Sensorized Tip for Monitoring People with Multiple Sclerosis that Require Assistive Devices for Walking

Multiple Sclerosis (MS) is a neurological degenerative disease with high impact on our society. In order to mitigate its effects, proper rehabilitation therapy is mandatory, in which individualisation is a key factor. Technological solutions can provide the information required for this purpose, by monitoring patients and extracting relevant indicators. In this work, a novel Sensorized Tip is proposed for monitoring People with Multiple Sclerosis (PwMS) that require Assistive Devices for Walking (ADW) such as canes or crutches. The developed Sensorized Tip can be adapted to the personal ADW of each patient to reduce its impact, and provides sensor data while naturally walking in the everyday activities. This data that can be processed to obtain relevant indicators that helps assessing the status of the patient. Different from other approaches, a full validation of the proposed processing algorithms is carried out in this work, and a preliminary study-case is carried out with PwMS considering a set of indicators obtained from the Sensorized Tip’s processed data. Results of the preliminary study-case demonstrate the potential of the device to monitor and characterise patient status

Virtual Sensors For Advanced Controllers In Rehabilitation Robotics

In order to properly control rehabilitation robotic devices, the measurement of interaction force and motion between patient and robot is an essential part. Usually, however, this is a complex task that requires the use of accurate sensors which increase the cost and the complexity of the robotic device. In this work, we address the development of virtual sensors that can be used as an alternative of actual force and motion sensors for the Universal Haptic Pantograph (UHP) rehabilitation robot for upper limbs training. These virtual sensors estimate the force and motion at the contact point where the patient interacts with the robot using the mathematical model of the robotic device and measurement through low cost position sensors. To demonstrate the performance of the proposed virtual sensors, they have been implemented in an advanced position/force controller of the UHP rehabilitation robot and experimentally evaluated. The experimental results reveal that the controller based on the virtual sensors has similar performance to the one using direct measurement (less than 0.005 m and 1.5 N difference in mean error). Hence, the developed virtual sensors to estimate interaction force and motion can be adopted to replace actual precise but normally high-priced sensors which are fundamental components for advanced control of rehabilitation robotic devices.This work was supported in part by the Basque Country Governments (GV/EJ) under grant PRE-2014-1-152, UPV/EHU's PPG17/56 project, Basque Country Governments IT914-16 project, Spanish Ministry of Economy and Competitiveness' MINECO & FEDER inside DPI2017-82694-R project, Euskampus, FIK and Spanish Ministry of Science and Innovation PDI-020100-2009-21 project

Kinematical and dynamical modelling of a multipurpose upper limbs rehabilitation robot

Knowing accurate model of a system is always beneficial to design a robust and safe control while allowing reduction of sensors-related cost as the system outputs are predictable using the model. In this context, this paper addresses the kinematical and dynamical model identification of the multipurpose rehabilitation robot, Universal Haptic Pantograph (UHP), and present experimental validations of the identified models. The UHP is a Pantograph based innovative robot actuated by two SEAs (Series Elastic Actuator), aiming at training impaired upper limbs after a stroke. This novel robot, thanks to its lockable/unlockable joints, can change its mechanical structure so that it enables stroke patient to perform different training exercises of the shoulder, elbow and wrist. This work focuses on the ARM mode, which is a training mode used to rehabilitate elbow and shoulder. The kinematical model of UHP is identified based on the loop vector equations, while the dynamical model is derived based on the Lagrangian formulation. To demonstrate the accuracy of the models, several experimental tests were performed. The results reveal that the mean position error between estimated values with the model and actual measured values stays in 3 mm (less than 2% of the maximum motion range). Moreover, the error between estimated and measured interaction force is smaller than 10% of maximum force range. So, the developed models can be adopted to estimate motion and force of UHP as well as control it without the need of additional sensors such as a force sensor, resulting in the reduction of total robot cost.This work was supported in part by the Basque Country Governments (GV/EJ) under grant PRE-2014-1-152, UPV/EHU’s PPG17/56 project, Basque Country Governments IT914-16 project, Spanish Ministry of Economy and Competitiveness’ MINECO & FEDER inside DPI2012-32882 projects, Spanish Ministry of Economy and Competitiveness BES-2013-066142 grant, Euskampus, FIK

Virtual Sensors for On-line Wheel Wear and Part Roughness Measurement in the Grinding Process

