Haptic Sensing, Estimation, and Control for Rehabilitation and Assistive Applications
A Special Issue of Sensors (ISSN 1424-8220) belonging to the section "Biomedical Sensors".
Deadline for manuscript submissions: 31 May 2027 | Viewed by 44
Editor
Interests: robotics; human–machine collaboration
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
Advances in rehabilitation robotics and assistive technologies are creating new opportunities to restore mobility, improve independence, and support people with motor impairments. At the center of many of these systems is haptic sensing—the measurement of force, pressure, touch, vibration, contact, and physical interaction between humans, devices, and their environments. Unlike conventional motion sensing alone, haptic information can reveal how a user interacts with a rehabilitation robot, whether assistance is excessive or insufficient, how firmly an object is grasped, or how contact conditions change during movement. The growing use of wearable devices, soft robotics, prostheses, exoskeletons, tele rehabilitation platforms, and human–robot collaborative systems has increased the need for reliable haptic perception and responsive control. Flexible tactile sensors, electronic skin, force–torque sensors, electromyography, inertial sensors, and multimodal sensing now provide rich streams of interaction data. At the same time, deep neural networks, transformers, self-supervised learning, physics-informed learning, and sensor-fusion methods are enabling more accurate estimation of user intention, limb impedance, contact state, fatigue, and motor performance. Translating these estimates into safe and meaningful assistance, however, remains challenging because of sensor uncertainty, human variability, communication delay, limited clinical data, and the need for real-time operation.
This Special Issue aims to present and disseminate the most recent advances related to haptic sensing, estimation, and control for rehabilitation and assistive applications. We consider contributions addressing novel sensing technologies, multimodal estimation, intelligent control, bilateral teleoperation, and human-centered evaluation. Particular interest is given to studies that connect sensing quality with estimation accuracy, closed-loop performance, user safety, clinical relevance, and practical implementation.
Topics of interest for publication include, but are not limited to, the following:
- Haptic, tactile, force, pressure, and proximity sensing;
- Flexible sensors, electronic skin, soft sensors, and wearable sensing systems;
- Multimodal sensor fusion involving tactile, visual, inertial, and physiological signals;
- Human intention, contact-state, force, impedance, and fatigue estimation;
- Deep neural networks, transformers, graph neural networks, and self-supervised learning for haptic data;
- Physics-informed and hybrid model-based/data-driven estimation;
- Impedance, admittance, and variable-impedance control;
- Assist-as-needed, shared, adaptive, robust, and learning-based control;
- Bilateral teleoperation, force reflection, and tele-rehabilitation;
- Passivity-based control and compensation for delay, packet loss, and uncertainty;
- Rehabilitation robots, prostheses, orthoses, exoskeletons, and assistive manipulators;
- Clinical studies, user evaluations, benchmark datasets, calibration, and real-time implementation.
Dr. Madan Mohan Rayguru
Guest Editor
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Keywords
- haptic sensing
- tactile sensing
- rehabilitation robotics
- assistive technologies
- human–robot interaction
- force and impedance estimation
- multimodal sensor fusion
- bilateral teleoperation
- wearable sensors
- prosthetics and exoskeletons
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