Adaptive walking assistance based on human-orthosis interaction

Rajasekaran, Vijaykumar; Aranda, Joan; Casals, Alı́cia

doi:10.1109/iros.2015.7354260

Cited by 6 publications

(13 citation statements)

References 12 publications

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“…Although it was not one of the main goals of this study, we measured the degree of assistance that the control strategy provided to healthy subjects and patients. The gait assistance for the healthy and SCI individuals is provided based on the adaptive control model presented in Rajasekaran et al ( 2015 ). The adaptive control applies an efficient stiffness to each joint, which is computed based on the interaction torques and position error of each joint.…”

Section: Resultsmentioning

confidence: 99%

“…A predefined trajectory, obtained from healthy subjects, was used as the desired gait pattern. The controller updated the stiffness values in real time according to the subject's performance in order to assist him/her just to the extent he/she needed (Rajasekaran et al, 2015 ). The exoskeleton was connected with long cables to its controller and to the power supply, which were on the trolley table.…”

Section: Methodsmentioning

confidence: 99%

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Control of an Ambulatory Exoskeleton with a Brain–Machine Interface for Spinal Cord Injury Gait Rehabilitation

et al. 2016

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The closed-loop control of rehabilitative technologies by neural commands has shown a great potential to improve motor recovery in patients suffering from paralysis. Brain–machine interfaces (BMI) can be used as a natural control method for such technologies. BMI provides a continuous association between the brain activity and peripheral stimulation, with the potential to induce plastic changes in the nervous system. Paraplegic patients, and especially the ones with incomplete injuries, constitute a potential target population to be rehabilitated with brain-controlled robotic systems, as they may improve their gait function after the reinforcement of their spared intact neural pathways. This paper proposes a closed-loop BMI system to control an ambulatory exoskeleton—without any weight or balance support—for gait rehabilitation of incomplete spinal cord injury (SCI) patients. The integrated system was validated with three healthy subjects, and its viability in a clinical scenario was tested with four SCI patients. Using a cue-guided paradigm, the electroencephalographic signals of the subjects were used to decode their gait intention and to trigger the movements of the exoskeleton. We designed a protocol with a special emphasis on safety, as patients with poor balance were required to stand and walk. We continuously monitored their fatigue and exertion level, and conducted usability and user-satisfaction tests after the experiments. The results show that, for the three healthy subjects, 84.44 ± 14.56% of the trials were correctly decoded. Three out of four patients performed at least one successful BMI session, with an average performance of 77.6 1 ± 14.72%. The shared control strategy implemented (i.e., the exoskeleton could only move during specific periods of time) was effective in preventing unexpected movements during periods in which patients were asked to relax. On average, 55.22 ± 16.69% and 40.45 ± 16.98% of the trials (for healthy subjects and patients, respectively) would have suffered from unexpected activations (i.e., false positives) without the proposed control strategy. All the patients showed low exertion and fatigue levels during the performance of the experiments. This paper constitutes a proof-of-concept study to validate the feasibility of a BMI to control an ambulatory exoskeleton by patients with incomplete paraplegia (i.e., patients with good prognosis for gait rehabilitation).

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Section: Resultsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Control of an Ambulatory Exoskeleton with a Brain–Machine Interface for Spinal Cord Injury Gait Rehabilitation

et al. 2016

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“…Comparing P.I.G.R.O. with other exoskeletons [19][20][21][22], it is possible to underline the following considerations.…”

Section: Methodsmentioning

confidence: 99%

“…In [19] an innovative assistive rehabilitation strategy is proposed by means of a wearable exoskeleton used without a treadmill and a body weight support. Here the dynamic stability of the patient is obtained by means of an efficient real-time stiffness adaptation for multiple joints (adaptive control system for assistive walking).…”

Section: Methodsmentioning

confidence: 99%

An Active Exoskeleton Called P.I.G.R.O. Designed for Unloaded Robotic Neurorehabilitation Training