Grinding is an advanced machining process for the manufacturing of valuable complex and accurate parts for high added value sectors such as aerospace, wind generation, etc. Due to the extremely severe conditions inside grinding machines, critical process variables such as part surface finish or grinding wheel wear cannot be easily and cheaply measured on-line. In this paper a virtual sensor for on-line monitoring of those variables is presented. The sensor is based on the modelling ability of Artificial Neural Networks (ANNs) for stochastic and non-linear processes such as grinding; the selected architecture is the Layer-Recurrent neural network. The sensor makes use of the relation between the variables to be measured and power consumption in the wheel spindle, which can be easily measured. A sensor calibration methodology is presented, and the levels of error that can be expected are discussed. Validation of the new sensor is carried out by comparing the sensor's results with actual measurements carried out in an industrial grinding machine. Results show excellent estimation performance for both wheel wear and surface roughness. In the case of wheel wear, the absolute error is within the range of microns (average value 32 mu m). In the case of surface finish, the absolute error is well below R-a 1 mu m (average value 0.32 mu m). The present approach can be easily generalized to other grinding operations.Thanks are given to the Spanish Ministry of Economy and Competitiveness for their support of the Research Project. Integration of numerical models and experimental techniques for improving the added value in grinding of precision parts. (DPI2010-21652-C02-01). This work was also supported in part by the Regional Government of the Basque Country through the Departamento de Educacion, Universidades e Investigacion (Project IT719-13) and UPV/EHU under grant UFI11/28

Intelligent Sitting Posture Classifier for Wheelchair Users

In recent years, there has been growing interest in postural monitoring while seated, thus preventing the appearance of ulcers and musculoskeletal problems in the long term. To date, postural control has been carried out by means of subjective questionnaires that do not provide continuous and quantitative information. For this reason, it is necessary to carry out a monitoring that allows to determine not only the postural status of wheelchair users, but also to infer the evolution or anomalies associated with a specific disease. Therefore, this paper proposes an intelligent classifier based on a multilayer neural network for the classification of sitting postures of wheelchair users. The posture database was generated based on data collected by a novel monitoring device composed of force resistive sensors. A training and hyperparameter selection methodology has been used based on the idea of using a stratified K-Fold in weight groups strategy. This allows the neural network to acquire a greater capacity for generalization, thus allowing, unlike other proposed models, to achieve higher success rates not only in familiar subjects but also in subjects with physical complexions outside the standard. In this way, the system can be used to support wheelchair users and healthcare professionals, helping them to automatically monitor their posture, regardless physical complexions.This work was supported in part by the Ministry of Science and Innovation-StateResearch Agency/Project funded by MCIN/State Research Agency(AEI)/10.13039/501100011033 under Grant PID2020-112667RB-I00,in part by the Basque Government under Grant IT1726-22, and in part by the Predoctoral Contracts of the Basque Government under Grant PRE-2021-1-0001 and Grant PRE-2021-1-021

Robot de rehabilitación configurable para terapias del miembro superior

La rehabilitación basada en dispositivos robóticos precisa de un robot capaz de adaptarse al estado de recuperación motora del paciente. En este trabajo se presenta un robot de rehabilitación reconfigurable denominado Universal Haptic Pantograph (UHP). Este dispositivo robótico, gracias a su estructura multiconfigurable, permite la rehabilitación del miembro superior (hombro, codo y muñeca) con un único dispositivo. Además, ha sido diseñado para trabajar con diferentes modalidades de interacción como son las asistidas, correctoras y opositoras, pudiendo así adaptarse al estado funcional progresivo del paciente durante el proceso de rehabilitación. Con el objetivo de garantizar el correcto funcionamiento de este sistema robótico se han realizado diferentes ensayos experimentales. Los resultados demuestran que el robot de rehabilitación UHP funciona correctamente con diferentes tareas de rehabilitación, realizando movimientos suaves que garantizan la seguridad del usuario en todo momento.Este trabajo ha sido parcialmente financiado por el Ministerio de Economía y Competitividad MINECO & FEDER en el marco del proyecto DPI-2012-32882, así como por la beca PRE-2014-1-152 y el proyecto IT914-16 del Gobierno Vasco, el proyecto PPG17/56 de la UPV/EHU y por Euskampus Fundazioa. Además, los autores desean expresar su agradecimiento al centro de investigación Tecnalia por su colaboración y por prestar su robot de rehabilitación UHP

Inclusive and seamless control framework for safe robot-mediated therapy for upper limbs rehabilitation

