Empowering Independence: The Role of Assistive Technologies in Enhancing Quality of Life

Assistive technologies are increasingly central to improving quality of life across various settings, from rehabilitation to ongoing care [1]. They are transforming how we address complex needs [2,3], ranging from communication support—such as augmentative and alternative communication (AAC) systems [4,5]—to solutions for neuromotor disabilities [6]. Continuous research advances drive the development of innovative, high-performance technologies, including robotics, wearable devices, and implantable prostheses, which enhance physical abilities, support mobility, and facilitate communication. These technologies also extend care beyond traditional settings through telemedicine and networked medical applications [7].

Despite significant progress, key challenges remain, including person-centered care, personalized assistive solutions, and improved accessibility [8]. Regulatory frameworks like the International Classification of Functioning, Disability, and Health (ICF) [9] and global initiatives led by the World Health Organization (WHO) [10] play a crucial role in raising awareness, monitoring developments, and promoting access to assistive technologies worldwide [8,9].

The Special Issue Assistive Technologies in Care and Rehabilitation: Research, Developments, and International Initiatives [11] explore topics such as the integration of robotics and artificial intelligence in rehabilitation, the role of wearable devices in enhancing autonomy, the impact of telemedicine on remote care, international standards and regulations, the personalization of assistive solutions, ambient assistive technologies, advances in virtual and augmented reality, ethical and economic considerations, user experience, training, and collaboration among healthcare providers, developers, and patients.

The editorial project produced 24 contributions (contributions 1 to 24) plus the present editorial. The contributions include 18 research studies, consisting of 17 scientific articles (contributions 1–5, 7–18), 1 communication (contribution 6), and 6 review studies (contributions 19–24), of which 3 are systematic reviews (contributions 22–24).

Overall, about 75% of the contributions are research studies (18 out of 24) and 25% are review studies (6 out of 24), with half of the reviews being systematic reviews (3 out of 6).

Common message

The collection of contributions (contribution 1–24) presents significant progress in assistive and rehabilitative technologies aimed at improving independence, functionality, and quality of life for diverse populations. The research articles (contribution 1–18) explore innovations such as real-time tactile feedback for speech assistance (contribution 1), socially assistive robots (contribution 3, 7), vision-based activity recognition (contribution 8), and AI-powered personalized rehabilitation programs (contribution 12). These studies emphasize user-centered design and the integration of advanced technologies into everyday and clinical settings.

Supporting these findings, the reviews (contribution 19–24) synthesize current knowledge on various assistive devices, virtual reality applications, robotic rehabilitation systems, and environmental monitoring technologies. They provide critical evaluations of effectiveness, trends, and knowledge gaps, guiding future research and development efforts.

Together, these contributions reflect a multidisciplinary approach where technology, clinical practice, and patient needs intersect to create accessible, effective, and sustainable healthcare solutions (contribution 1–24).

Key Scientific Contributions of the Articles

A total of 18 original research articles present innovative advancements across various fields, including healthcare, assistive technologies, rehabilitation, and human–technology interactions. Each contribution offers novel solutions or insights that enhance quality of life, improve clinical practices, and support independent living for diverse populations such as individuals with disabilities, the elderly, and patients undergoing medical treatment. Together, these studies demonstrate the growing impact of technology-driven research in addressing complex challenges and fostering personalized, effective interventions.

Contribution 1 addresses a wearable haptic feedback system designed to assist speech training for individuals with speech and hearing impairments. Unlike previous methods, this system offers real-time, phoneme-level tactile cues that empower users to independently improve their pronunciation through a multimodal interface combining audio, visual, and vibrotactile feedback. Validation studies demonstrated significant improvements in articulation accuracy and user engagement, highlighting its potential as an accessible tool for speech rehabilitation and language learning.

Contribution 2 focuses on the integration of advanced assistive technologies—such as socially assistive robots, virtual reality, and conversational AI—into Speech and Language Therapy (SLT) for children with communication disorders. This work presents the “ATLog” platform, a user-friendly software enabling therapists to design personalized interactive learning scenarios without programming expertise. Evaluations by SLT experts show high acceptance and usability, suggesting the platform effectively supports the practical adoption of these innovative technologies in therapy.

Contribution 3 explores the role of social robots within Ambient Assisted Living (AAL) environments aimed at enhancing elderly care. The proposed framework positions a social robot as the central coordinator of smart home devices, facilitating natural interaction and real-time recognition of gestures and moods to support seniors’ independence. This paper discusses the technical aspects and scenarios demonstrating how this integration can improve quality of life and reduce caregiver burden.

Contribution 4 presents a novel approach to assess neck pain by using a virtual reality (VR) environment simulating an apple-harvesting task. By continuously tracking head movement kinematics, this study identifies functional limitations in patients with neck pain that traditional range-of-motion measurements might miss. The VR-based assessment shows promise for remote evaluation and personalized telerehabilitation strategies.

