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Advances in Biomedical Sensing Technologies for Assistive Robotics
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Advances in Biomedical Sensing Technologies for Assistive Robotics

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

Deadline for manuscript submissions: 30 October 2026 | Viewed by 1937

Editor

Dr. Liang He

E-Mail Website
Guest Editor
Department of Engineering Science, University of Oxford, Oxford OX1 3PJ, UK
Interests: soft robotics; wearable and assistive robotics; haptics; AI–robotics–human interaction; sports medicine

Special Issue Information

Dear Colleagues,

Assistive robotics is rapidly transforming biomedical engineering by enhancing diagnosis, rehabilitation, mobility, physical performance, and quality of life for individuals with disabilities, age-related impairments, and sports-related injuries. Advances in sensor technologies, artificial intelligence (AI), soft robotics, wearable systems, and human–machine interfaces have enabled the development of intelligent, adaptive, and user-centered robotic solutions for clinical and healthcare-related applications. This Special Issue, "Advances in Biomedical Sensing Technologies for Assistive Robotics", highlights cutting-edge research on advanced sensor design, multimodal sensing integration, machine learning for intelligent perception and intention recognition, and data-driven methodologies for safer, more efficient, and personalized assistive and performance-enhancing robotic systems.

Topics of interest include biosignal acquisition and processing (e.g., EMG and EEG), multimodal sensor fusion, human and machine haptics, and wearable systems in the context of assistive robotics (exoskeletons, prosthetics, rehabilitation robots, robotic extended-reality systems). Emphasis is placed on real-world deployment and the human-in-the-loop design of sensors in assistive robotics to improve usability, clinical outcomes, and athletic performance.

By integrating advances in sensing technologies, assistive robotics, and sports medicine, this Special Issue promotes solutions that bridge engineering and clinical practice, fostering independent living, functional recovery, injury prevention, and enhanced human performance.

Dr. Liang He
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 250 words) can be sent to the Editorial Office for assessment.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-anonymized peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Sensors is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • assistive robotics
  • soft robotics
  • wearable sensors
  • sports medicine
  • rehabilitation robotics
  • exoskeletons and prosthetics
  • human–robot interaction
  • biosignal processing (EMG/EEG)
  • sensor fusion
  • injury prevention and performance monitoring
  • artificial intelligence in healthcare
 

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Published Papers (3 papers)