Belforte¹,

Raparelli²,

Eula³

et al. 2020

Medical Robotics - New Achievements

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The development of innovative robotic devices allows the design of exoskeletons for robotic neurorehabilitation training. This paper presents the active exoskeleton called pneumatic interactive gait rehabilitation orthosis (P.I.G.R.O.), developed by the authors. The main innovative characteristic of this prototype is its design for fully unloaded robotic neurorehabilitation training, specific for brain-injured patients. It has six degrees of freedom (DOF) in the sagittal plane, an active ankle joint (removable if it is required); a wide range of anthropometric regulations, both for men and for women; a useful human machine interface (HMI); and an innovative harness system for the patient for the unloaded training. It is realized using light and strong materials, and it is electropneumatically controlled. In particular the authors also studied and defined some innovative input control curves useful for the unloaded training. In this paper, the main characteristics and innovations of P.I.G.R.O. are presented.

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“…This adaptation can be employed in general, even in the presence of external perturbations. A detailed description of this stiffness adaptation model is available in [ 38 , 49 ].…”

Section: Volitional-adaptive Controlmentioning

confidence: 99%

Volition-adaptive control for gait training using wearable exoskeleton: preliminary tests with incomplete spinal cord injury individuals

Rajasekaran

López‐Larraz

Trincado-Alonso

et al. 2018

J NeuroEngineering Rehabil

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BackgroundGait training for individuals with neurological disorders is challenging in providing the suitable assistance and more adaptive behaviour towards user needs. The user specific adaptation can be defined based on the user interaction with the orthosis and by monitoring the user intentions. In this paper, an adaptive control model, commanded by the user intention, is evaluated using a lower limb exoskeleton with incomplete spinal cord injury individuals (SCI).MethodsA user intention based adaptive control model has been developed and evaluated with 4 incomplete SCI individuals across 3 sessions of training per individual. The adaptive control model modifies the joint impedance properties of the exoskeleton as a function of the human-orthosis interaction torques and the joint trajectory evolution along the gait sequence, in real time. The volitional input of the user is identified by monitoring the neural signals, pertaining to the user’s motor activity. These volitional inputs are used as a trigger to initiate the gait movement, allowing the user to control the initialization of the exoskeleton movement, independently. A Finite-state machine based control model is used in this set-up which helps in combining the volitional orders with the gait adaptation.ResultsThe exoskeleton demonstrated an adaptive assistance depending on the patients’ performance without guiding them to follow an imposed trajectory. The exoskeleton initiated the trajectory based on the user intention command received from the brain machine interface, demonstrating it as a reliable trigger. The exoskeleton maintained the equilibrium by providing suitable assistance throughout the experiments. A progressive change in the maximum flexion of the knee joint was observed at the end of each session which shows improvement in the patient performance. Results of the adaptive impedance were evaluated by comparing with the application of a constant impedance value. Participants reported that the movement of the exoskeleton was flexible and the walking patterns were similar to their own distinct patterns.ConclusionsThis study demonstrates that user specific adaptive control can be applied on a wearable robot based on the human-orthosis interaction torques and modifying the joints’ impedance properties. The patients perceived no external or impulsive force and felt comfortable with the assistance provided by the exoskeleton. The main goal of such a user dependent control is to assist the patients’ needs and adapt to their characteristics, thus maximizing their engagement in the therapy and avoiding slacking. In addition, the initiation directly controlled by the brain allows synchronizing the user’s intention with the afferent stimulus provided by the movement of the exoskeleton, which maximizes the potentiality of the system in neuro-rehabilitative therapies.

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Adaptive walking assistance based on human-orthosis interaction

Cited by 6 publications

References 12 publications

Control of an Ambulatory Exoskeleton with a Brain–Machine Interface for Spinal Cord Injury Gait Rehabilitation

Control of an Ambulatory Exoskeleton with a Brain–Machine Interface for Spinal Cord Injury Gait Rehabilitation

An Active Exoskeleton Called P.I.G.R.O. Designed for Unloaded Robotic Neurorehabilitation Training

Volition-adaptive control for gait training using wearable exoskeleton: preliminary tests with incomplete spinal cord injury individuals

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