Investigating sensory-motor interactions to shape rehabilitation

Over the last decades, robotic devices for neurorehabilitation have been developed with the aim of providing better and faster improvement of motor performance. These devices are being used to help patients repeat movements and (re)learn different dynamic tasks. Over the years, these devices have become bigger and more complex, so as to provide the end user with a more realistic and sophisticated stimuli while still allowing the experimenter to have control over the interaction forces that can potentially shape the motor behaviour. However, experimental results have shown no clear advantage of these complex devices over simpler versions. In this context, this thesis investigates sensory-motor processes of human interaction, which can help us understand the main issues for rehabilitation devices and how to overcome the limitations of simple devices to train particular motor behaviours. Conventional neurorehabilitation of motor function relies on haptic interaction between the patient and physiotherapist. However, how humans deal with human-human interactions is largely unknown, and has been little studied. In this regard, experiments of the first section of the thesis investigate the mechanisms of interaction during human-human collaborative tasks. It goes from identifying the different strategies that dyads can take to proposing methods to measure and understand redundancy and synchrony in haptic interactions. It also shows that one can shape the interaction between partners by modifying only the visual information provided to each agent. Learning a novel skill requires integration of different sensory modalities, in particular vision and proprioception. Hence, one can expect that learning will depend on the mechanical characteristics of the device. For instance, a device with limited degrees of freedom will reduce the amount of information about the environment, modify the dynamics of the task and prevent certain error-based corrections. To investigate this, the second section of the thesis examines whether the lack of proprioceptive feedback that is created due to mechanical constraints or haptic guidance can be substituted with visual information. Psychophysical experiments with healthy subjects and some preliminary experiments with stroke patients presented in this thesis support the idea that by incorporating task-relevant visual feedback into simple devices, one could deliver effective neurorehabilitation protocols. The contributions of the thesis are not limited to the role of visual feedback to shape motor behaviour, but also advance our understanding on the mechanisms of learning and human-human interaction

Violencia intrafamiliar y bienestar psicológico en adolescentes de una institución educativa de Lima Metropolitana, 2022

El presente estudio posee el objetivo general de determinar la relación entre violencia intrafamiliar y bienestar psicológico en adolescentes de una institución educativa de Lima Metropolitana, 2022. Utilizando como metodología de estudio tipo cuantitativo y diseño correlacional, trabajando con una muestra de 109 participantes de dicha institución. Como instrumentos a aplicar en la investigación se utilizaron, el Cuestionario de violencia familiar (CVIFA) de la autora Altamirano (2019), y la Escala de Bienestar Psicológico para Adolescentes (EBPA) de los autores González y Andrade (2015) que fue adaptado por Rojas (2020). Los resultados obtenidos indican que no hay correlación entre ambas variables rechazando la hipótesis de investigación. En conclusión, el presente estudio determinó que no hay relación entre la violencia intrafamiliar y el bienestar psicológico; por lo tanto, la presencia de violencia en el hogar no indica necesariamente alteración en el bienestar psicológico de los adolescentes, asumiendo que este último se construye en razón de otros factores necesarios a investigar en un futuro

Assessing walking ability using a robotic gait trainer: opportunities and limitations of assist-as-needed control in spinal cord injury

Background: Walking impairments are a common consequence of neurological disorders and are assessed with clinical scores that suffer from several limitations. Robot-assisted locomotor training is becoming an established clinical practice. Besides training, these devices could be used for assessing walking ability in a controlled environment. Here, we propose an adaptive assist-as-needed (AAN) control for a treadmill-based robotic exoskeleton, the Lokomat, that reduces the support of the device (body weight support and impedance of the robotic joints) based on the ability of the patient to follow a gait pattern displayed on screen. We hypothesize that the converged values of robotic support provide valid and reliable information about individuals' walking ability.Methods: Fifteen participants with spinal cord injury and twelve controls used the AAN software in the Lokomat twice within a week and were assessed using clinical scores (10MWT, TUG). We used a regression method to identify the robotic measure that could provide the most relevant information about walking ability and determined the test–retest reliability. We also checked whether this result could be extrapolated to non-ambulatory and to unimpaired subjects.Results: The AAN controller could be used in patients with different injury severity levels. A linear model based on one variable (robotic knee stiffness at terminal swing) could explain 74% of the variance in the 10MWT and 61% in the TUG in ambulatory patients and showed good relative reliability but poor absolute reliability. Adding the variable 'maximum hip flexor torque' to the model increased the explained variance above 85%. This did not extend to non-ambulatory nor to able-bodied individuals, where variables related to stance phase and to push-off phase seem more relevant.Conclusions: The novel AAN software for the Lokomat can be used to quantify the support required by a patient while performing robotic gait training. The adaptive software might enable more challenging training conditions tuned to the ability of the individuals. While the current implementation is not ready for assessment in clinical practice, we could demonstrate that this approach is safe, and it could be integrated as assist-as-needed training, rather than as assessment.Trial registration: ClinicalTrials.gov Identifier: NCT02425332

