Ejercicio y resultados clínicos en pacientes con enfermedad de Parkinson: una revisión sistemática y metaanálisis

Antecedentes. La enfermedad de Parkinson (EP) es la segunda enfermedad neurodegenerativa más común en el mundo, la cual afecta el componente físico, psicológico y social de los individuos que la padecen. Numerosos estudios han abordado los beneficios de diferentes programas de ejercicio, llegando a ser una estrategia no-farmacológica efectiva para aminorar el deterioro funcional de los pacientes con EP. Objetivo. Determinar los efectos de las diferentes modalidades de ejercicio físico en los principales desenlaces clínicos en pacientes con EP. Métodos. Se consultaron las bases de datos MEDLINE, EMBASE, Scopus, CENTRAL y PEDro desde febrero de 1990 hasta febrero de 2014 para identificar Ensayos Clínicos Aleatorizados (ECA) publicados. Además, se examinaron las listas de referencias de otras revisiones y de estudios identificados. La extracción de datos se realizó por dos autores independientes. Se empleó un modelo de efectos aleatorios en presencia de heterogeneidad estadística (I2>50%). El sesgo de publicación fue evaluado mediante el gráfico de embudo. Resultados: Un total de 18 estudios fueron incluidos. Se encontraron diferencias estadísticamente significativas en las intervenciones con ejercicio y las siguientes medidas de resultado, severidad de los síntomas motores (MDS-UPDRS) DME 1.44, IC 95% [-2.09 a -0.78] (p<0.001) I2= 87,9% y el equilibrio DME 0,52 IC 95% [0,30 a 0,74] (p<0.001) I2= 85,6%. En el análisis de subgrupos en la modalidad de ejercicio aeróbico, en MDS-UPDRS DME -1,28, IC 95% [-1,98 a -0,59] (p<0.001), 3 calidad de vida DME -1,91 IC 95% [-2,76 a -1,07] (p<0.001), equilibrio DME 0,54 IC 95% [0,31 a 0,77] (p<0.001), 10-m WT DME 0,15 IC 95% [0,06 a 0,25] (p<0.001) y Vo2 máximo DME -1,09 IC 95% [-1,31 a -0,88] (p=0.001), 6MWT DME 40,46 IC 95% [11,28 a 69,65] (p=0.007). Conclusiones: El ejercicio aeróbico produjo mejoras significativas en MDS UPDRS, equilibrio, calidad de vida, 10-m WT y y Vo2 máximo; mientras que el ejercicio combinado mejoró la fuerza.

Reach & grasp therapy: Design and control of a 9-DOF robotic neuro-rehabilitation system

This paper presents the Gentle/G integrated system for reach & grasp therapy retraining following brain injury. The design, control and integration of an experimental grasp assistance unit is described for use in robot assisted stroke rehabilitation. The grasp assist unit is intended to work with the hardware and software of the Gentle/S robot although the hardware could be adapted to other rehabilitation applications. When used with the Gentle/S robot a total of 6 active and 3 passive degrees of freedom are available to provide active, active assist or passive grasp retraining in combination with reaching movements in a reach-grasp-transfer-release sequence.

Synthesis of Hand Exoskeletons for the Rehabilitation of Post-Stroke Patients

This dissertation presents the synthesis of a hand exoskeleton (HE) for the rehabilitation of post-stroke patients. Through the analysis of state-of-the-art, a topological classification was proposed. Based on the proposed classification principles, the rehabilitation HEs were systematically analyzed and classified. This classification is helpful to both understand the reason of proposing certain solutions for specific applications and provide some useful guidelines for the design of a new HE, that was actually the primary motivation of this study. Further to this classification, a novel rehabilitation HE was designed to support patients in cylindrical shape grasping tasks with the aim of recovering the basic functions of manipulation. The proposed device comprises five planar mechanisms, one per finger, globally actuated by two electric motors. Indeed, the thumb flexion/extension movement is controlled by one actuator whereas a second actuator is devoted to the control of the flexion/extension of the other four fingers. By focusing on the single finger mechanism, intended as the basic model of the targeted HE, the feasibility study of three different 1 DOF mechanisms are analyzed: a 6-link mechanism, that is connected to the human finger only at its tip, an 8-link and a 12-link mechanisms where phalanges and articulations are part of the kinematic chain. The advantages and drawbacks of each mechanism are deeply analyzed with respect to targeted requirements: the 12-link mechanism was selected as the most suitable solution. The dimensional synthesis based on the Burmester theory as well as kinematic and static analyses were separately done for all fingers in order to satisfy the desired specifications. The HE was finally designed and a prototype was built. The experimental results of the first tests are promising and demonstrate the potential for clinical applications of the proposed device in robot-assisted training of the human hand for grasping functions.

