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A Systematic Review on Haptic Feedback in Medical Robotics: Technologies, Applications, Clinical Translation, and an
1Control and Instrumentation Engineering Department, King Fahd University of Petroleum and Minerals, P.O. Box 1816, Dhahran 31261, Saudi Arabia.
Sensors (Basel, Switzerland)
|August 13, 2026
Summary
Haptic technology enhances human-robot interaction in healthcare but faces adoption challenges. Future progress relies on delivering clinically meaningful information via user-centered haptic systems, not just physical realism.
Area of Science:
- Robotics
- Human-Computer Interaction
- Neuroscience
- Clinical Medicine
Background:
- Haptic technology is crucial for safe human-robot interaction in healthcare.
- Despite advances, clinical adoption of haptic systems is limited.
- A gap exists between laboratory research and real-world medical deployment.
Purpose of the Study:
- To synthesize research on haptic feedback for healthcare applications.
- To adopt an information-centric perspective on haptic feedback.
- To provide a roadmap for advancing clinically deployable haptic technologies.
Main Methods:
- Systematic literature search (2000-2025) in IEEE Xplore, PubMed, Scopus.
- Focus on clinically relevant information conveyed through haptic feedback.
- Examination of tactile, kinesthetic, and hybrid feedback modalities; rendering, stability, and control principles; and applications.
Main Results:
- Haptic feedback can improve performance, reduce forces, and enhance situational awareness, but benefits are task-dependent.
- Clinical translation is hindered by sensing, miniaturization, stability, human factors, and regulatory issues.
- Current research trends include sensorless estimation, AI-assisted rendering, soft interfaces, and neurohaptics.
Conclusions:
- Future haptic technology progress depends on delivering clinically meaningful, user-centered information.
- A shift towards task-oriented and information-centric feedback is evident.
- Advancing haptic systems requires addressing limitations and focusing on interpretable, stable feedback.
