Approach &
Clinical Study


Our ambition is to build upon the successfully completing HOLOBALANCE project and technological platform that supports remotely monitored, home performed balance rehabilitation in order to provide an optimised and semiautomated balance telerehabilitation, to improve balance and reduce the prevalence and impact of falls in older people with additional neurological comorbidity (stroke, cognitive, musculoskeletal, other) to balance impairment, who are in higher need or multifactorial intervention.

This will be achieved through a telerehabilitation diagnostic and management decision support system for patients and clinicians, that will be co-created with all stakeholders (patients, clinicians, regulatory and commissioning bodies) harnessing knowledge and tools developed and validated and the experimentally proven machine learning approach of the HOLOBALANCE project.

The proposed TeleRehaB DSS will include:

  • An adaptable and expandable web-based and cloud facilitated platform and mobile phone apps, coupled with selected sensors, that will link therapist to patient to provide optimised cost-effective balance intervention.

  • An AI model that will be constructed on the basis of systematic guidelines and literature reviews, existing clinical partner data, multimorbidity data from biobank/twin studies repositories and synthetic data. This model will consider multifactorial falls/balance disorders data and related socioeconomic costs and will automatically provide patient-specific, cost-effective interventions.
  • A further AI model for exercise progression and patient motivation that will capitalise on the models already developed within HOLOBALANCE and that will be expanded to include additional disease and patient specific factors.

  • Disease specific toolboxes according to the balance model that informs patients/carers and clinicians about the intervention, information/links on disease specific assessment and outcome measures used in the intervention, related disease and intervention guidelines and meta-analyses, instructional videos, which will be reviewed and updated annually.

Clinical Study

The TeleRehaB project will utilize the cloud-based diagnostic DM-DSS platform which incorporates different apps for users that run on mobile devices.

This system will incorporate real time monitoring via sensors to be analysed via cloud-based AI/ML that together with the medical and other patient data and consideration of health costs will generate diagnostic decision rules and personalised interventions to be made available on the clinician’s cloud-based platform and delivered to the patient by their mobile apps.

The clinical study is composed by two types of intervention:

Active intervention: HOLOBALANCE balance rehabilitation programme

The HOLOBALANCE intervention is based upon established, evidence-based multi-sensory rehabilitation (MSR) protocols that have been shown to improve balance control in healthy older adults with exercises which challenge the balance system that patients need to perform regularly over a period of time. These interventions have been widely used and are safe, and evidence-based in patients with vestibular dysfunction in that they significantly improve balance and gait.

Screenshots of:
A. Physiotherapist avatar B & C. v Representative gameplay from the HOLOBALANCE system

The HOLOBALANCE intervention includes both standing and walking exercises, and cognitive exercises that were prescribed, according to the physiotherapist’s clinical judgement, together with physical activity information and targets decided on an individual’s needs and preferences. The exercises are presented to participants by the hologram based virtual physiotherapist with exercises participants required to wear a series of body worn sensors while performing the exercises and progressed over time depending upon the participant’s task performance determined by the treating balance physiotherapist

In the TeleRehaB DSS the platform will decide which patient will benefit most by performing all components of the HOLOBALANCE intervention consisting of TeleRehaB DSS delivered/progressed balance exercises with/without:

  • the AR avatar and feedback
  • AR gamified intervention
  • sensor monitored exercise performance
  • cognitive training

Control intervention

The comparator will be based on:

  • OTAGO Home Exercise Programme for those patients who report falls/are at risk of fall. The OTAGO is a progressive strength and balance training programme provided by a workbook with written instructions and pictures for each exercise.
  • Booklet based vestibular rehabilitation for those people with chronic dizziness/imbalance without falls/risk of falls that is a validated and widely used intervention for vestibular disorders.

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