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Research

23 pages, 8642 KB  
Article
Study on the Influence of Rotation Axis Misalignment of the Exoskeleton Knee Joint on Human Knee Joint Torque
by Changlong Jiang, Xiaorong Guan, Zheng Wang, Dingzhe Li and Long He
Sensors 2026, 26(16), 5119; https://doi.org/10.3390/s26165119 - 12 Aug 2026
Viewed by 367
Abstract
Misalignment between the rotation axis of a lower-limb exoskeleton knee joint and the human knee joint in the sagittal plane introduces additional human-exoskeleton interaction forces, affecting gait and assistance efficiency. This study proposes an equivalent stiffness-damping scheme that simultaneously accounts for the serial [...] Read more.
Misalignment between the rotation axis of a lower-limb exoskeleton knee joint and the human knee joint in the sagittal plane introduces additional human-exoskeleton interaction forces, affecting gait and assistance efficiency. This study proposes an equivalent stiffness-damping scheme that simultaneously accounts for the serial characteristics of both the exoskeleton’s strapping and human soft tissues, and establishes a human-exoskeleton coupling model based on OpenSim that allows for precise adjustment of the misalignment magnitude along the sagittal coordinate system. Simulation results indicate that the effects of misalignment exhibit significant directional dependence: at a misalignment of 0.05 m, the peak increase in extension torque in the positive y-axis direction reached 38.9%, while the peak increase in flexion torque in the negative x-axis direction reached 211.2%. The trends in human-exoskeleton interaction torque and electromyographic signals measured experimentally were consistent with the simulation results. Considering that, at a misalignment of 0.02 m, the maximum difference in torque in the negative x-axis direction was 54.65% and the assist efficiency in the positive x-axis direction dropped to −5.13%, it is recommended that the misalignment of the exoskeleton knee joint be controlled within 0.02 m. This provides quantitative evidence for the structural design and wear calibration of the exoskeleton. Full article
(This article belongs to the Special Issue Advances in Biomedical Sensing Technologies for Assistive Robotics)
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22 pages, 4992 KB  
Article
Older Adult Movement Assessment Through Rehabilitation Software for Upper Limb Exoskeleton
by Angel Camacho, Daniel Celis-Ruiz, Hellen Rivero-Pineda, Mariana Ballesteros and David Cruz-Ortiz
Sensors 2026, 26(12), 3658; https://doi.org/10.3390/s26123658 - 8 Jun 2026
Viewed by 503
Abstract
This work presents a pilot study to analyze the effect of aging on motor performance of young adults (YAs) and older adults (OAs) through wrist movement assessment, using an upper limb rehabilitation robot (ULRR) in passive mode coupled to a maze-solving task serious [...] Read more.
This work presents a pilot study to analyze the effect of aging on motor performance of young adults (YAs) and older adults (OAs) through wrist movement assessment, using an upper limb rehabilitation robot (ULRR) in passive mode coupled to a maze-solving task serious video game. The proposed approach considers the use of kinematic metrics, such as ROM, path accuracy, and movement smoothness, as quantitative biomarkers that evidence differences between YAs and OAs. An experimental protocol was conducted with 20 participants: 10 OAs and 10 YAs. Standardized wrist movements corresponding to flexion (F), extension (E), radial deviation (R), and ulnar deviation (U) were assessed at each level of the maze. The kinematic analysis was based on metrics for range of motion (ROM), path accuracy, smoothness, and root-mean-square error (RMSE) in trajectory tracking. The results revealed clear differences between the groups: the YAs achieved a greater ROM and made fewer errors on mean (2.167 errors for YAs compared to 6.000 errors for OAs), and showed a lower RMSE, while the OAs showed greater smoothness in their movements, because the YAs exhibit greater variability and disturbances in movement when correcting and controlling their movements to achieve good performance, reflecting more precise motor control and a greater capacity for error correction during movements with trajectory constraints. Full article
(This article belongs to the Special Issue Advances in Biomedical Sensing Technologies for Assistive Robotics)
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10 pages, 4655 KB  
Article
Haptic Feedback Reduces Telesurgery Operators’ Reaction Times Compared to Conventional Stimulation: Results of a First-in-Human Study
by Vaidas Labunskas, Vilius Dambrauskas, Augustė Melaikaitė, Vilhelmas Konstantinas Landsbergis, Radvilė Kadytė, Augustinas Baušys and Tomas Baltrūnas
Sensors 2026, 26(9), 2597; https://doi.org/10.3390/s26092597 - 23 Apr 2026
Viewed by 747
Abstract
This prospective, cross-sectional study evaluated reaction time (RT) variations across different sensory stimuli to investigate the efficacy of haptic feedback (HF) in reducing response latency for telesurgical applications. Three healthy-volunteer age cohorts (18–25, 35–45, and 55–65 years) were tested using visual, auditory, superficial, [...] Read more.
This prospective, cross-sectional study evaluated reaction time (RT) variations across different sensory stimuli to investigate the efficacy of haptic feedback (HF) in reducing response latency for telesurgical applications. Three healthy-volunteer age cohorts (18–25, 35–45, and 55–65 years) were tested using visual, auditory, superficial, and deep sensations, alongside a multimodal stimulus combining visual and superficial inputs to simulate HF. The findings revealed that combined visual and superficial stimulation yielded a mean RT of 227 ± 27 ms, outperforming visual-only stimulation by 40 ms (95% CI: 32–48 ms) and superficial-only stimulation by 26 ms (95% CI: 20–33 ms) (p = 0.001). While this performance boost was consistent across all age groups, the 55–65 age cohort demonstrated the most pronounced reduction in RT when the combined stimuli were used. These results suggest that integrating tactile sensations with visual cues significantly mitigates latency compared to unimodal inputs, underscoring the potential of haptic feedback to enhance operator performance and safety in latency-sensitive environments like remote surgery. Full article
(This article belongs to the Special Issue Advances in Biomedical Sensing Technologies for Assistive Robotics)
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