Contribution 5 introduces a non-contact system leveraging a Microsoft Azure Kinect depth camera to evaluate physical function and postural stability in older adults. Through motion capture during squats and balance stances, the platform detects biomechanical differences associated with aging and fall risk. The findings support the feasibility of using low-cost depth-camera technology for ongoing risk assessment and fall prevention.

Contribution 6 details an innovative in vivo device for dynamic mechanical analysis (DMA) of plantar soft tissue, enabling multidimensional characterization under physiological conditions. This device overcomes limitations of conventional testing by providing real-time measurements of viscoelastic properties such as tensile, compressive, shear, and torsional behaviors. The open-source design facilitates further research and has applications in diagnostics and personalized orthopedic treatments.

Contribution 7 investigates changes in elderly residents’ perceptions of a humanoid social robot (HSR) following direct interaction. Using the Godspeed Questionnaire Series, this study found positive shifts in views on anthropomorphism, animation, likeability, and perceived intelligence after hands-on experience. Results emphasize the importance of real interaction in developing social robots tailored to older adults’ needs.

Contribution 8 proposes a computer vision-based activity monitoring system for elderly care environments, combining cameras and infrared sensors to detect daily activities and anomalies without extensive labeled data. Real-world deployment demonstrated improved emergency response and respect for privacy via anonymized views. The system supports continuous, unobtrusive monitoring to enhance safety and independence.

Contribution 9 analyzes the impact of emerging technologies on the quality of life for individuals with autism spectrum disorder (ASD) and comorbid chronic anxiety or depression. Using large-scale survey data, this study identifies communication and learning challenges as significant factors affecting well-being. It suggests that technological interventions, potentially evaluated through quantum computing methods, could improve emotional regulation and social skills in this population.

Contribution 10 explores the optimization of sensor types, locations, and models for high-accuracy Human Activity Recognition (HAR) in fall prevention. By analyzing four multimodal HAR datasets (USC-HAD, HuGaDB, Camargo et al., CSL-SHARE), it identifies that window sizes between 2 and 5 s and models such as Support Vector Machines (SVMs) and Artificial Neural Networks (ANNs) achieve the best performance. This study further reveals that Inertial Measurement Units (IMUs) placed on the thigh yield optimal classification accuracy, while Electromyography (EMG) sensors show inconsistent results.

Contribution 11 proposes a study on the usability of no-code (NC) platforms by individuals with disabilities. Conducted in a German sheltered workshop, this study involved targeted training enabling participants to develop workplace chatbots. Results demonstrate that participants successfully created multiple chatbots that were well received by their peers, confirming that, with appropriate support, people with disabilities can leverage NC tools to build effective, accessible workplace applications.

Contribution 12 evaluates the feasibility of using large language models (LLMs) to generate personalized postoperative rehabilitation plans for head and neck surgery patients. Four LLMs (ChatGPT-4o, DeepSeek V3, Gemini 2, and Copilot) were compared across clinical scenarios, with ChatGPT-4o producing the most clinically relevant plans. This study highlights that AI-generated rehabilitation programs have potential to complement existing protocols but require further clinical validation.

Contribution 13 introduces a Neuro-Visual Adaptive Control (NVAC) architecture for enhanced precision in robot-assisted surgery. Combining a YOLO11n-based vision system, Model Reference Adaptive Control with Proportional-Derivative terms (MRAC-PD), and Closed-Form Continuous-Time Neural Networks (CfC-mmRNNs), the system achieves sub-millimeter tracking accuracy in laparoscope guidance under dynamic disturbances, demonstrating a scalable framework for increasing surgical robot autonomy.

Contribution 14 investigates a novel technology system designed to assist individuals with intellectual disabilities and blindness in handling and transporting boxes within a facility. Using RFID tags, a smartphone interface, and audio prompts with preferred music, the system significantly increased the frequency of correct box handling without human guidance, suggesting potential benefits for supporting autonomy in this population.

Contribution 15 presents improvements in the “Infinity” foot controller for prosthetic arm operation and introduces the “Persistence Arm,” a novel transradial prosthesis prototype. The new system enables barefoot foot control with low latency, and the arm features advanced direct-drive wrist actuation and tendon-driven fingers. Tests demonstrate effective grip strength and adaptability, indicating the promise of foot control and 3D-printed prosthetics as cost-effective alternatives to traditional upper limb prostheses.

Contribution 16 applies a technology assessment framework and key performance indicators (KPIs) to evaluate telemedicine services within the Telemechron project. This study confirms the framework’s effectiveness in measuring telemedicine improvements and stresses the need for KPI customization to fit diverse contexts. It advocates for further development of adaptable evaluation metrics to support telemedicine performance nationally and internationally.

Contribution 17 proposes an original rehabilitation device for passive mobilization of the neck joint using pneumatic muscle actuators. Designed for patients with work-related musculoskeletal disorders, the device adapts to individual pain tolerance and provides controlled mobilization in sagittal and frontal planes. This paper details the device’s construction, mechanical properties, and offers recommendations for optimal clinical use.