Investigating sensory-motor interactions to shape rehabilitation

Over the last decades, robotic devices for neurorehabilitation have been developed with the aim of providing better and faster improvement of motor performance. These devices are being used to help patients repeat movements and (re)learn different dynamic tasks. Over the years, these devices have become bigger and more complex, so as to provide the end user with a more realistic and sophisticated stimuli while still allowing the experimenter to have control over the interaction forces that can potentially shape the motor behaviour. However, experimental results have shown no clear advantage of these complex devices over simpler versions. In this context, this thesis investigates sensory-motor processes of human interaction, which can help us understand the main issues for rehabilitation devices and how to overcome the limitations of simple devices to train particular motor behaviours. Conventional neurorehabilitation of motor function relies on haptic interaction between the patient and physiotherapist. However, how humans deal with human-human interactions is largely unknown, and has been little studied. In this regard, experiments of the first section of the thesis investigate the mechanisms of interaction during human-human collaborative tasks. It goes from identifying the different strategies that dyads can take to proposing methods to measure and understand redundancy and synchrony in haptic interactions. It also shows that one can shape the interaction between partners by modifying only the visual information provided to each agent. Learning a novel skill requires integration of different sensory modalities, in particular vision and proprioception. Hence, one can expect that learning will depend on the mechanical characteristics of the device. For instance, a device with limited degrees of freedom will reduce the amount of information about the environment, modify the dynamics of the task and prevent certain error-based corrections. To investigate this, the second section of the thesis examines whether the lack of proprioceptive feedback that is created due to mechanical constraints or haptic guidance can be substituted with visual information. Psychophysical experiments with healthy subjects and some preliminary experiments with stroke patients presented in this thesis support the idea that by incorporating task-relevant visual feedback into simple devices, one could deliver effective neurorehabilitation protocols. The contributions of the thesis are not limited to the role of visual feedback to shape motor behaviour, but also advance our understanding on the mechanisms of learning and human-human interaction.EThOS - Electronic Theses Online ServiceGBUnited Kingdo

Estimating Movement Smoothness From Inertial Measurement Units

Inertial measurement units (IMUs) are increasingly used to estimate movement quality and quantity to the infer the nature of motor behavior. The current literature contains several attempts to estimate movement smoothness using data from IMUs, many of which assume that the translational and rotational kinematics measured by IMUs can be directly used with the smoothness measures spectral arc length (SPARC) and log dimensionless jerk (LDLJ-V). However, there has been no investigation of the validity of these approaches. In this paper, we systematically evaluate the use of these measures on the kinematics measured by IMUs. We show that: (a) SPARC and LDLJ-V are valid measures of smoothness only when used with velocity; (b) SPARC and LDLJ-V applied on translational velocity reconstructed from IMU is highly error prone due to drift caused by integration of reconstruction errors; (c) SPARC can be applied directly on rotational velocities measured by a gyroscope, but LDLJ-V can be error prone. For discrete translational movements, we propose a modified version of the LDLJ-V measure, which can be applied to acceleration data (LDLJ-A). We evaluate the performance of these measures using simulated and experimental data. We demonstrate that the accuracy of LDLJ-A depends on the time profile of IMU orientation reconstruction error. Finally, we provide recommendations for how to appropriately apply these measures in practice under different scenarios, and highlight various factors to be aware of when performing smoothness analysis using IMU data.ISSN:2296-418

Technology-aided assessments of sensorimotor function: current use, barriers and future directions in the view of different stakeholders

