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Gallego J.A.,Bioengineering Group | Rocon E.,Bioengineering Group | Belda-Lois J.M.,Polytechnic University of Valencia | Belda-Lois J.M.,CIBER ISCIII | Pons J.L.,Bioengineering Group
Journal of NeuroEngineering and Rehabilitation | Year: 2013

Background: Pathological tremor is the most prevalent movement disorder. Current treatments do not attain a significant tremor reduction in a large proportion of patients, which makes tremor a major cause of loss of quality of life. For instance, according to some estimates, 65% of those suffering from upper limb tremor report serious difficulties during daily living. Therefore, novel forms for tremor management are required. Since muscles intrinsically behave as a low pass filter, and tremor frequency is above that of volitional movements, the authors envisioned the exploitation of these properties as a means of developing a novel treatment alternative. This treatment would rely on muscle co-contraction for tremor management, similarly to the strategy employed by the intact central nervous system to stabilize a limb during certain tasks. Methods. We implemented a neuroprosthesis that regulated the level of muscle co-contraction by injecting current at a pair of antagonists through transcutaneous neurostimulation. Co-contraction was adapted to the instantaneous parameters of tremor, which were estimated from the raw recordings of a pair of solid state gyroscopes with a purposely designed adaptive algorithm. For the experimental validation, we enrolled six patients suffering from parkinsonian or essential tremor of different severity, and evaluated the effect of the neuroprosthesis during standard tasks employed for neurological examination. Results: The neuroprosthesis attained significant attenuation of tremor (p<0.001), and reduced its amplitude up to a 52.33±25.48%. Furthermore, it alleviated both essential and parkinsonian tremor in spite of their different etiology and symptomatology. Tremor severity was not a limiting factor on the performance of the neuroprosthesis, although there was a subtle trend towards larger attenuation of more severe tremors. Tremor frequency was not altered during neurostimulation, as expected from the central origin of Parkinson's disease and essential tremor. All patients showed a good tolerance to neurostimulation in terms of comfort and absence of pain, and some spontaneously reported that they felt that tremor was reduced when the neuroprosthesis was activated. Conclusions: The results presented herein demonstrate that the neuroprosthesis provides systematic attenuation of the two major types of tremor, irrespectively from their severity. This study sets the basis for the validation of the neuroprosthesis as an alternative, non-invasive means for tremor management. © 2013 Gallego et al.; licensee BioMed Central Ltd.


Martins M.M.,University of Minho | Santos C.P.,University of Minho | Frizera-Neto A.,Federal University of Espirito Santo | Ceres R.,Bioengineering Group
Robotics and Autonomous Systems | Year: 2012

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. © 2011 Elsevier B.V. All rights reserved.


Forner-Cordero I.,Hospital la Fe | Munoz-Langa J.,University of Valencia | Forner-Cordero A.,Bioengineering Group | Demiguel-Jimeno J.M.,Hospital San Pedro
Annals of Surgical Oncology | Year: 2010

Background: Many studies have reported the benefits of Decongestive treatment in patients with breast-cancer-related lymphedema (BCRL) but few have study what are the predictive factors of response. Methods: We performed a prospective, multicenter controlled cohort study of 171 patients with BCRL to identify independent predictive factors of response to decongestive treatment (CDT). Demographic data and clinical and lymphedema characteristics were collected prospectively. The end point was the "percentage reduction in excess volume (PREV)." Volumes were measured prior and at the end of CDT. Factors associated with response (PREV) were tested in univariate and multivariate analyses using linear regression techniques. Results: Median age was 60.4 years (range 32-84); mean lymphedema chronicity 4 years [95% confidence interval (95% CI): 3.1-5.0]; mean baseline excess volume (EV) was 936 mL (95% CI: 846-1026), and mean percentage EV was 35.3% (95% CI: 32.0-38.7); compliance to bandages was good in 81.3% of patients. PREV was 71.7% (95% CI: 65.2-78.2). After univariate screening, 11 variables were found to be associated with PREV but only 4 variables were independent predictive factors of response to CDT in the multivariate analysis: Venous insufficiency, percentage of EV (the higher the EV, the lower the reduction with CDT); compliance to bandages (a good compliance improved PREV in 25%), and treatment in autumn (better results than during the rest of the year). Conclusions: This study shows that compliance to bandages during CDT is one of the most important predictors of response. Moreover, data support the idea that more severe lymphedemas have a worse response to treatment, and it should be recommended in early stages. The association between the season of treatment and response was also very strong, so weather conditions are an additional factor that must be taken into account in further studies. © 2009 Society of Surgical Oncology.


