Effects of Augmented Reality Functional Integrated Training (AR-FIT) on Balance and Mobility in Stroke

Overview

The present study aims to develop and validate an evidence-based functional balance task library for Augmented Reality-Functional Integrated Training (AR-FIT), incorporating standardized real-object integration through expert consensus and pilot usability testing. Furthermore, the study seeks to determine the effects of AR-FIT on balance and functional mobility in stroke survivors in comparison to conventional Augmented Reality \& task oriented training over an eight-week intervention period. In addition, it intends to evaluate participant motivation, engagement, and perceived task realism during AR-FIT using structured questionnaires and post-intervention interviews, thereby examining both clinical effectiveness and user-centered experience outcomes.

Detailed description

Stroke remains a leading cause of long-term disability, with its burden rising sharply in low- and middle-income countries such as Pakistan. Despite advances in acute care, many survivors continue to experience persistent balance and mobility impairments that limit independence. While augmented reality (AR) based rehabilitation has shown promise in improving motor recovery and engagement, current AR systems often emphasize generalized or gamified tasks, offering limited opportunities for practicing functionally relevant, real-world movements. Therefore, the current study introduces an Augmented Reality-Functional Interactive Training (AR-FIT), designed to evaluate the feasibility and effectiveness of combining AR-guided feedback with real-object manipulation for post-stroke balance training. The objectives are threefold: first, to determine the feasibility and usability of AR-FIT as a balance training platform; second, to assess its impact on postural control, balance, and functional mobility compared to conventional AR training; and third, to explore patient motivation and engagement associated with tangible, ecologically valid tasks. By enhancing realism, sensory engagement, and functional relevance, this approach is expected to bridge the existing gap between digital rehabilitation technologies and the real-world demands of stroke recovery.

Interventions

• Other Augmented Reality-Functional Integrated Training (AR-FIT) Group
  Each participant will receive a standardized intervention program consisting of 24 supervised training sessions delivered over 8 consecutive weeks (3 sessions per week, approximately 45 minutes per session). All sessions will follow a structured format including a 5-7 minute warm-up phase, a 30-35 minute task-specific training phase, and a 5-6 minute cool-down period. In Augmented Reality-Functional Integrated Training (AR-FIT) Group, participants will perform structured functional balance task
• Other Augmented Reality-Generic Balance Training (GBT) Group
  In the AR- based Generic AR Balance Training Group, participants will undergo augmented reality-based balance training without real-object integration. The intervention will include AR-guided weight shifting, virtual stepping, diagonal reaching, trunk control tasks, and tool-based stability exercises (e.g., virtual ball reaching, wobble-board simulations). Exercises will be selected from a structured pool of balance and mobility activities and will be progressed through virtual task difficulty,
• Other Conventional Balance Training (CBT) Group
  In the Conventional Training Group, participants will receive therapist-guided task-oriented balance training based on standard neurorehabilitation principles. Exercises will include sit-to-stand practice, stepping and step-up training, weight shifting, lunges, trunk rotation, reaching activities, and functional mobility drills using real objects without augmented reality support. Task selection and progression will be individualized according to the participant's baseline motor function and cli

Primary outcome measures

• Berg Balance Scale (BBS) [Time frame: Baseline-4 Weeks-8 Week-3 Months Follow Up]
• Timed Up & Go (TUG) [Time frame: Baseline-4 Weeks-8 Week-3 Months Follow Up]
• Balance Evaluation Systems Test (Mini-BESTest) [Time frame: Baseline-4 Weeks-8 Week-3 Months Follow Up]
• FUGL Meyer (Lower limb) [Time frame: Baseline-4 Weeks-8 Week-3 Months Follow Up]

Secondary outcome measures (2)

• User Engagement Questionnaire (UEQ) [Time frame: 8 Weeks]
• Stroke Impact Scale (SIS v3.0) [Time frame: Baseline-4 Weeks-8 Week-3 Months Follow Up]

Eligibility criteria

Inclusion criteria

• Adults aged 40-70 years with first-ever ischemic or hemorrhagic stroke (>3 months post-onset).
• Cognitive ability: MMSE > 24.
• No or mild spasticity in upper/lower limb MAS ≤ 2
• Functional Ambulation Category (FAC) ≥ 3.
• Berg Balance Scale (BBS) 20-40 (to avoid floor/ceiling effects).
• Ability to walk 10 meters independently
• Willingness to provide informed consent and participate regularly.

Exclusion criteria

• Severe musculoskeletal or neurological comorbidities (e.g., contractures, Parkinson's disease).
• Severe visual, neglect, or communication impairments.
• Uncontrolled systemic illness or unstable cardiovascular condition.
• Participation in another interventional trial within the last 3 months.

Criteria are shown verbatim from the registry (in English). Final eligibility is always assessed by the study center.

Healthy volunteers: No

Study design

Allocation

Randomized

Model

Parallel assignment

Masking

Single blind

Primary purpose

Treatment

Study locations

Pakistan · 1 center

• Railway General Hospital, Rawalpindi — Rawalpindi

Identifiers

NCT: NCT07487207 · REC/PhD/011107

Primary sources (government registries)

• ClinicalTrials.gov (US NIH)

View this study on ClinicalTrials.gov ↗