SplitBody: Reducing Mental Workload while Multitasking via Muscle Stimulation

Title of the Paper

SplitBody: Reducing Mental Workload while Multitasking via Muscle Stimulation

Paper Information

• Field of Study: Human-Computer Interaction and Wearable Technology
• Keywords: Haptics, Electrical Muscle Stimulation (EMS), Agency, Mental Workload, Cognitive Load

Research Background and Problem

• Problems and Challenges: In multitasking scenarios, traditional Electrical Muscle Stimulation (EMS) primarily focuses on assisting users with their primary tasks, while its potential to aid background tasks that divert attention remains underexplored. Additionally, EMS may cause side effects such as distraction (e.g., tingling sensations or reduced sense of agency), which could diminish overall task performance.
• Significance: Multitasking environments are prevalent in daily life, but simultaneously performing physical tasks and high-cognitive-load tasks often leads to increased mental workload and reduced task completion rates. Effectively allocating physical resources could significantly enhance efficiency and reduce mental strain for users.
• Motivation and Related Work:
  • EMS demonstrates significant potential in diverse interaction design scenarios but is currently primarily used to assist users with their focused tasks.
  • The performance bottleneck in multitasking is associated with mental workload. Existing studies have explored the use of haptic feedback to alleviate mental workload but have not investigated automated physical actions to reduce task burdens.

Solution

• Proposed Method: The authors designed an interactive technique called "SplitBody," which utilizes Electrical Muscle Stimulation (EMS) to automate users' simple repetitive muscle tasks (e.g., stirring motions), allowing them to focus on more critical cognitive tasks.
• Innovations:
  • Applying EMS to tasks that users are not actively focusing on, rather than the traditional approach of assisting with tasks that are the center of attention.
  • Introducing a new design space that enables users to concentrate on complex foreground tasks while simple background tasks are executed automatically.
• Implementation Steps and Key Techniques:
  • The experimental design employed a dual-task model, consisting of a purely physical task requiring repetitive arm movements and a cognitive task based on short-term memory (N-back test).
  • The physical task was automated via EMS, while the cognitive task required manual operation by the user.
  • Multi-level data collection included task accuracy, reaction time, and NASA-TLX scales (to evaluate workload).

Research Outcomes

• Specific Results:
  1. Overall task performance improved by 78% with the SplitBody technique, compared to 44% under baseline conditions.
  2. Physical task performance increased by 2.5 times, cognitive task accuracy improved by 1.3 times, and errors and omissions were significantly reduced.
  3. Mental workload decreased by 26%, and physical workload decreased by 31%.
• Advantages:
  • Compared to baseline conditions, the technique optimized cognitive resource allocation in multitasking scenarios, resulting in reduced mental strain for users.
  • Although EMS caused slight distraction, it overall reduced the interference of background tasks on foreground tasks.
• Experimental or Evaluation Results:
  • Users reported feeling less distracted while focusing on cognitive tasks, as physical tasks were automated by EMS.
  • Key statistical results demonstrated systematic and significant improvements in both types of tasks.
• Limitations and Future Directions:
  • The current experiments were limited to simple repetitive actions and short-term memory tasks, leaving the performance of EMS in more complex background tasks unexplored.
  • Individual differences in user acceptance of EMS may exist, such as weaker natural feedback when muscles are involuntarily moved.
  • The effectiveness of EMS depends on the precision of movements, necessitating further research into technical refinements.

Future Application Scenarios

• Design Space Demonstration: The authors envisioned four potential application scenarios for the SplitBody technique:
  1. Stirring while writing a paper (automated stirring motion).
  2. Using the dominant hand for drawing while the non-dominant hand automatically fills in colors or generates shading.
  3. Assisting drummers in learning progressive rhythms by using EMS to support background rhythms for faster mastery.
  4. Supporting instrument players in switching between active and background tasks (e.g., alternating between playing the piano and drums).
• Technical Feasibility Explanation:
  • Each application scenario leverages the existing precision of EMS (e.g., drawing precision error ±4.07mm, circular motion error 17.8mm) to meet design requirements.
  • The technique is particularly suitable for tasks requiring user involvement, creativity enhancement, or learning, rather than fully automated background tasks.

Conclusion and Future Work

• Conclusion: The SplitBody technique significantly reduces mental workload in multitasking scenarios by delegating simple physical actions to EMS, freeing users from manual control. It also optimizes overall performance in both cognitive and physical tasks.
• Future Directions:
  • Exploring the performance of EMS in more complex action scenarios and tasks.
  • Integrating mechanical muscles (e.g., artificial muscles or exoskeletons) to expand the design space, balancing portability and precision.
  • Incorporating multi-user virtual reality operations or integrating with ultra-multi-limb control systems to create new interaction experiences.

This paper provides a new perspective on the application of human-computer interaction technology in physical and cognitive multitasking scenarios, proposing key techniques for reducing mental workload and laying the foundation for future research directions.