Contribution 18 examines the relationships between technology readiness/acceptance, exercise motivation, sensation seeking, and the use of Smart Sport Watches (SSWs) in adolescents. This study finds that SSW users display higher positive technology readiness and lower negative readiness, while exercise motivation is more related to physical activity (walking/running) than to SSW usage. The findings highlight the role of technology acceptance in wearable adoption and suggest tailored measures for deeper understanding.

Key Scientific Contributions of the review studies

The following review studies provide valuable insights into the advancement of assistive technologies and rehabilitation interventions across various medical conditions. Contributions range from comprehensive analyses of assistive devices for joint mobility (Contribution 19) and virtual reality applications in physical rehabilitation (Contribution 20) to detailed examinations of hand rehabilitation devices for neurological disorders (Contribution 21). Additionally, systematic reviews explore sensor-based remote rehabilitation for chronic low back pain (Contribution 22), assistive technologies aimed at stress reduction in autism spectrum disorder (Contribution 23), and the role of indoor air quality monitoring in managing chronic respiratory diseases (Contribution 24). Collectively, these reviews highlight technological progress, clinical effectiveness, challenges, and emerging research needs in their respective fields.

Contribution 19 presents a comprehensive review of assistive devices for synovial joints, focusing on their definitions, classifications, and technological evolution. This work analyzes artificial exoskeletons, orthoses, prostheses, and splints, clarifying terminology and biomechanical principles. It emphasizes the need for a systematic approach to design and categorization to enhance rehabilitation and human mobility across medical, industrial, and military applications.

Contribution 20 presents a scoping review of virtual reality (VR) interventions aimed at improving mobility in both adults and children, based on studies from 2010 to 2023. It highlights significant clinical research demonstrating VR’s effectiveness, primarily in inpatient settings, with many studies showing statistically significant motor improvements. This review underlines VR’s transition from proof of concept to clinical translation in physical rehabilitation.

Contribution 21 provides an extensive review of hand rehabilitation devices for neurological conditions such as stroke, Parkinson’s disease, and multiple sclerosis. Categorizing devices by design, mobility, and actuation, it identifies key trends like the predominance of electric actuation and dorsal placement. This review notes challenges like incomplete data and limited clinical validation but underscores opportunities for improving device functionality and therapeutic efficacy.

Contribution 22 offers a systematic review of sensor-based remote rehabilitation and VR interventions for chronic low back pain (CLBP). Analyzing randomized controlled trials and observational studies from 2015 to 2025, it reports positive outcomes in pain reduction, functional mobility, adherence, and quality of life. This review highlights gamification and biofeedback as critical to enhancing patient engagement but calls for more long-term and economic evaluations.

Contribution 23 presents a systematic review investigating assistive and emerging technologies aimed at reducing stress and neurophysiological distress in children and adolescents with autism spectrum disorder (ASD). Using PRISMA guidelines, this study found beneficial impacts of these technologies on stress reduction and identified limitations affecting replicability and generalizability.

Contribution 24 offers a systematic review on indoor air quality (IAQ) monitoring and its role in managing chronic respiratory diseases such as COPD and asthma. This review highlights significant research gaps including standardization issues, geographic and patient heterogeneity, and the need for long-term studies. It also points to the emerging potential of integrating IAQ monitoring with machine learning to improve respiratory health outcomes.

Conclusions

The collection of 24 scientific articles reviewed herein—including 18 original research contributions and 6 comprehensive reviews—demonstrates significant innovative advancements across healthcare, assistive technologies, rehabilitation, and human–technology interactions. Together, these works highlight the accelerating impact of technology-driven research in addressing complex health challenges, improving clinical practices, and enhancing quality of life for diverse populations such as individuals with disabilities, elderly people, and patients undergoing specialized medical care. The original studies present novel solutions ranging from wearable feedback systems and AI-supported therapy platforms to advanced prosthetics and intelligent monitoring frameworks. The review articles further contextualize these advances by synthesizing current evidence on assistive devices, virtual reality in rehabilitation, sensor-based remote therapies, stress-reducing technologies in autism, and environmental health monitoring. Collectively, the body of work underscores the critical importance of user-centered design, clinical validation, and interdisciplinary collaboration in fostering effective and personalized interventions.

Future Directions

Future efforts should focus on longitudinal clinical validation and real-world implementation to ensure the efficacy, safety, and scalability of these emerging technologies. Enhancing personalization through AI and adaptive systems, improving accessibility via no-code and user-friendly platforms, and emphasizing inclusive design for vulnerable and underserved populations will be essential. Cross-disciplinary partnerships among clinicians, engineers, data scientists, and users are crucial to accelerate translation from research to practice. Furthermore, proactive attention to ethical considerations, data privacy, and regulatory frameworks will support responsible technology deployment. By integrating these priorities, ongoing research can fully harness technological innovation to transform healthcare and rehabilitation, ultimately improving patient outcomes and autonomy.