Influence of Robotic Therapy on Severe Stroke Patients.

Robotic rehabilitation has emerged as a promising approach to enhance motor recovery after stroke, but there is limited knowledge about its efficacy in individuals who have experienced severe stroke. The study presented in this paper aims to analyze the effect of robotic therapy on the recovery of patients with severe stroke when combined with conventional rehabilitation therapies, and we want to observe whether there is a relationship between the clinical assessment provided by the therapist and the data recorded by the robotic device. Participants were divided into an experimental group and a control group, both receiving 15 sessions of conventional therapy in three consecutive weeks, but the experimental group underwent three out of five sessions per week with a robotic device. Both groups were evaluated using clinical scales, and in addition the experimental group was evaluated using an assessment game incorporated in the robotic device that provides session data such as the level of assistance needed by each user to complete the activity, or the score obtained in the game. These preliminary results showed that patients who received robot-assisted therapy had better motor function recovery compared to those who only received conventional therapy. In addition, it is also observed that the robot assistance needed by patients in the experimental group decreased as the sessions progressed, suggesting that robot-assisted therapy could be an effective tool for severe stroke patients.

Patients' physiological reactions to competitive rehabilitation therapies assisted by robotic devices.

BACKGROUND: The aging of the population and the progressive increase in life expectancy in developed countries is leading to a high incidence of cerebrovascular diseases. Several studies have demonstrated that robot-assisted rehabilitation therapies combined with serious games can improve rehabilitation outcomes. Social interaction in the form of multiplayer games has been highlighted as a potential element to increase patient's motivation and exercise intensity, which professionals have described as one of the determining factors in maximizing rehabilitation outcomes. Despite this, it has not been widely studied. Physiological measures have been proven as an objective tool to evaluate patients' experience in robot-assisted rehabilitation environments. However, they have not been used to evaluate patients' experience in multiplayer robot-assisted rehabilitation therapies. The main objective of this study is to analyze whether the interpersonal interaction inherent in a competitive game mode affects the patients' physiological responses in robot-assisted rehabilitation environments. METHODS: A total of 14 patients participated in this study. The results of a competitive game mode were compared with a single-player game mode with different difficulty levels. Exercise intensity and performance were measured through parameters extracted from the game and the information provided by the robotic rehabilitation platforms. The physiological response of patients in each game mode was measured by the heart rate (HR) and the galvanic skin response (GSR). Patients were asked to fill out the IMI and the overall experience questionnaire. RESULTS: The exercise intensity results show that high-difficulty single-player game mode is similar in terms of intensity level to a competitive game mode, based on velocity values, reaction time and questionnaire results. However, the results of the physiological responses of the patients measured by GSR and HR are lower in the case of the competitive mode compared to the high-difficulty single-player game mode, obtaining results similar to those obtained in the low-difficulty single-player game mode. CONCLUSIONS: Patients find the competitive game mode the most fun, which is also the mode they report experiencing the most effort and stress level. However, this subjective evaluation is not in line with the results of physiological responses. This study concludes that interpersonal interaction inherent to a competitive game mode influences patients' physiological responses. This could mean that social interaction is an important factor to consider when interpreting the results obtained from physiological measurements.

Differences in Physiological Reactions Due to a Competitive Rehabilitation Game Modality.

Interpersonal rehabilitation games, compared to single-player games, enhance motivation and intensity level. Usually, it is complicated to restrict the use of the system to pairs of impaired patients who have a similar skill level. Thus, such games must be dynamically adapted. Difficulty-adaptation algorithms are usually based only on performance parameters. In this way, the patient's condition cannot be considered when adapting the game. Introducing physiological reactions could help to improve decision-making. However, it is difficult to control how social interaction influences physiological reactions, making it difficult to interpret physiological responses. This article aimed to explore the changes in physiological responses due to the social interaction of a competitive game modality. This pilot study involved ten unimpaired participants (five pairs). We defined different therapy sessions: (i) a session without a competitor; (ii) two sessions with a virtual competitor with different difficulty levels; (iii) a competitive game. Results showed a difference in the physiological response in the competitive mode concerning single-player mode only due to the interpersonal game modality. In addition, feedback from participants suggested that it was necessary to keep a certain difficulty level to make the activity more challenging, and therefore be more engaging and rewarding.

User activity recognition system to improve the performance of environmental control interfaces: a pilot study with patients.