Feasibility of Using EMG for Early Detection of the Facial Nerve During Robotic Direct Cochlear Access

HYPOTHESIS Facial nerve monitoring can be used synchronous with a high-precision robotic tool as a functional warning to prevent of a collision of the drill bit with the facial nerve during direct cochlear access (DCA). BACKGROUND Minimally invasive direct cochlear access (DCA) aims to eliminate the need for a mastoidectomy by drilling a small tunnel through the facial recess to the cochlea with the aid of stereotactic tool guidance. Because the procedure is performed in a blind manner, structures such as the facial nerve are at risk. Neuromonitoring is a commonly used tool to help surgeons identify the facial nerve (FN) during routine surgical procedures in the mastoid. Recently, neuromonitoring technology was integrated into a commercially available drill system enabling real-time monitoring of the FN. The objective of this study was to determine if this drilling system could be used to warn of an impending collision with the FN during robot-assisted DCA. MATERIALS AND METHODS The sheep was chosen as a suitable model for this study because of its similarity to the human ear anatomy. The same surgical workflow applicable to human patients was performed in the animal model. Bone screws, serving as reference fiducials, were placed in the skull near the ear canal. The sheep head was imaged using a computed tomographic scanner and segmentation of FN, mastoid, and other relevant structures as well as planning of drilling trajectories was carried out using a dedicated software tool. During the actual procedure, a surgical drill system was connected to a nerve monitor and guided by a custom built robot system. As the planned trajectories were drilled, stimulation and EMG response signals were recorded. A postoperative analysis was achieved after each surgery to determine the actual drilled positions. RESULTS Using the calibrated pose synchronized with the EMG signals, the precise relationship between distance to FN and EMG with 3 different stimulation intensities could be determined for 11 different tunnels drilled in 3 different subjects. CONCLUSION From the results, it was determined that the current implementation of the neuromonitoring system lacks sensitivity and repeatability necessary to be used as a warning device in robotic DCA. We hypothesize that this is primarily because of the stimulation pattern achieved using a noninsulated drill as a stimulating probe. Further work is necessary to determine whether specific changes to the design can improve the sensitivity and specificity.

New Technologies and Concepts for Rehabilitation in the Acute Phase of Stroke: A Collaborative Matrix

The process of developing a successful stroke rehabilitation methodology requires four key components: a good understanding of the pathophysiological mechanisms underlying this brain disease, clear neuroscientific hypotheses to guide therapy, adequate clinical assessments of its efficacy on multiple timescales, and a systematic approach to the application of modern technologies to assist in the everyday work of therapists. Achieving this goal requires collaboration between neuroscientists, technologists and clinicians to develop well-founded systems and clinical protocols that are able to provide quantitatively validated improvements in patient rehabilitation outcomes. In this article we present three new applications of complementary technologies developed in an interdisciplinary matrix for acute-phase upper limb stroke rehabilitation – functional electrical stimulation, arm robot-assisted therapy and virtual reality-based cognitive therapy. We also outline the neuroscientific basis of our approach, present our detailed clinical assessment protocol and provide preliminary results from patient testing of each of the three systems showing their viability for patient use.

Enhanced Recovery after Urological Surgery: A Contemporary Systematic Review of Outcomes, Key Elements, and Research Needs

