Periodic Reporting for period 1 - V-HAB (Optimizing Vision reHABilition with virtual-reality games in paediatric amblyopia)
Reporting period: 2021-03-01 to 2023-02-28
Paediatric amblyopia (lazy eye) is a common, developmental vision disorder in children, causing a vision loss in one eye. Typical treatment for paediatric amblyopia is based on forcing the use of the bad eye to obtain a clear retinal image in each eye. But several aspects of paediatric amblyopia, like the involvement of 3D vision and motor function, are still understudied and not integrated in the rehabilitation process. The EU-funded V-HAB project conducted a deep investigation into vision-related sciences with emphasis on the role of motor control as well as selective attention in paediatric amblyopia.
Whilst the main diagnosis for pediatric amblyopia was visual acuity (e.g. being able to see the letters in a Snellen chart), 3-dimensional vision may remain problematic, hampering people to drive cars or to play sports. With this project, we aimed to include this important vision skill in the treatment paradigm and to relate it with other functional skills (motor skills).
The objectives of the project were:
1) To develop a novel task to depict eye-hand coordination at different depths (in three dimensions), namely the ReGraD task, which involved motion analysis of the hand during the task execution. Data was collected to test its reliability over two time points.
2) To map the relation between vision, attention and motor disorders in children and young adults (6-35 years old) with paediatric amblyopia, using the ReGraD task.
3) To test the efficacy of a treatment involving novel games in a 3-dimensions virtual reality headset (in collaboration with the company Vivid Vision Inc, USA).
Whilst the main diagnosis for pediatric amblyopia was visual acuity (e.g. being able to see the letters in a Snellen chart), 3-dimensional vision may remain problematic, hampering people to drive cars or to play sports. With this project, we aimed to include this important vision skill in the treatment paradigm and to relate it with other functional skills (motor skills).
The objectives of the project were:
1) To develop a novel task to depict eye-hand coordination at different depths (in three dimensions), namely the ReGraD task, which involved motion analysis of the hand during the task execution. Data was collected to test its reliability over two time points.
2) To map the relation between vision, attention and motor disorders in children and young adults (6-35 years old) with paediatric amblyopia, using the ReGraD task.
3) To test the efficacy of a treatment involving novel games in a 3-dimensions virtual reality headset (in collaboration with the company Vivid Vision Inc, USA).
The V-HAB project completed the data collection of objectives 1 and 2. The data of these objectives could not be analysed as the project terminted earlier than planned. The data can be found here: https://doi.org/10.5281/zenodo.8363126 which was collected with the software made available here:https://doi.org/10.5281/zenodo.8413091
The ReGraD dataset provides kinematic data during hand-object interaction in monocular and binocular conditions at different depths and monocular/binocular conditions. It comprises two sub-datasets: ReGraD A (two measurements) can determine its test-retest reliability, whilst ReGraD B (one measurement) can characterize individuals with and without visual disorders. ReGraD includes 35 controls and 3 patients with amblyopia aged 6 to 35.
The ReGraD dataset may aid to (1) gain insights into hand-object interaction under various eye conditions and depths, (2) assess reliability and reproducibility and (3) examine the effects of groups (control vs. patients) and age, among others. The ReGraD dataset contains raw data that can also be used to develop algorithms for data segmentation and data interpolation in the kinematic field.
Objective 3 comprised a randomized clinical trial in collaboration with the University Hospitals Geneva (registered here). The original plan was to recruit 30 participants, whilst this became challenging as the recruitment started later due to the COVID-19 pandemic. We then recruited 16 participants who came for 5 visits every 2 months. About 60% of their data of this was collected within objective 3 of this project, and the protocol of the trial was defined and published in BMC Ophthalmology (https://doi.org/10.1186/s12886-023-02944-y).
The ReGraD dataset provides kinematic data during hand-object interaction in monocular and binocular conditions at different depths and monocular/binocular conditions. It comprises two sub-datasets: ReGraD A (two measurements) can determine its test-retest reliability, whilst ReGraD B (one measurement) can characterize individuals with and without visual disorders. ReGraD includes 35 controls and 3 patients with amblyopia aged 6 to 35.
The ReGraD dataset may aid to (1) gain insights into hand-object interaction under various eye conditions and depths, (2) assess reliability and reproducibility and (3) examine the effects of groups (control vs. patients) and age, among others. The ReGraD dataset contains raw data that can also be used to develop algorithms for data segmentation and data interpolation in the kinematic field.
Objective 3 comprised a randomized clinical trial in collaboration with the University Hospitals Geneva (registered here). The original plan was to recruit 30 participants, whilst this became challenging as the recruitment started later due to the COVID-19 pandemic. We then recruited 16 participants who came for 5 visits every 2 months. About 60% of their data of this was collected within objective 3 of this project, and the protocol of the trial was defined and published in BMC Ophthalmology (https://doi.org/10.1186/s12886-023-02944-y).
The V-HAB project advanced the state of the art with the development of a task to investigate motor control skills, especially eye-hand coordination, during the manipulation of objects at different depths, where 3-dimensional vision is required. Besides the development of this task, the software that we developed to collect the data as well as a dataset so that other researchers can profit from this project and re-use it as they see fit.