Assistive and Rehabilitation Technologies Proceedings of the International Workshop on Assistive & Rehabilitation Technology, December 14-16, 2016, Elche, Spain

—RoboHealth is a project that is focused on giving assistance to medical staff in order to improve the quality of treatment provided to patients in rehabilitation processes. The project covers two aspects during the rehabilitation process: assessment and therapy itself. In previous work [1], an automatic assessment system was presented for the evaluation of patient progress and effectiveness of the therapy, that is based on the Box and Blocks Test (BBT) of manual dexterity. In this article, an extension of the ﬁrst trials including more participants is presented. This further advocates the use of automated methods in physical rehabilitation assessment. Abstract —Robust ethical and research governance is vital to safeguard both the participant and the researcher in the development of novel technology. Designing new technology solutions with people living with disabilities can raise a host of ethical challenges and risks. The lessons learned from working within an ethical framework to develop brain computer interfaces and a multimodal perception system with upper limb exoskeleton and robotics are presented. The ethical challenges that emerged are considered within three domains: obtaining ethical approval; the technology; and the target end user. Abstract —User centered design (UCD) is used to ensure target end users are at the heart of the design and development of assistive technology and robotics. The present paper sets out a user centered methodological approach. The design cycle focuses on three components to enhance the communication between the technical team and stakeholders. User specification is focused on identifying what users want from the system. Data was collected from people living with neurological conditions, therapists and caregivers and analyzed using PACT (People, Activities, Context and Technology). The system design required decisions on the component specifications of the system and functionality mapped to the user’s requirements. Finally, iterative cycles of testing with end users is proposed. An evaluation matrix focusing on effectiveness, efficiency and user satisfaction will be applied. UCD is essential for the appropriate development of emerging technology and this approach can support future user centered development of systems. Abstract —The Activities of Daily Living (ADL) have been deﬁned as those purposeful activities in the areas of self-care, productivity, and leisure, which are part of human’s daily life. This research studies the accuracy of three different prediction models: Support Vector Machines (SVM); Artiﬁcial Neural Networks (ANN); and Decision Trees (DT). This research aims to study this supervised learning models through data that can be acquired from the fusion of the smart environment, user location and wearable sensors. The success rate obtained is over than 90% with the DT model. It can be concluded that a high success rate can be obtained with this model, however it could be studied the routine adaptation of this model performing an adapted decision tree with new labeled data coming from each user.  Abstract —Sophisticated technologies or methods are required to control an exoskeleton, because of the interaction with human users. However, for any control method, the basic task is to capture the user’s motion intention. Electromyographic (EMG) signals carry information about the human motion intention encoded in the muscle activity of the user even prior the movement. Here, we developed an advanced machine learning (ML) algorithm for detecting the intention of a reaching movement as fast as possible, and discuss its applicability to the control of an upper-limb exoskeleton used as an assistive device for people with severe arm disabilities. [4]. The detector evaluated the outputs of multiple GMM algorithms working in parallel on 4 features: MMAV, SSI, VAR, and LOG [5]. We compared the performance of 3 detector types based on: (i) single EMG signals, (ii) multiple EMG signals, with a majority voting procedure for the final decision, (iii) a compound EMG signal,  Abstract —This paper presents a shared human-machine control system of an upper-limb robotic exoskeleton for people with highly reduced arm mobility, to perform activities of daily living. The control system is based on a finite-state machine that splits the main task in elementary actions that can be accomplished separately by the device. A finite-state machine for a drinking task has been implemented and validated on three healthy subjects on a preliminary integrated system. The drinking task was triggered by the user via a gaze tracking interface; then the arm and hand exoskeletons performed the task autonomously. Abstract —This paper present two calibration methods, an analytic process and a stochastic RANSAC procedure, with which to determinate the relation between the reference system of an assistive robot and a 3D tracking camera system. The objective of this study, is to test if an iterative method like RANSAC is able to help solve issues that arise in analytical calibration methods because of the uncertainty in the colloca- tion of a tracking element exactly on a known place of the robot with the purpose of relate the robot kinematics with the camera information. The result is intended to be used in the control of a assistance robot from the camera system information. Abstract —The main goal of NAOTherapist is to provide a social robot with enough autonomy to carry out a non-contact upper-limb rehabilitation therapy for patients with physical impairments, such as cerebral palsy and obstetric brachial plexus palsy. Our robotic system is focused on pediatric patients aiming to increase their motivation and engagement with the treatment. The robot shows a set of prescribed exercises and the patient has to repeat them correctly by imitation. The rehabilitation tool supervises and gives a set of clues and correction mechanisms to help them during the training. The system has been initially evaluated with a large number of healthy children, a ﬁrst experience of 3 pediatric patients and a long-term evaluation with 8 patients during 4 months.  Abstract —This work describes two mechanical design solutions adopted to develop a novel robotic tele-rehabilitation system for in-home use. To make home-use a reality, it is of paramount importance for the system to be low-cost, safe, reliable and simple to operate. These demanding specifications often end up in low performance systems that seriously affect the rehabilitation outcomes. The proposed solutions are related to mechanical transmission and force sensing with the aim of minimizing the trade-off between performance and cost. The research is part of the ongoing HOMEREHAB European project.  Abstract — This paper present two designed studies for analyze and characterize the psyco-emotional states by psycho- physiological measurements in a group of healthy volunteers and the first analysis of the usefulness of this information. The aim is the characterization of the psychophysiological state during the performance of active therapy with the E2REBOT robotic platform, which we have developed for upper limb rehabilitation. Psycho-physiological measurements by means of the Self-Assessment Manikim (SAM) test and biomedical signals (heart rate variability, skin conductance, and skin temperature) were obtained in this first trial with E2REBOT. The protocol design and the results of the experiments are presented. These results suggest that is possible to quantitatively characterize the psycho-physiological state of an individual who interacts with the E2REBOT system. Abstract —Brain/neural-computer interaction (BNCI) systems translating brain/neural activity into control commands of external devices, such as exoskeletons or robots, are promising tools to restore lost functions, e.g. in paralysis. A critical challenge in long-term use of these systems relates to adapting the difficulty of BNCI control to avoid decline of reliability due to mental fatigue, particularly in patient populations with lesions of the central nervous system. Therefore, it would be important to establish physiological measures indicating the level of task difficulty before decline of BNCI control performance. Here we tested whether heart rate variability (HRV) can be used to assess task difficulty during EEG/EOG-based BNCI system control. A first study indicated reliable detection of task difficulty across three different levels of BNCI control difficulty based on HRV, while BNCI control performance remained stable. These findings pave the way for establishing a novel BNCI calibration approach that continuously adapts BNCI control difficulty avoiding early mental fatigue.  Abstract — This extended abstract studies which is the optimum amount of sizes that a hand exoskeleton needs in order to be useful to as many adult subjects as possible. For this purpose, U.S. Army anthropometric data has been used in combination with a musculoskeletal simulation in order to check the effect of the deviations of the real hand measures with respect to the design ones. Abstract —This paper presents the development of a software module to estimate the location and pose estimation of 3D texture less objects. The presented algorithms have some interesting properties for their application in real live environments: real time, simultaneous object detection and robust detection under varying lighting conditions and heavy cluttered scenes. This software module is one of the pieces of AIDE system.