Periodic Reporting for period 1 - REPAIRS (Relearning Perception Action In Rehabilitation from a Systems perspective)
Berichtszeitraum: 2021-01-01 bis 2022-12-31
Rehabilitation of movement disorders such as stroke, aims to restore functional ability through re-learning perception-action couplings. However, current day rehabilitation leads to marginal improvements of daily functioning at best. To improve effectiveness of rehabilitation training we take a starting point that is different than the one taken usually when developing rehabilitation training. We start from the idea that functional behaviour emerges from non-linear interactions within and between the neural system, the movement system, the agent-environment system and the agent-agent system, a so-called systems perspective. We use this perspective to develop fundamental knowledge on learning perception-action couplings. To this end, we perform behavioural experiments and computer modelling. This knowledge is then translated to training applications for rehabilitation to improve rehabilitation effectiveness. These applications are developed using translational knowledge using insights from clinical, technological and philosophical domains.
Our fellows have participated in high-level training to prepare them to become the next generation of researchers in the systems perspective. They have participated in online training that familiarized them with the perspective used in REPAIRS and at which its objectives were explained. The fellows participated in two Network Training Events (NTEs). These events are set up to train the fellows in content and transferrable skills. The training events have a build-up that follows stages that can be found in perception-action learning. The overarching theme of the first NTE was ‘Learning the basics’ while the second focused on ‘Skill advancement’. The themes of the training events were reflected in the level of the content courses that were provided. The fellows also engaged in an Experiential Skill Learning workshop in which they train a novel perception-action skill at home and during the NTEs they discuss the experiences and strategies used during practice and how they change over their skill advancement. The goal of this workshop is to stimulate fellows to think about learning through reflections on their own experiences when learning a new skill. Such reflections should give the fellows thorough insight into how to build a training tool for rehabilitation of patients who will have to learn a new skill. The fellows also developed a broad range of transferrable skills related to topics such as Open Science, Gender issues in science, project planning, time management and scientific pitching.
The first main objective of REPAIRS entails developing fundamental knowledge on learning new perception-action couplings. Since it is generally assumed that variability in practice is helpful in learning a new perception-action skill, several of the fellows examine how variability in training conditions can contribute to learning a new skill. For instance, we are studying how a vibrotactile device can help people with a visual impairment pick up an object. We have established that variability in object size and object location helps blindfolded people to learn to use the signals from the vibrotactile device to guide their grasping actions. Moreover, we have found that participants have an intrinsic variability in their joint angle coordination pattern that differs among individuals. Intrinsic variability, and differences therein, will be exploited in upcoming studies.
In line with the first objective, several experimental setups have been developed to study coordination in joint actions. A ‘doubles pong’ task has been implemented to study how two individuals coordinate their actions to jointly achieve a goal. The focus will be on the information that guides the actions of the players and how communication between players contributes to the goal achievement. The first steps have been made in implementing an artificial agent in the doubles pong task so that it can be applied in rehabilitation. In a different type of setup developed by other fellows, two people had to move a surface to role a ball into a target. These projects focus on how the dynamics of the action system contribute to the dynamics of goal achievement.
The second main objective of REPAIRS entails developing knowledge on requirements for translating knowledge on perception-action learning to rehabilitation practice. Therefore, fellows prepare experiments with stroke patients, people with visual impairment and people with ASD. In addition, we exploit machine learning techniques to develop a model to predict patient-specific, evidence-based treatment pathways. We are currently implementing Generative Adversarial Networks to estimate individualized treatment effects. We are also developing a rehabilitation training module in which inertial sensor technology is used in exergames. Finally, we focus on normative practices and their coordination in interdisciplinary projects to find ways of improving interdisciplinary coordination. Revealing tension between practices in different disciplines (scientific, clinic, industry), we formulate requirements for translating scientific results in rehabilitation practice.
To widely share the developed knowledge, we developed toolboxes on theories, methodologies and analyses that are open for public use and can be found on our website. For instance, we give background on the Uncontrolled Manifold Method, present a tutorial on how to explain dynamic touch from an Ecological Psychology perspective, and we give a perspective on knowledge translation and coordination of practices when people of different disciplines work together. In addition, the fellows were active in communicating their work through presentations at local, national and international scientific meetings. We have active social media accounts where instant updates are given, and the team is presented.
