A Validation Study.

Spasticity is a motor disorder characterised by a velocity-dependent increase in muscle tone, which is critical in neurorehabilitation given its high prevalence and potential negative influence among the post-stroke population. Accurate measurement of spasticity is important as it guides the strategy of spasticity treatment and evaluates the effectiveness of spasticity management. However, spasticity is commonly measured using clinical scales which may lack objectivity and reliability.

Application of the extended technology acceptance model to explore clinician likelihood to use robotics in rehabilitation.

Purpose: Evidence suggests that patients with upper limb impairment following a stroke do not receive recommended amounts of motor practice. Robotics provide a potential solution to address this gap, but clinical adoption is low. The aim of this study was to utilize the technology acceptance model as a framework to identify factors influencing clinician adoption of robotic devices into practice.

Towards a Gaze-Informed Movement Intention Model for Robot-Assisted Upper-Limb Rehabilitation.

Gaze-based intention detection has been explored for robotic-assisted neuro-rehabilitation in recent years. As eye movements often precede hand movements, robotic devices can use gaze information to augment the detection of movement intention in upper-limb rehabilitation. However, due to the likely practical drawbacks of using head-mounted eye trackers and the limited generalisability of the algorithms, gaze-informed approaches have not yet been used in clinical practice.

Inducing Human Motor Adaptation Without Explicit Error Feedback: A Motor Cost Approach.

Recent studies have shown that motor adaptation is an optimisation process on both kinematic error and effort. This work aims to induce a motor adaption in an experimental setup solely relying on the effort without any explicit kinematic error. In this experiment, the intervention space and adaptation space are decoupled: while the force field only applies to the hand linear velocity, the adaptation is expected to happen in the arm joint null space (i.

Promoting clinical best practice in a user-centred design study of an upper limb rehabilitation robot.

Purpose: Despite their promise to increase therapy intensity in neurorehabilitation, robotic devices have not yet seen mainstream adoption. Whilst there are a number of contributing factors, it is obvious that the treating clinician should have a clear understanding of the objectives and limitations of robotic device use. This study sought to explore how devices can be developed to support a clinician in providing clinical best practice.

Indirect Robotic Movement Shaping through Motor Cost Influence.

Movement patterns are commonly disrupted after a neurological incident. The correction and recovery of these movement patterns is part of therapeutic practice, and should be considered in the development of robotic device control strategies. This is an area which has limited exploration in rehabilitation robotics literature.

Capturing Upper Limb Gross Motor Categories Using the Kinect® Sensor.

Importance: Along with growth in telerehabilitation, a concurrent need has arisen for standardized methods of tele-evaluation.

Objective: To examine the feasibility of using the Kinect sensor in an objective, computerized clinical assessment of upper limb motor categories.

Design: We developed a computerized Mallet classification using the Kinect sensor.

Effect Of Arm Deweighting Using End-Effector Based Robotic Devices On Muscle Activity.

Deweighting of the limb is commonly performed for patients with a neurological injury, such as stroke, as it allows these patients with limited muscle activity to perform movements. Deweighting has been implemented in exoskeletons and other multi-contact devices, but not on an end-effector based device with single contact point between the assisting robot and the human limb being assisted. This study inves-tigates the effects of deweighting using an end-effector based device on healthy subjects.

Modulation of shoulder muscle and joint function using a powered upper-limb exoskeleton.

Robotic-assistive exoskeletons can enable frequent repetitive movements without the presence of a full-time therapist; however, human-machine interaction and the capacity of powered exoskeletons to attenuate shoulder muscle and joint loading is poorly understood. This study aimed to quantify shoulder muscle and joint force during assisted activities of daily living using a powered robotic upper limb exoskeleton (ArmeoPower, Hocoma). Six healthy male subjects performed abduction, flexion, horizontal flexion, reaching and nose touching activities.

EMU: A transparent 3D robotic manipulandum for upper-limb rehabilitation.

This paper introduces the EMU, a three-dimensional robotic manipulandum for rehabilitation of the upper extremity for patients with neurological injury. The device has been designed to be highly transparent, have a large workspace, and allow the use of the hand for interaction with real-world objects to provide additional contextual cues during exercises. The transparency is achieved through the use of a capstan transmission for the drive joints; a hybrid serial parallel kinematics minimising moving inertia; and lightweight materials.

Modifying Kinect placement to improve upper limb joint angle measurement accuracy.

Study Design: Repeated measures.

Introduction: The Kinect (Microsoft, Redmond, WA) is widely used for telerehabilitation applications including rehabilitation games and assessment.

Purpose Of The Study: To determine effects of the Kinect location relative to a person on measurement accuracy of upper limb joint angles.

Usability evaluation of low-cost virtual reality hand and arm rehabilitation games.

The emergence of lower-cost motion tracking devices enables home-based virtual reality rehabilitation activities and increased accessibility to patients. Currently, little documentation on patients' expectations for virtual reality rehabilitation is available. This study surveyed 10 people with stroke for their expectations of virtual reality rehabilitation games.

Upper-Limb Robotic Exoskeletons for Neurorehabilitation: A Review on Control Strategies.

Since the late 1990s, there has been a burst of research on robotic devices for poststroke rehabilitation. Robot-mediated therapy produced improvements on recovery of motor capacity; however, so far, the use of robots has not shown qualitative benefit over classical therapist-led training sessions, performed on the same quantity of movements. Multidegree-of-freedom robots, like the modern upper-limb exoskeletons, enable a distributed interaction on the whole assisted limb and can exploit a large amount of sensory feedback data, potentially providing new capabilities within standard rehabilitation sessions.

Robotic exoskeletons: a perspective for the rehabilitation of arm coordination in stroke patients.

Upper-limb impairment after stroke is caused by weakness, loss of individual joint control, spasticity, and abnormal synergies. Upper-limb movement frequently involves abnormal, stereotyped, and fixed synergies, likely related to the increased use of sub-cortical networks following the stroke. The flexible coordination of the shoulder and elbow joints is also disrupted.

Constraining upper limb synergies of hemiparetic patients using a robotic exoskeleton in the perspective of neuro-rehabilitation.

The aim of this paper was to explore how an upper limb exoskeleton can be programmed to impose specific joint coordination patterns during rehabilitation. Based on rationale which emphasizes the importance of the quality of movement coordination in the motor relearning process, a robot controller was developed with the aim of reproducing the individual corrections imposed by a physical therapist on a hemiparetic patient during pointing movements. The approach exploits a description of the joint synergies using principal component analysis (PCA) on joint velocities.

A methodology to quantify alterations in human upper limb movement during co-manipulation with an exoskeleton.

While a large number of robotic exoskeletons have been designed by research teams for rehabilitation, it remains rather difficult to analyse their ability to finely interact with a human limb: no performance indicators or general methodology to characterize this capacity really exist. This is particularly regretful at a time when robotics are becoming a recognized rehabilitation method and when complex problems such as 3-D movement rehabilitation and joint rotation coordination are being addressed. The aim of this paper is to propose a general methodology to evaluate, through a reduced set of simple indicators, the ability of an exoskeleton to interact finely and in a controlled way with a human.