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Applied Sciences
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Emerging Technologies for Assistive Robotics
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Emerging Technologies for Assistive Robotics

A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Robotics and Automation".

Deadline for manuscript submissions: 20 April 2025 | Viewed by 1864

Special Issue Editors

Dr. Andrea Zanela

E-Mail Website
Guest Editor
ENEA Centro Ricerche Casaccia, Rome, Italy
Interests: robotics; artificial intelligence; neural networks
Prof. Dr. Alessandro Di Nuovo

E-Mail Website
Guest Editor
Department of Computing, Sheffield Hallam University, Sheffield S1 1WB, UK
Interests: cognitive robotics; developmental robotics; human–robot interactions; intelligent robots; machine and deep learning applications
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

The rapid advancement of robotics and artificial intelligence is transforming modern society, with assistive robotics emerging as a particularly promising field. As the global population ages and the demand for personalized healthcare grows, assistive robots are playing an increasingly vital role in improving the quality of life for individuals with disabilities, the elderly, and those in need of rehabilitation. Rising life expectancy worldwide is placing unprecedented pressure on healthcare systems, as age-related conditions such as mobility impairments, cognitive decline, and chronic illnesses become more prevalent. Traditional care models are struggling to meet this growing demand, making it crucial to explore innovative solutions like assistive robotics to ensure accessible and sustainable care. Assistive robots offer support that enables people to extend their active lives at home, enhancing their independence and wellbeing. These technologies range from wearable exoskeletons that aid mobility to intelligent prosthetics and socially interactive robots that provide companionship and cognitive support. Advances in machine learning, sensor technologies, and human–robot interactions are enabling these systems to better understand and adapt to the dynamic needs of users. This Special Issue highlights the latest research in novel robotic platforms, adaptive control algorithms, and the integration of smart sensors and artificial intelligence to enhance the autonomy and usability of assistive robots. It aims to inspire future research that will continue to push the boundaries of assistive robotics, creating impactful solutions that can significantly improve the lives of those who need them most.

Dr. Andrea Zanela
Prof. Dr. Alessandro Di Nuovo
Guest Editors

Manuscript Submission Information

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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-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Applied Sciences 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 2400 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
  • personalized healthcare
  • aging population
  • cognitive support
  • human–robot interactions
  • machine learning
  • adaptive control algorithms
  • smart sensors
  • multimodal interfaces

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Published Papers (3 papers)