Background: There is growing interest in the use of technology in neurorehabilitation, from robotic to sensor-based devices. These technologies are believed to be excellent tools for quantitative assessment of sensorimotor ability, addressing the shortcomings of traditional clinical assessments. However, clinical adoption of technology-based assessments is very limited. To understand this apparent contradiction, we sought to gather the points-of-view of different stakeholders in the development and use of technology-aided sensorimotor assessments. Methods: A questionnaire regarding motivators, barriers, and the future of technology-aided assessments was prepared and disseminated online. To promote discussion, we present an initial analysis of the dataset; raw responses are provided to the community as Supplementary Material. Average responses within stakeholder groups were compared across groups. Additional questions about respondent's demographics and professional practice were used to obtain a view of the current landscape of sensorimotor assessments and interactions between different stakeholders. Results: One hundred forty respondents from 23 countries completed the survey. Respondents were a mix of Clinicians (27%), Research Engineers (34%), Basic Scientists (15%), Medical Industry professionals (16%), Patients (2%) and Others (6%). Most respondents were experienced in rehabilitation within their professions (67% with > 5 years of experience), and had exposure to technology-aided assessments (97% of respondents). In general, stakeholders agreed on reasons for performing assessments, level of details required, current bottlenecks, and future directions. However, there were disagreements between and within stakeholders in aspects such as frequency of assessments, and important factors hindering adoption of technology-aided assessments, e.g., Clinicians' top factor was cost, while Research Engineers indicated device-dependent factors and lack of standardization. Overall, lack of time, cost, lack of standardization and poor understanding/lack of interpretability were the major factors hindering the adoption of technology-aided assessments in clinical practice. Reimbursement and standardization of technology-aided assessments were rated as the top two activities to pursue in the coming years to promote the field of technology-aided sensorimotor assessments. Conclusions: There is an urgent need for standardization in technology-aided assessments. These efforts should be accompanied by quality cross-disciplinary activities, education and alignment of scientific language, to more effectively promote the clinical use of assessment technologies. Trial registration: NA; see Declarations section

A robust and sensitive metric for quantifying movement smoothness

The need for movement smoothness quantification to assess motor learning and recovery has resulted in various measures that look at different aspects of a movements profile. This paper first shows that most of the previously published smoothness measures lack validity, consistency, sensitivity, or robustness. It then introduces and evaluates the spectral arc-length metric that uses a movement speed profiles Fourier magnitude spectrum to quantify movement smoothness. This new metric is systematically tested and compared to other smoothness metrics, using experimental data from stroke and healthy subjects as well as simulated movement data. The results indicate that the spectral arc-length metric is a valid and consistent measure of movement smoothness, which is both sensitive to modifications in motor behavior and robust to measurement noise. We hope that the systematic analysis of this paper is a step toward the standardization of the quantitative assessment of movement smoothness

Analysis of pick-and-place, eating and drinking movements for the workspace definition of simple robotic devices

Current robotic devices for rehabilitation after stroke are often large and complex as they are conceived to train arbitrary movements in the 3D space. This paper analyzes the minimal requirements that the workspace of a robotic device should have in order to promote training of principal activities of daily living, considering the shoulder movement's limitations of subacute patients. Pick-and-place, drinking and eating movements of five healthy subjects were analyzed. In all these three tasks, approximately 82% of all trials deviate laterally less than 5% of the target distance and we recommend target distances of less than 40% of the arm length in order to minimize improper shoulder movements. The study can be applied for designing simpler, yet efficient robotic devices for rehabilitation of the upper limb or for constraining exercises on existing ones when dealing with stroke patients, especially for those prone to shoulder complications (e.g. subacute patients)

An Adaptive and Hybrid End-Point/Joint Impedance Controller for Lower Limb Exoskeletons

Assist-as-needed (AAN) algorithms for the control of lower extremity rehabilitation robots can promote active participation of patients during training while adapting to their individual performances and impairments. The implementation of such controllers requires the adaptation of a control parameter (often the robot impedance) based on a performance (or error) metric. The choice of how an adaptive impedance controller is formulated implies different challenges and possibilities for controlling the patient's leg movement. In this paper, we analyze the characteristics and limitations of controllers defined in two commonly used formulations: joint and end-point space, exploring especially the implementation of an AAN algorithm. We propose then, as a proof-of-concept, an AAN impedance controller that combines the strengths of working in both spaces: a hybrid joint/end-point impedance controller. This approach gives the possibility to adapt the end-point stiffness in magnitude and direction in order to provide a support that targets the kinematic deviations of the end-point with the appropriate force vector. This controller was implemented on a two-link rehabilitation robot for gait training-the Lokomat®Pro V5 (Hocoma AG, Switzerland) and tested on 5 able-bodied subjects and 1 subject with Spinal Cord Injury. Our experiments show that the hybrid controller is a feasible approach for exoskeleton devices and that it could exploit the benefits of the end-point controller in shaping a desired end-point stiffness and those of the joint controller to promote the correct angular changes in the trajectories of the joints. The adaptation algorithm is able to adapt the end-point stiffness based on the subject's performance in different gait phases, i.e., the robot can render a higher stiffness selectively in the direction and gait phases where the subjects perform with larger kinematic errors. The proposed approach can potentially be generalized to other robotic applications for rehabilitation or assistive purposes