Del-Ama A.J.,National Hospital for Spinal Cord Injury | Del-Ama A.J.,Bioengineering Group | Gil-Agudo A.,National Hospital for Spinal Cord Injury | Pons J.L.,Bioengineering Group | Moreno J.C.,Bioengineering Group
Journal of NeuroEngineering and Rehabilitation | Year: 2014

Robotic and functional electrical stimulation (FES) approaches are used for rehabilitation of walking impairment of spinal cord injured individuals. Although devices are commercially available, there are still issues that remain to be solved. Control of hybrid exoskeletons aims at blending robotic exoskeletons and electrical stimulation to overcome the drawbacks of each approach while preserving their advantages. Hybrid actuation and control have a considerable potential for walking rehabilitation but there is a need of novel control strategies of hybrid systems that adequately manage the balance between FES and robotic controllers. Combination of FES and robotic control is a challenging issue, due to the non-linear behavior of muscle under stimulation and the lack of developments in the field of hybrid control. In this article, a cooperative control strategy of a hybrid exoskeleton is presented. This strategy is designed to overcome the main disadvantages of muscular stimulation: electromechanical delay and change in muscle performance over time, and to balance muscular and robotic actuation during walking.Experimental results in healthy subjects show the ability of the hybrid FES-robot cooperative control to balance power contribution between exoskeleton and muscle stimulation. The robotic exoskeleton decreases assistance while adequate knee kinematics are guaranteed. A new technique to monitor muscle performance is employed, which allows to estimate muscle fatigue and implement muscle fatigue management strategies. Kinesis is therefore the first ambulatory hybrid exoskeleton that can effectively balance robotic and FES actuation during walking. This represents a new opportunity to implement new rehabilitation interventions to induce locomotor activity in patients with paraplegia.Acronym list: 10mWT: ten meters walking test; 6MWT: six minutes walking test; FSM: finite-state machine; t-FSM: time-domain FSM; c-FSM: cycle-domain FSM; FES: functional electrical stimulation; HKAFO: hip-knee-ankle-foot orthosis; ILC: iterative error-based learning control; MFE: muscle fatigue estimator; NILC: Normalized stimulation output from ILC controller; PID: Proportional-Integral-derivative Control; PW: Stimulation pulse width; QUEST: Quebec User Evaluation of Satisfaction with assistive Technology; SCI: Spinal cord injury; TTI: torque-time integral; VAS: Visual Analog Scale. © 2014 del-Ama et al.; licensee BioMed Central Ltd.


del-Ama A.J.,National Hospital for Spinal Cord Injury | Gil-Agudo A.,National Hospital for Spinal Cord Injury | Pons J.L.,Bioengineering Group | Moreno J.C.,Bioengineering Group
Frontiers in Human Neuroscience | Year: 2014

Locomotor training has proved to provide beneficial effect in terms of mobility in incomplete paraplegic patients. Neuroprosthetic technology can contribute to increase the efficacy of a training paradigm in the promotion of a locomotor pattern. Robotic exoskeletons can be used to manage the unavoidable loss of performance of artificially driven muscles. Hybrid exoskeletons blend complementary robotic and neuro-prosthetic technologies. The aim of this pilot study was to determine the effects of hybrid gait training in three case studies with persons with incomplete spinal cord injury (iSCI) in terms of locomotion performance during assisted gait, patient-robot adaptations, impact on ambulation and assessment of lower limb muscle strength and spasticity. Participants with iSCI received interventions with a hybrid bilateral exoskeleton for 4 days. Assessment of gait function revealed that patients improved the 6 min and 10 m walking tests after the intervention, and further improvements were observed 1 week after the intervention. Muscle examination revealed improvements in knee and hip sagittal muscle balance scores and decreased score in ankle extensor balance. It is concluded that improvements in biomechanical function of the knee joint after the tested overground hybrid gait trainer are coherent with improvements in gait performance. © 2014 del-Ama, Gil-Agudo, Pons and Moreno.


