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Recent Advances in Sensor Technology and Robotics Integration

A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Sensors and Robotics".

Deadline for manuscript submissions: 28 February 2026 | Viewed by 1957

Special Issue Editors


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Guest Editor
Global Education & Training, University of Illinois at Urbana-Champaign, Champaign, IL 61820, USA
Interests: rehabilitation robotics; robotics and mechatronics; artificial intelligence; computer vision; transmissions

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Guest Editor
1. University Research and Innovation Center (EKIK), Obuda University, Budapest, Hungary
2. School of Computing, Queen’s University in Kingston, Kingston, ON K7L 3N6, UK
Interests: Medical Cyber-Physical Systems; surgical robotics; telerobotics; time-delayed systems; image-guided surgery; surgical data science; digital infection prevention & control; autonomous vehicle safety; agrifood robotics; Internet of Medical Things; technology transfer and innovation management
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

This Special Issue aims to explore the latest developments and innovations in sensor technology and its integration into robotics, rehabilitation robotics and assistive devices. The focus will be on how advanced sensors enhance the capabilities of rehabilitation robots and enable new applications. Topics of interest include, but are not limited to, the design and development of novel sensors for rehabilitation purposes, sensor fusion techniques for enhanced feedback and control, machine learning applications in sensor data processing, real-time sensing and the role of sensors in improving robotics. This Special Issue seeks to bring together researchers and practitioners from academia and industry to share their latest findings, foster collaboration and inspire future research directions in the fields of sensor technology and robotics.

Dr. Gani Sergazin
Dr. Tamás Haidegger
Guest Editors

Manuscript Submission Information

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Keywords

  • intelligent medical robotic systems and control
  • medical imaging and image-based robotic intervention
  • haptics and physical interaction in medical robotics
  • sensor-based rehabilitation robots
  • intuitive and advanced medical instrumentation
  • computer-integrated interventional systems

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Published Papers (2 papers)

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Research

31 pages, 5417 KiB  
Article
Design and Analysis of an Autonomous Active Ankle–Foot Prosthesis with 2-DoF
by Sayat Akhmejanov, Nursultan Zhetenbayev, Aidos Sultan, Algazy Zhauyt, Yerkebulan Nurgizat, Kassymbek Ozhikenov, Abu-Alim Ayazbay and Arman Uzbekbayev
Sensors 2025, 25(16), 4881; https://doi.org/10.3390/s25164881 - 8 Aug 2025
Viewed by 430
Abstract
This paper presents the development, modeling, and analysis of an autonomous active ankle prosthesis with two degrees of freedom (2-DoF), designed to reproduce movements in the sagittal (dorsiflexion/plantarflexion) and frontal (inversion/eversion) planes in order to enhance the stability and naturalness of the user’s [...] Read more.
This paper presents the development, modeling, and analysis of an autonomous active ankle prosthesis with two degrees of freedom (2-DoF), designed to reproduce movements in the sagittal (dorsiflexion/plantarflexion) and frontal (inversion/eversion) planes in order to enhance the stability and naturalness of the user’s gait. Unlike most commercial prostheses, which typically feature only one active degree of freedom, the proposed device combines a lightweight mechanical design, a screw drive with a stepper motor, and a microcontroller-based control system. The prototype was developed using CAD modeling in SolidWorks 2024, followed by dynamic modeling and finite element analysis (FEA). The simulation results confirmed the achievement of physiological angular ranges of ±20–22 deg. in both planes, with stable kinematic behavior and minimal vertical displacements. According to the FEA data, the maximum von Mises stress (1.49 × 108 N/m2) and deformation values remained within elastic limits under typical loading conditions, though cyclic fatigue and impact energy absorption were not experimentally validated and are planned for future work. The safety factor was estimated at ~3.3, indicating structural robustness. While sensor feedback and motor dynamics were idealized in the simulation, future work will address real-time uncertainties such as sensor noise and ground contact variability. The developed design enables precise, energy-efficient, and adaptive motion control, with an estimated average power consumption in the range of 7–9 W and an operational runtime exceeding 3 h per charge using a standard 18,650 cell pack. These results highlight the system’s potential for real-world locomotion on uneven surfaces. This research contributes to the advancement of affordable and functionally autonomous prostheses for individuals with transtibial amputation. Full article
(This article belongs to the Special Issue Recent Advances in Sensor Technology and Robotics Integration)
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24 pages, 13787 KiB  
Article
Design and Evaluation of a Soft Robotic Actuator with Non-Intrusive Vision-Based Bending Measurement
by Narges Ghobadi, Witold Kinsner, Tony Szturm and Nariman Sepehri
Sensors 2025, 25(13), 3858; https://doi.org/10.3390/s25133858 - 20 Jun 2025
Viewed by 720
Abstract
This paper presents the design and evaluation of a novel soft pneumatic actuator featuring two independent bending chambers, enabling independent joint actuation and localization for rehabilitation purposes. The actuator’s dual-chamber configuration provides flexibility for applications requiring customized bending profiles. To measure the bending [...] Read more.
This paper presents the design and evaluation of a novel soft pneumatic actuator featuring two independent bending chambers, enabling independent joint actuation and localization for rehabilitation purposes. The actuator’s dual-chamber configuration provides flexibility for applications requiring customized bending profiles. To measure the bending angle of the finger joints in real time, a camera-based system is employed, utilizing a deep learning detection model to localize the joints and estimate their bending angles. This approach provides a non-intrusive, sensor-free alternative to hardware-based measurement methods, reducing complexity and wiring typically associated with wearable devices. Experimental results demonstrate the effectiveness of the proposed actuator in achieving bending angles of 105 degrees for the metacarpophalangeal (MCP) joint and 95 degrees for the proximal interphalangeal (PIP) joint, as well as a gripping force of 9.3 N. The vision system also captures bending angles with a precision of 98%, indicating potential applications in fields such as rehabilitation and human–robot interaction. Full article
(This article belongs to the Special Issue Recent Advances in Sensor Technology and Robotics Integration)
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