People with hand and wrist conditions, such as carpal tunnel syndrome or hand injuries, often experience pain and discomfort when using a computer mouse. This study will evaluate a new artificial intelligence (AI)-assisted computer input system ("AI-mouse") designed to reduce the amount of hand movement needed during computer tasks. Participants will complete short computer-based tasks using both a conventional mouse and the AI-assisted system while researchers measure task performance, muscle activity using surface electromyography (EMG), and participants' ratings of pain, physical strain, and usability. The study aims to determine whether the AI-assisted system can reduce physical effort and muscle load while maintaining effective computer interaction. Findings may help improve accessible computer technologies and support the development of ergonomic tools for people with hand and wrist impairments.
Study Type
INTERVENTIONAL
Allocation
NON_RANDOMIZED
Purpose
SUPPORTIVE_CARE
Masking
NONE
Enrollment
15
A non-invasive computer input system that uses artificial intelligence to predict the user's intended on-screen action. Instead of relying primarily on continuous cursor movement and mouse clicking, the system presents predicted actions that participants can preview, accept, or discard using minimal keyboard input. The intervention is designed to reduce repetitive hand movements during computer interaction while preserving user control. Participants complete standardized computer tasks using the system during a single study session lasting less than four minutes.
A standard computer mouse used for conventional point-and-click interaction. Participants complete the same standardized computer tasks as in the experimental condition, allowing direct comparison of task performance, upper-limb muscle activity measured by surface electromyography (EMG), and participant-reported pain, physical strain, and usability.
APDF90 surface electromyography (sEMG) amplitude
90th percentile amplitude probability distribution function (APDF90) of the processed sEMG envelope recorded from selected upper-limb muscles during standardized computer tasks.
Time frame: Baseline (during each intervention condition on Day 1)
Muscular rest time
Percentage of task duration during which the processed sEMG envelope remained below the predefined muscular-rest threshold of 2 µV.
Time frame: Baseline (during each intervention condition on Day 1)
Integrated squared dynamic acceleration
Cumulative dynamic movement workload measured by tri-axial accelerometry and expressed as integrated squared dynamic acceleration (mG²·s).
Time frame: Baseline (during each intervention condition on Day 1)
90th percentile dynamic acceleration
Peak dynamic movement intensity measured by tri-axial accelerometry and expressed as the 90th percentile of dynamic acceleration (mG).
Time frame: Baseline (during each intervention condition on Day 1)
Task completion time
Time required to complete the standardized computer task using the conventional mouse and the AI-assisted computer input system.
Time frame: Baseline (during each intervention condition on Day 1)
Error rate
Percentage of incorrect target selections during the standardized computer task
Time frame: Baseline (during each intervention condition on Day 1)
Self-reported pain
Participant-reported hand and wrist pain after completing each intervention condition, assessed using a numeric rating scale
Time frame: Immediately after each intervention condition on Day 1
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