Periodic Reporting for period 1 - TeleRehaB DSS (TeleRehabilitation of Balance clinical and economic Decision Support System)
Período documentado: 2022-12-01 hasta 2024-05-31
TeleRehaB DSS targets the promotion of AI adoption in everyday clinical practice for balance rehabilitation training.
It is the continuation of the HOLOBalance project, funded by the EU Horizon 2020 programme. The HOLOBalance platform delivers exercises demonstrated via a hologram of the physiotherapist and corrected in real time by the hologram prompts, based on performance monitoring via sensors, and aiming to improve balance function in older adults.
The TeleRehaB DSS project aims to explore the effectiveness (including cost) of running such programs in comparison with the current standard care for middle-age/older adults with balance disorders/falls due to MCI, vestibular disorders, stroke or long Covid. The clinical study that will be conducted aims to review treatment results, regarding risk of falls, balance and memory function, based on clinical tests and real-life sensor information, and collect information about the program’s safety and performance, while determining program usability.
To achieve the goals of this study, an AI-enabled decision support system (DSS) is being developed, to provide suggestive feedback for experts through the entire clinical rehabilitation pathway. The first component of AI models of TeleRehaB DSS assess prognostic factors for risk of falls, treatment effectiveness, outcomes and side effects at baseline level, using a high volume of retrospective data for initial training. The other AI pillar of TeleRehaB DSS introduces automated balance intervention planning and management functionality. The DSS will provide an optimal set of personalised rehabilitation activities, considering the best clinically effective treatment in conjunction with socioeconomic effectiveness, and eHealth literacy. The latter will be evaluated with a quick and easy tool with simple tasks, to assess patients' level of technological awareness, potentially affecting compliance and adherence to their programs. Finally, tαhe platform will allow remote patient monitoring with wearables and IoT sensing devices, providing for rehabilitation programs to be performed at home.
It is the continuation of the HOLOBalance project, funded by the EU Horizon 2020 programme. The HOLOBalance platform delivers exercises demonstrated via a hologram of the physiotherapist and corrected in real time by the hologram prompts, based on performance monitoring via sensors, and aiming to improve balance function in older adults.
The TeleRehaB DSS project aims to explore the effectiveness (including cost) of running such programs in comparison with the current standard care for middle-age/older adults with balance disorders/falls due to MCI, vestibular disorders, stroke or long Covid. The clinical study that will be conducted aims to review treatment results, regarding risk of falls, balance and memory function, based on clinical tests and real-life sensor information, and collect information about the program’s safety and performance, while determining program usability.
To achieve the goals of this study, an AI-enabled decision support system (DSS) is being developed, to provide suggestive feedback for experts through the entire clinical rehabilitation pathway. The first component of AI models of TeleRehaB DSS assess prognostic factors for risk of falls, treatment effectiveness, outcomes and side effects at baseline level, using a high volume of retrospective data for initial training. The other AI pillar of TeleRehaB DSS introduces automated balance intervention planning and management functionality. The DSS will provide an optimal set of personalised rehabilitation activities, considering the best clinically effective treatment in conjunction with socioeconomic effectiveness, and eHealth literacy. The latter will be evaluated with a quick and easy tool with simple tasks, to assess patients' level of technological awareness, potentially affecting compliance and adherence to their programs. Finally, tαhe platform will allow remote patient monitoring with wearables and IoT sensing devices, providing for rehabilitation programs to be performed at home.
In this period the project achieved major milestones in management, setting the foundations for a smooth and effective collaboration. An External Advisory Board was formed and a comprehensive Data Management Plan was developed, ensuring data privacy and security. A Gender Equality Plan was drafted, integrating sex/gender variables into research efforts. Project visibility was promoted through branding, online presence, and events. Significant progress was made in user-centric platform design and development for the TeleRehaB DSS platform. User requirements were gathered through stakeholder engagement, leading to design assessments for user interfaces and evaluation of devices like headsets and AR glasses. The platform's architecture was defined to support its complexity, while advancements were achieved in technical component development and integration, data repository setup, and security implementation. AI models for prognostic analytics, treatment planning, and activity scoring were developed, enhancing the platform's decision support capabilities.
Preparation for the clinical study progressed well, with ethics approvals obtained for most partners and a new clinical partner integrated. Recruitment and equipment procurement began, with pilot testing scheduled for the technical platform. Challenges like software operation issues were addressed through developer collaboration, ensuring clinical assessment readiness.
Overall, the project maintained steady progress, with collaborative efforts from technical and clinical partners supporting continued development and validation of AI models and tools, strengthening the TeleRehaB platform's functionality and impact.
Preparation for the clinical study progressed well, with ethics approvals obtained for most partners and a new clinical partner integrated. Recruitment and equipment procurement began, with pilot testing scheduled for the technical platform. Challenges like software operation issues were addressed through developer collaboration, ensuring clinical assessment readiness.
Overall, the project maintained steady progress, with collaborative efforts from technical and clinical partners supporting continued development and validation of AI models and tools, strengthening the TeleRehaB platform's functionality and impact.
In this initial phase of the project, where the selection of the (m)IoT devices/sensors is ongoing, and the implementation of the workflows and services is nearing completion, no measurable impact has been noted. Still, the effective use of the platform within the clinical study is expected to yield advanced data analytics and learning capabilities for large-scale analysis of the pilot study datasets. The first version of prognostic analytics based on retrospective data offered valuable insights on the identification of predictors for clinical endpoints like risk of falls and treatment effectiveness. These developments are expected to contribute to the research field of data analytics beyond the state of the art, integrating socioeconomic factors to support patient outcomes as well as efficient resource management.Moreover the ethical, legal, and regulatory aspects have been addressed to pave the ground for the forthcoming clinical study. The stakeholders' map has been finalized, identifying main groups such as patients, carers, healthcare professionals and administrators, researchers, data analysts, and technology providers, with group-specific communication means being elaborated. Stakeholder involvement is an ongoing task throughout the project, aiming to assess and project the results into medium-term outcomes and long-term impacts in terms of clinical outcomes and socioeconomic benefits compared to the standard of care. In the first reporting period, the primary groups targeted and involved in the system design and balance rehabilitation programs to be remotely delivered were the direct end-users: patients, carers, physiotherapists, and treating clinicians. In the forthcoming period, as the clinical trial study results are collected and assessed, communication to other stakeholders will intensify.