Exploring Innovative Strategies to Enhance Eye-Hand Coordination and Cognitive Functions Through Drone Catching Exercise.
Trial Snapshot
- Phase
- Not Applicable
- Status
- Completed
- Enrollment
- 38
- Locations
- 1
- Primary Endpoint
- Executive Functions via Flanker-ERP Measurement
Study Overview
Brief Summary
Eye-hand coordination (EHC) is a critical cognitive-motor function that enables individuals to interact effectively with their environment through visually guided hand movements. It plays an essential role in daily activities such as reaching, grasping, and object manipulation. Previous studies have shown that targeted physical activities and sports can enhance EHC performance. However, aging is commonly associated with declines in EHC, executive function, and postural control, which can negatively affect independence in daily living. These age-related changes are also closely linked to cognitive decline and may contribute to the development of mild cognitive impairment (MCI), dementia, and Alzheimer's disease, thereby increasing the burden on families and healthcare systems.
To mitigate these effects, various cognitive-motor and technology-assisted training approaches have been proposed to improve EHC and cognitive function in older adults. While many existing EHC training systems are computerized and implemented using virtual reality (VR) or mixed reality (MR), accumulating evidence suggests that virtual environments may not fully replicate real-world eye-hand interactions. Limitations in depth perception, haptic feedback, and realism may alter visual fixation strategies, movement execution, and overall task performance, potentially reducing training effectiveness compared with real-world interactions.
Given these limitations, it remains unclear whether real-world EHC training provides greater benefits to executive functions and motor performance than virtual training. Therefore, this study aims to compare the acute effects of EHC exercise performed in a real-world environment and a mixed reality passthrough environment among older adults. The proposed EHC training task involves catching a real three-dimensional (3D) object guided by a physical mini drone, inspired by natural human behaviors such as swatting at flying insects, and its virtual counterpart involving a virtual 3D object and drone. The primary objective is to examine differences in executive functions, task performance, and postural stability between real and virtual EHC conditions. By identifying which training modality better supports cognitive-motor performance, this study seeks to inform the design of effective and engaging interventions for healthy aging and early prevention of cognitive decline.
Study Design
- Study Type
- Interventional
- Allocation
- Randomized
- Intervention Model
- Single Group
- Primary Purpose
- Other
- Masking
- None
Eligibility Criteria
- Ages
- 60 Years to — (Adult, Older Adult)
- Sex
- All
- Accepts Healthy Volunteers
- Yes
Inclusion Criteria
- •60 years and older (65 years and older preferred).
- •Able to perform regular exercise.
- •Normal vision or normal vision after correction.
Exclusion Criteria
- •Have a history of significant chronic diseases such as neurological (e.g., stroke, dementia, Parkinson's disease, poor vision, and hearing loss), cardiovascular, metabolic, pulmonary, or musculoskeletal diseases.
- •Have a history of significant motion sickness, active nausea, and vomiting, or epilepsy.
- •Fear of wearing a VR headset.
Arms & Interventions
Underwent the virtual system after the real system
Intervention: Virtual Object-Based Catching System (Other)
Underwent the real system after the virtual system
Intervention: Real Object-Based Catching System (Other)
Underwent the virtual system after the real system
Intervention: Real Object-Based Catching System (Other)
Underwent the real system after the virtual system
Intervention: Virtual Object-Based Catching System (Other)
Outcomes
Primary Outcomes
Executive Functions via Flanker-ERP Measurement
Time Frame: 2 hours
Each participant underwent Flanker-ERP assessment at three stages: at baseline (pre-intervention) and following both the physical and virtual object-based EHC training sessions.
Success Rate (SR)
Time Frame: 1-1.5 hours
SR was measured for each participant during object-catching trials across two EHC training modalities: the physical and the virtual 3D object-based drone-catching systems.
Reaction Time (RT)
Time Frame: 1-1.5 hours
RT was measured for each participant during object-catching trials across two EHC training modalities: the physical and the virtual 3D object-based drone-catching systems.
Movement Time (MT)
Time Frame: 1-1.5 hours
MT was measured for each participant during object-catching trials across two EHC training modalities: the physical and the virtual 3D object-based drone-catching systems.
Peak Hand Velocity (PHV)
Time Frame: 1-1.5 hours
PHV was measured for each participant during object-catching trials across two EHC training modalities: the physical and the virtual 3D object-based drone-catching systems.
Time-to-Peak Hand Velocity (TPHV)
Time Frame: 1-1.5 hours
TPHV was measured for each participant during object-catching trials across two EHC training modalities: the physical and the virtual 3D object-based drone-catching systems.
Center of Mass (CoM)
Time Frame: 1-1.5 hours
The CoM of every participant while performing EHC training tasks was investigated regarding two different EHC training modalities, including physical object-based and virtual object-based drone-catching systems.
Center of Pressure (CoP)
Time Frame: 1-1.5 hours
The CoP of every participant while performing EHC training tasks was investigated regarding two different EHC training modalities, including physical object-based and virtual object-based drone-catching systems.
Secondary Outcomes
- Subjective participant feedback on perceived task difficulty(10-15 minutes)
- Subjective participant feedback on system preference(10-15 minutes)
- Virtual Reality Sickness Questionnaire (VRSQ)(10-15 minutes)
Investigators
Fong Chin Su
University Chair Professor
National Cheng-Kung University Hospital