Gallego J.A.,Bioengineering Group
Conference proceedings : ... Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Conference | Year: 2011

In spite of decades of intense research, pathological tremors still constitute unknown disorders. This study addresses, based on a multi-scale model, the behavior of an entire pool of motor neurons in tremor, under the hypothesis that tremor is an oscillation of central origin commonly projected to all motor neurons that innervate a muscle. Our results show that under such conditions both paired discharges and enhanced motor neuron synchronization, two of the characteristic landmarks of tremor, emerge. Moreover, coherence and correlation analyses suggest that the central tremor oscillator is transmitted linearly by the motor neuron pool given that a small set (7 or 8) of motor neurons are sampled.


Rocon E.,Bioengineering Group
Conference proceedings : ... Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Conference | Year: 2010

Tremor constitutes the most common movement disorder; in fact 14.5% of population between 50 to 89 years old suffers from it. Moreover, 65% of patients with upper limb tremor report disability when performing their activities of daily living (ADL). Unfortunately, 25% of patients do not respond to drugs or neurosurgery. In this regard, TREMOR project proposes functional compensation of upper limb tremors with a soft wearable robot that applies biomechanical loads through functional electrical stimulation (FES) of muscles. This wearable robot is driven by a Brain Neural Computer Interface (BNCI). This paper presents a multimodal BCI to assess generation, transmission and execution of both volitional and tremorous movements based on electroencephalography (EEG), electromyography (EMG) and inertial sensors (IMUs). These signals are combined to obtain: 1) the intention to perform a voluntary movement from cortical activity (EEG), 2) tremor onset, and an estimation of tremor frequency from muscle activation (EMG), and 3) instantaneous tremor amplitude and frequency from kinematic measurements (IMUs). Integration of this information will provide control signals to drive the FES-based wearable robot.


Pons J.L.,Bioengineering Group
IEEE Engineering in Medicine and Biology Magazine | Year: 2010

Exoskeletons are wearable robots exhibiting a close cognitive and physical interaction with the human user. These are rigid robotic exoskeletal structures that typically operate alongside human limbs. Scientific and technological work on exoskeletons began in the early 1960s but have only recently been applied to rehabilitation and functional substitution in patients suffering from motor disorders. Key topics for further development of exoskeletons in rehabilitation scenarios include the need for robust humanrobot multimodal cognitive interaction, safe and dependable physical interaction, true wearability and portability, and user aspects such as acceptance and usability. This discussion provides an overview of these aspects and draws conclusions regarding potential future research directions in robotic exoskeletons. © 2006 IEEE.


Piazza S.,Bioengineering Group
Conference proceedings : ... Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Conference | Year: 2012

Hybrid exoskeletons combine robotic orthoses and motor neuroprosthetic devices to compensate for motor disabilities and assist rehabilitation. The basic idea is to take benefits from the strength of each technology, primarily the power of robotic actuators and the clinical advantages of using patient's muscles, while compensating for the respective weaknesses: weight and autonomy for the former, fatigue and stability for the latter. While a wide repertory of solutions have been proposed in literature for the control of robotic orthoses and simple motor neuroprosthesis, the same problem on a complex hybrid architecture, involving a wide number of muscles distributed on multiple articulations, still waits for a practical solution. In this article we present a general algorithm for the control of the neuroprosthesis in the execution of functional coordinated movements. The method extracts muscle synergies as a mean to diagnose residual neuromotor capabilities, and adapts the rehabilitation exercise to patient requirements in a dynamic way. Fatigue effects and unexpected perturbations are compensated by monitoring functional state variables estimated from sensors in the robot. The proposed concept is applied to a case-study scenario, in which a postural balance rehabilitation therapy is presented.


Collantes I.,Bioengineering Group
Conference proceedings : ... Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Conference | Year: 2012

Recent studies have shown evidence indicating that effective robotic rehabilitation is only possible when the user actively participates during training. Providing a complete effective biofeedback to the patient representing his compliance to the therapy and his performance is thought that his active participation will be enhanced significantly, thus, improving his rehabilitation. We have performed a study with the driven gait orthosis (DGO) Lokomat (Hocoma AG, Volketswil, Switzerland). The objective of the present study is the analysis of the effect of different types of participation (attention to the functional task) from subjects receiving robotic assisted gait training on the kinematic and kinetic patterns. The obtained results provide useful evidence of specific biomechanical features that can be used to design more useful, robust, focused and intuitive biomechanical biofeedback during robotic assisted gait rehabilitation in stroke survivors.

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