BACKGROUND: Assistive technologies aim to increase quality of life, reduce dependence on care giver and on the long term care system. Several studies have demonstrated the effectiveness in the use of assistive technology for environment control and communication systems. The progress of brain-computer interfaces (BCI) research together with exoskeleton enable a person with motor impairment to interact with new elements in the environment. This paper aims to evaluate the environment control interface (ECI) developed under the AIDE project conditions, a multimodal interface able to analyze and extract relevant information from the environments as well as from the identification of residual abilities, behaviors, and intentions of the user. METHODS: This study evaluated the ECI in a simulated scenario using a two screen layout: one with the ECI and the other with a simulated home environment, developed for this purpose. The sensorimotor rhythms and the horizontal oculoversion, acquired through BCI2000, a multipurpose standard BCI platform, were used to online control the ECI after the user training and system calibration. Eight subjects with different neurological diseases and spinal cord injury participated in this study. The subjects performed simulated activities of daily living (ADLs), i.e. actions in the simulated environment as drink, switch on a lamp or raise the bed head, during ten minutes in two different modes, AIDE mode, using a prediction model, to recognize the user intention facilitating the scan, and Manual mode, without a prediction model. RESULTS: The results show that the mean task time spent in the AIDE mode was less than in the Manual, i.e the users were able to perform more tasks in the AIDE mode during the same time. The results showed a statistically significant differences with p<0.001. Regarding the steps, i.e the number of abstraction levels crossed in the ECI to perform an ADL, the users performed one step in the 90% of the tasks using the AIDE mode and three steps, at least, were necessary in the Manual mode. The user's intention prediction was performed through conditional random fields (CRF), with a global accuracy about 87%. CONCLUSIONS: The environment analysis and the identification of the user's behaviors can be used to predict the user intention opening a new paradigm in the design of the ECIs. Although the developed ECI was tested only in a simulated home environment, it can be easily adapted to a real environment increasing the user independence at home.

A Comparative Analysis of 2D and 3D Tasks for Virtual Reality Therapies Based on Robotic-Assisted Neurorehabilitation for Post-stroke Patients.

Post-stroke neurorehabilitation based on virtual therapies are performed completing repetitive exercises shown in visual electronic devices, whose content represents imaginary or daily life tasks. Currently, there are two ways of visualization of these task. 3D virtual environments are used to get a three dimensional space that represents the real world with a high level of detail, whose realism is determinated by the resolucion and fidelity of the objects of the task. Furthermore, 2D virtual environments are used to represent the tasks with a low degree of realism using techniques of bidimensional graphics. However, the type of visualization can influence the quality of perception of the task, affecting the patient's sensorimotor performance. The purpose of this paper was to evaluate if there were differences in patterns of kinematic movements when post-stroke patients performed a reach task viewing a virtual therapeutic game with two different type of visualization of virtual environment: 2D and 3D. Nine post-stroke patients have participated in the study receiving a virtual therapy assisted by PUPArm rehabilitation robot. Horizontal movements of the upper limb were performed to complete the aim of the tasks, which consist in reaching peripheral or perspective targets depending on the virtual environment shown. Various parameter types such as the maximum speed, reaction time, path length, or initial movement are analyzed from the data acquired objectively by the robotic device to evaluate the influence of the task visualization. At the end of the study, a usability survey was provided to each patient to analysis his/her satisfaction level. For all patients, the movement trajectories were enhanced when they completed the therapy. This fact suggests that patient's motor recovery was increased. Despite of the similarity in majority of the kinematic parameters, differences in reaction time and path length were higher using the 3D task. Regarding the success rates were very similar. In conclusion, the using of 2D environments in virtual therapy may be a more appropriate and comfortable way to perform tasks for upper limb rehabilitation of post-stroke patients, in terms of accuracy in order to effectuate optimal kinematic trajectories.

Estimation of Human Arm Joints Using Two Wireless Sensors in Robotic Rehabilitation Tasks.

This paper presents a novel kinematic reconstruction of the human arm chain with five degrees of freedom and the estimation of the shoulder location during rehabilitation therapy assisted by end-effector robotic devices. This algorithm is based on the pseudoinverse of the Jacobian through the acceleration of the upper arm, measured using an accelerometer, and the orientation of the shoulder, estimated with a magnetic angular rate and gravity (MARG) device. The results show a high accuracy in terms of arm joints and shoulder movement with respect to the real arm measured through an optoelectronic system. Furthermore, the range of motion (ROM) of 50 healthy subjects is studied from two different trials, one trying to avoid shoulder movements and the second one forcing them. Moreover, the shoulder movement in the second trial is also estimated accurately. Besides the fact that the posture of the patient can be corrected during the exercise, the therapist could use the presented algorithm as an objective assessment tool. In conclusion, the joints' estimation enables a better adjustment of the therapy, taking into account the needs of the patient, and consequently, the arm motion improves faster.

Supervised and dynamic neuro-fuzzy systems to classify physiological responses in robot-assisted neurorehabilitation.

This paper presents the application of an Adaptive Resonance Theory (ART) based on neural networks combined with Fuzzy Logic systems to classify physiological reactions of subjects performing robot-assisted rehabilitation therapies. First, the theoretical background of a neuro-fuzzy classifier called S-dFasArt is presented. Then, the methodology and experimental protocols to perform a robot-assisted neurorehabilitation task are described. Our results show that the combination of the dynamic nature of S-dFasArt classifier with a supervisory module are very robust and suggest that this methodology could be very useful to take into account emotional states in robot-assisted environments and help to enhance and better understand human-robot interactions.

Kinematic reconstruction of the human arm joints in robot-aided therapies with Hermes robot.

This paper presents a kinematic reconstruction algorithm for the variables of the human arm joints in robot-aided neurorehabilitation therapies. The presented algorithm uses the end effector of a rehabilitation robot and an accelerometer placed onto the upper arm to compute accurate values of the human arm chain. The goal of this algorithm is to obtain the joint values of the patient's arm to provide objective information to the therapist about the progress of the patient and to study the effectiveness of these kind of therapies.