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Research

19 pages, 9800 KiB  
Article
Assist-as-Needed Controller of a Rehabilitation Exoskeleton for Upper-Limb Natural Movements
by Shuo Pei, Jiajia Wang, Chenghua Tian, Xibin Li, Bingqi Guo, Junlong Guo and Yufeng Yao
Appl. Sci. 2025, 15(5), 2644; https://doi.org/10.3390/app15052644 - 28 Feb 2025
Viewed by 288
Abstract
Active patient participation in the rehabilitation process after stroke has been shown to accelerate neural remodeling. The control framework of rehabilitation robots should provide appropriate assistive forces to users. An assist-as-needed (AAN) control method is proposed to help users to move upper limbs [...] Read more.
Active patient participation in the rehabilitation process after stroke has been shown to accelerate neural remodeling. The control framework of rehabilitation robots should provide appropriate assistive forces to users. An assist-as-needed (AAN) control method is proposed to help users to move upper limbs in the workspace freely, and to control the exoskeleton to provide assistance. The method is based on zero moment control (ZMC), helping the user achieve robotic traction with minimal interaction force. Based on the posture of the upper arm and forearm, an AAN controller can modify assistive forces at two human–robot-interaction (HRI) points along the direction opposite to gravity. A shoulder motion prediction model is proposed to enable the exoskeleton to mimic the user’s upper limb natural movements. In order to improve the transparency during rehabilitation training, a nonlinear numerical friction model based on the Stribeck friction model is developed. A healthy adult male was recruited to perform various activities of daily living (ADL) tests to assess the effectiveness of the controllers. The experimental results show that the proposed ZMC controller has high HRI transparency and can control the exoskeleton to complete a wide range of upper limb movements, and the maximum interaction force and torque can be captured within −7.76 N and 4.58 Nm, respectively. The AAN controller can provide appropriate assistance in the desired direction, and the exoskeleton maintains kinematic synchronization with the user’s shoulder during shoulder girdle movement. Full article
(This article belongs to the Special Issue Emerging Technologies for Assistive Robotics)
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19 pages, 858 KiB  
Article
The Impact of RObotic Assisted Rehabilitation on Trunk Control in Patients with Severe Acquired Brain Injury (ROAR-sABI)
by Letizia Castelli, Claudia Loreti, Anna Maria Malizia, Chiara Iacovelli, Sabina Renzi, Luca Fioravanti, Vincenza Amoruso, Ilaria Paolasso, Francesca Di Caro, Luca Padua and Silvia Giovannini
Appl. Sci. 2025, 15(5), 2539; https://doi.org/10.3390/app15052539 - 26 Feb 2025
Viewed by 218
Abstract
Daily activities require balance and control posture. A severe Acquired Brain Injury (sABI) disrupts movement organization, control and execution, affecting trunk control and balance. Trunk control therapy for difficult patients requires known and novel methods. This study analyzes how hunova® robotic platform [...] Read more.
Daily activities require balance and control posture. A severe Acquired Brain Injury (sABI) disrupts movement organization, control and execution, affecting trunk control and balance. Trunk control therapy for difficult patients requires known and novel methods. This study analyzes how hunova® robotic platform therapy affects sABI patients’ sitting balance and trunk control. Twenty-six sABI patients were randomized into the experimental group (HuG) that employed hunova® for trunk control in addition to traditional therapy and the control group (CoG) that received only conventional rehabilitation. Clinical assessments were performed for trunk, balance, cognitive and motor performance, disability, autonomy, quality of life, and fatigue. Both static and dynamic sitting balance and trunk control were assessed with hunova®. HuG and CoG were significant in intragroup analysis. Intergroup comparisons showed substantial differences in trunk control, affected side motor function, autonomy, quality of life, and fatigue. Only patients with HuG improved statistically in the instrumental assessment of trunk control and sitting balance. Between-group analysis showed that a statistically significant difference emerged in COP path and trunk movement. The study found effectiveness and adaptability of hunova® for trunk control rehabilitation, showing improvement in static and dynamic trunk control, motor function, autonomy, quality of life and fatigue in sABI patients. Registration: NCT05280587. Full article
(This article belongs to the Special Issue Emerging Technologies for Assistive Robotics)
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41 pages, 3669 KiB  
Article
Exploring Embodiment Form Factors of a Home-Helper Robot: Perspectives from Care Receivers and Caregivers
by Katherine M. Tsui, Rune Baggett and Carol Chiang
Appl. Sci. 2025, 15(2), 891; https://doi.org/10.3390/app15020891 - 17 Jan 2025
Viewed by 845
Abstract
Society’s aging is a worldwide crisis that affects many countries, as the Older Adult (OA) population is growing faster than younger populations. With this, there are fewer caregivers (CGs), and more care receivers (CRs) exist. It is vital to understand how we can [...] Read more.
Society’s aging is a worldwide crisis that affects many countries, as the Older Adult (OA) population is growing faster than younger populations. With this, there are fewer caregivers (CGs), and more care receivers (CRs) exist. It is vital to understand how we can ease the burden of caregiving on both the care receivers’ and caregivers’ sides. Our research focuses on robotic mobility and stability assistance for independent living OAs. We draw upon best practices from Occupational Therapy for sit-to-stand (STS) transfer techniques and question what sit-to-stand could look like if performed by a robot. Drawing inspiration from assistive devices, we designed 3 robot embodiments: a humanoid robot, a pair of robots, and a simple pole robot. We conducted a cross-cultural study with 24 CR and CG focus groups in both the United States and Japan to understand OAs’ preferences and expected functionality for continued independence in their homes. Our findings show that, from the perspectives of both CRs and CGs in both countries, TRIbot, the humanoid robot was the most preferred (Japan 34 of 48 participants; 70.8% and US 24 of 43 participants; 55.8%) for caregiving tasks as it was perceived to be the most capable of providing increased assistance as OAs age. Additionally and unsurprisingly, OAs expected the robot to perform general household tasks and that they would speak to the robot. We contextualize our results within the rising popularity of humanoid robots and the desire for general purpose Artificial Intelligence. Full article
(This article belongs to the Special Issue Emerging Technologies for Assistive Robotics)
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