Robot-based rehabilitation requires not only the use of a suitable robot, but also an optimal strategy to guarantee that the interaction forces with the patient fit his or her impairment level. In this work, an inclusive and seamless control framework for upper limb rehabilitation robots is presented and validated. The proposed control framework involves 1) a complete set of training modes (assistive, corrective and resistive) that can be adapted to the needs of the different states of the patient’s recovery, and 2) three different advanced controllers (position, force, impedance) to track safely the force and motion references defined by the aforementioned training modes. In addition, the proposed framework allows one to tune the parameters critical to the safety of the user, such as the maximum interaction forces or the maximum speed of the robot movement. In order to validate the proposed control framework, a set of experiments have been carried out in the Universal Haptic Pantograph (UHP) upperlimb rehabilitation robot. Results show that the proposed control framework for robot-mediated therapy works properly in terms of adaptability, robustness, and safety, which are crucial factors for use with patients.This work was supported in part by the Basque Country Governments (GV/EJ) under grant PRE-2014-1-152, UPV/EHU’s PPG17/56 project, Basque Country Governments IT914-16 project, Spanish Ministry of Economy and Competitiveness’ MINECO & FEDER inside DPI2017- 82694-R project, Euskampus, FIK and Spanish Ministry of Science and Innovation PDI-020100-2009-21 project

Pre-clinical validation of the UHP multifunctional upper-limb rehabilitation robot based platform

Interest in robotic devices for rehabilitation has increased in the last years, due to the increasing number of patients that require rehabilitation therapies, and the need to optimize existing resources. The UHP rehabilitation robot is a multifunctional device that allows to execute robotized therapies for the upper-limb using a simple pantograph based reconfigurable structure and the implementation of advanced position/force control approaches. However, in applications such as rehabilitation, where the robotic device interacts directly with the user, complying with the demands of the users is as important as complying with the functional requirements. Otherwise, the patient will reject the robotic device. Therefore, in this work the pre-clinical validation of the UHP upper-limb rehabilitation robotic platform is presented. 25 subjects of different physical characteristics have participated in the evaluation of the device, evaluating not only the correct behaviour of the device, but also its safety and adaptativity. Results show the correct behaviour of the platform, and a good acceptance rate of the device.This work was supported in part by the Basque Country Governments (GV/EJ) under grant PRE-2014-1-152, UPV/EHU’s PPG17/56 project, Basque Country Governments IT914-16 project, Spanish Ministry of Economy and Competitiveness’ MINECO & FEDER inside DPI2017-82694-R project, Euskampus, FIK and Spanish Ministry of Science and Innovation PDI-020100-2009-21 project

Virtual Sensor for Kinematic Estimation of Flexible Links in Parallel Robots

The control of flexible link parallel manipulators is still an open area of research, endpoint trajectory tracking being one of the main challenges in this type of robot. The flexibility and deformations of the limbs make the estimation of the Tool Centre Point (TCP) position a challenging one. Authors have proposed different approaches to estimate this deformation and deduce the location of the TCP. However, most of these approaches require expensive measurement systems or the use of high computational cost integration methods. This work presents a novel approach based on a virtual sensor which can not only precisely estimate the deformation of the flexible links in control applications (less than 2% error), but also its derivatives (less than 6% error in velocity and 13% error in acceleration) according to simulation results. The validity of the proposed Virtual Sensor is tested in a Delta Robot, where the position of the TCP is estimated based on the Virtual Sensor measurements with less than a 0.03% of error in comparison with the flexible approach developed in ADAMS Multibody Software.This work was supported in part by the Spanish Ministry of Economy and Competitiveness under grant BES-2013-066142, UPV/EHU's PPG17/56 projects, Spanish Ministry of Economy and Competitiveness' MINECO & FEDER inside DPI-2012-32882 project and the Basque Country Government's (GV/EJ) under PRE-2014-1-152 and BFI-2012-223 grants and under recognized research group IT914-16

A preliminary analysis of gait performance of patients with multiple sclerosis using a sensorized crutch tip

The quality of life and functional mobility of patients with Multiple Sclerosis (MS) can significantly improve with exercise and a rehabilitation therapy adjusted to the needs of each patient. The assessment of gait and functional mobility of patients with MS is usually done based on clinical scales and tests, which have various limitations. This work presents the preliminary results of a clinical study carried out with patients with MS walking with a sensorized crutch tip. This tip allows to define new indicators that can be correlated with the clinical assessment scales and provide further objective and quantitative information to assess gait performance and level of impairment of patients with MS, and characterize their gait patterns. The results suggest that parameters such as the average cycle time and the average percentage of body weight might be useful to evaluate the gait performance and level of disability. Moreover, parameters related with the pitch angle of the crutch allow to determine crutch usage patterns and spot differences between patients with similar functional performance.This work was supported by the Government of the Basque Country (grant PRE-2018-2-210), by the University of the Basque Country (project GIU19/45), by the Ministerio de Ciencia e Innovacion (MCI) under grant number DPI2017-82694-R (AEI/FEDER, UE), by Fundacion Euskampus and Fundacion BB