CONTEXT Enhanced Recovery after Surgery (ERAS) programs are multimodal care pathways that aim to decrease intra-operative blood loss, decrease postoperative complications, and reduce recovery times. OBJECTIVE To overview the use and key elements of ERAS pathways, and define needs for future clinical trials. EVIDENCE ACQUISITION A comprehensive systematic MEDLINE search was performed for English language reports published before May 2015 using the terms "postoperative period," "postoperative care," "enhanced recovery after surgery," "enhanced recovery," "accelerated recovery," "fast track recovery," "recovery program," "recovery pathway", "ERAS," and "urology" or "cystectomy" or "urologic surgery." EVIDENCE SYNTHESIS We identified 18 eligible articles. Patient counseling, physical conditioning, avoiding excessive alcohol and smoking, and good nutrition appeared to protect against postoperative complications. Fasting from solid food for only 6h and perioperative liquid-carbohydrate loading up to 2h prior to surgery appeared to be safe and reduced recovery times. Restricted, balanced, and goal-directed fluid replacement is effective when individualized, depending on patient morbidity and surgical procedure. Decreased intraoperative blood loss may be achieved by several measures. Deep vein thrombosis prophylaxis, antibiotic prophylaxis, and thermoregulation were found to help reduce postsurgical complications, as was a multimodal approach to postoperative nausea, vomiting, and analgesia. Chewing gum, prokinetic agents, oral laxatives, and an early resumption to normal diet appear to aid faster return to normal bowel function. Further studies should compare anesthetic protocols, refine analgesia, and evaluate the importance of robot-assisted surgery and the need/timing for drains and catheters. CONCLUSIONS ERAS regimens are multidisciplinary, multimodal pathways that optimize postoperative recovery. PATIENT SUMMARY This review provides an overview of the use and key elements of Enhanced Recovery after Surgery programs, which are multimodal, multidisciplinary care pathways that aim to optimize postoperative recovery. Additional conclusions include identifying effective procedures within Enhanced Recovery after Surgery programs and defining needs for future clinical trials.

RASMA: plataforma para la creación de animaciones Stop-motion con asistencia robótica

En este artículo se describe el concepto de plataforma RASMA, Robot-Assisted Stop-Motion Animation, cuya finalidd es facilitar la tarea de generar los fotogramas necesarios para crear una secuencia animada en 2D. Se describen tanto la generación de trayectorias que deben seguir los objetos (en Unity 3D o en Adobe Flash Player), como la exportación/importación de los ficheros de datos en XML, la planificación de las trayectorias del robot, la toma de fotogramas y el ensamblado final de toda la secuencia.

Optical Enhancement of Exoskeleton-Based Estimation of Glenohumeral Angles

In Robot-Assisted Rehabilitation (RAR) the accurate estimation of the patient limb joint angles is critical for assessing therapy efficacy. In RAR, the use of classic motion capture systems (MOCAPs) (e.g., optical and electromagnetic) to estimate the Glenohumeral (GH) joint angles is hindered by the exoskeleton body, which causes occlusions and magnetic disturbances. Moreover, the exoskeleton posture does not accurately reflect limb posture, as their kinematic models differ. To address the said limitations in posture estimation, we propose installing the cameras of an optical marker-based MOCAP in the rehabilitation exoskeleton. Then, the GH joint angles are estimated by combining the estimated marker poses and exoskeleton Forward Kinematics. Such hybrid system prevents problems related to marker occlusions, reduced camera detection volume, and imprecise joint angle estimation due to the kinematic mismatch of the patient and exoskeleton models. This paper presents the formulation, simulation, and accuracy quantification of the proposed method with simulated human movements. In addition, a sensitivity analysis of the method accuracy to marker position estimation errors, due to system calibration errors and marker drifts, has been carried out. The results show that, even with significant errors in the marker position estimation, method accuracy is adequate for RAR.

Improved joint control using a genetic algorithm for a humanoid robot

This paper describes experiments conducted in order to simultaneously tune 15 joints of a humanoid robot. Two Genetic Algorithm (GA) based tuning methods were developed and compared against a hand-tuned solution. The system was tuned in order to minimise tracking error while at the same time achieve smooth joint motion. Joint smoothness is crucial for the accurate calculation of online ZMP estimation, a prerequisite for a closedloop dynamically stable humanoid walking gait. Results in both simulation and on a real robot are presented, demonstrating the superior smoothness performance of the GA based methods.

Statistically assisted fluid registration algorithm - SAFIRA

In this paper, we develop and validate a new Statistically Assisted Fluid Registration Algorithm (SAFIRA) for brain images. A non-statistical version of this algorithm was first implemented in [2] and re-formulated using Lagrangian mechanics in [3]. Here we extend this algorithm to 3D: given 3D brain images from a population, vector fields and their corresponding deformation matrices are computed in a first round of registrations using the non-statistical implementation. Covariance matrices for both the deformation matrices and the vector fields are then obtained and incorporated (separately or jointly) in the regularizing (i.e., the non-conservative Lagrangian) terms, creating four versions of the algorithm. We evaluated the accuracy of each algorithm variant using the manually labeled LPBA40 dataset, which provides us with ground truth anatomical segmentations. We also compared the power of the different algorithms using tensor-based morphometry -a technique to analyze local volumetric differences in brain structure- applied to 46 3D brain scans from healthy monozygotic twins.