The first main objective of REPAIRS entails developing fundamental knowledge on learning new perception-action couplings. Since it is generally assumed that variability in practice is helpful in learning a new perception-action skill, several of the fellows examine how variability in training conditions can contribute to learning a new skill. For instance, we are studying how a vibrotactile device can help people with a visual impairment pick up an object. We have established that variability in object size and object location helps blindfolded people to learn to use the signals from the vibrotactile device to guide their grasping actions. Moreover, we have found that participants have an intrinsic variability in their joint angle coordination pattern that differs among individuals. Intrinsic variability, and differences therein, will be exploited in upcoming studies.
In line with the first objective, several experimental setups have been developed to study coordination in joint actions. A ‘doubles pong’ task has been implemented to study how two individuals coordinate their actions to jointly achieve a goal. The focus will be on the information that guides the actions of the players and how communication between players contributes to the goal achievement. The first steps have been made in implementing an artificial agent in the doubles pong task so that it can be applied in rehabilitation. In a different type of setup developed by other fellows, two people had to move a surface to role a ball into a target. These projects focus on how the dynamics of the action system contribute to the dynamics of goal achievement.
The second main objective of REPAIRS entails developing knowledge on requirements for translating knowledge on perception-action learning to rehabilitation practice. Therefore, fellows prepare experiments with stroke patients, people with visual impairment and people with ASD. In addition, we exploit machine learning techniques to develop a model to predict patient-specific, evidence-based treatment pathways. We are currently implementing Generative Adversarial Networks to estimate individualized treatment effects. We are also developing a rehabilitation training module in which inertial sensor technology is used in exergames. Finally, we focus on normative practices and their coordination in interdisciplinary projects to find ways of improving interdisciplinary coordination. Revealing tension between practices in different disciplines (scientific, clinic, industry), we formulate requirements for translating scientific results in rehabilitation practice.
To widely share the developed knowledge, we developed toolboxes on theories, methodologies and analyses that are open for public use and can be found on our website. For instance, we give background on the Uncontrolled Manifold Method, present a tutorial on how to explain dynamic touch from an Ecological Psychology perspective, and we give a perspective on knowledge translation and coordination of practices when people of different disciplines work together. In addition, the fellows were active in communicating their work through presentations at local, national and international scientific meetings. We have active social media accounts where instant updates are given, and the team is presented.
The project is currently in the process of shifting from fundamental research to translational research, where the first steps are taken to implement the findings in rehabilitation practice.
Our findings on intrinsic variability in arm joint movements and variability of practice in training, and the calibration methods for sensor-based joint measurements, will be translated to computer games for rehabilitation of stroke patients that potentially improve their functional abilities.
The ideas of emergent joint actions can be applied in treatment of people with autistic spectrum disorder to improve their social interaction and communication skills.
The knowledge on variability in training in using vibrotactile devices can have impact on the rehabilitation of visually impaired people. To increase the potential impact, we are currently conducting an interview study with visually impaired individuals.
Currently, we use machine-learning to develop a patient-specific, evidence-based treatment pathway for patients with low back pain and knee arthroplasty, which might affect the patient trajectory in the clinic.
The guidelines of translating knowledge between different domains might have a lasting impact on how research into rehabilitation practice is set up and implemented.
Our findings on intrinsic variability in arm joint movements and variability of practice in training, and the calibration methods for sensor-based joint measurements, will be translated to computer games for rehabilitation of stroke patients that potentially improve their functional abilities.
The ideas of emergent joint actions can be applied in treatment of people with autistic spectrum disorder to improve their social interaction and communication skills.
The knowledge on variability in training in using vibrotactile devices can have impact on the rehabilitation of visually impaired people. To increase the potential impact, we are currently conducting an interview study with visually impaired individuals.
Currently, we use machine-learning to develop a patient-specific, evidence-based treatment pathway for patients with low back pain and knee arthroplasty, which might affect the patient trajectory in the clinic.
The guidelines of translating knowledge between different domains might have a lasting impact on how research into rehabilitation practice is set up and implemented.