Soft Nanomembrane Sensor-Enabled Wearable Multimodal Sensing and Feedback System for Upper-Limb Sensory Impairment Assistance

ACS Nano, Journal Year: 2025, Volume and Issue: 19(5), P. 5613 - 5628

Published: Jan. 31, 2025

Sensory rehabilitation in pediatric patients with traumatic spinal cord injury is challenging due to the ongoing development of their nervous systems. However, these sensory problems often result nonuse impaired limb, which disturbs limb and leads overuse contralateral other physical or psychological issues that may persist. Here, we introduce a soft nanomembrane sensor-enabled wearable glove system wirelessly delivers haptic sensation from hand tactile feedback responses for impairment assistance. The smart uses gold nanomembranes, copper-elastomer composites, laser-induced graphene sensitive detection pressure, temperature, strain changes. nanomaterial sensors are integrated low-profile actuators wireless flexible electronics offer real-time feedback. system's thin-film demonstrate 98% 97% accuracy detecting pressure finger flexion, respectively, along coverage real-life temperature changes as an effective tool. Collectively, upper-limb assistance embodies latest materials technology incorporate miniaturized maximize its compatibility human users, offering promising solution patient rehabilitation.

Language: Английский

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Neural Network for Enhancing Robot-Assisted Rehabilitation: A Systematic Review

Actuators, Journal Year: 2025, Volume and Issue: 14(1), P. 16 - 16

Published: Jan. 6, 2025

The integration of neural networks into robotic exoskeletons for physical rehabilitation has become popular due to their ability interpret complex physiological signals. Surface electromyography (sEMG), (EMG), electroencephalography (EEG), and other signals enable communication between the human body systems. Utilizing communicating with robots plays a crucial role in robot-assisted neurorehabilitation. This systematic review synthesizes 44 peer-reviewed studies, exploring how can improve exoskeleton individuals impaired upper limbs. By categorizing studies based on joints, sensor systems, control methodologies, we offer comprehensive overview network applications this field. Our findings demonstrate that networks, such as Convolutional Neural Networks (CNNs), Long Short-Term Memory (LSTM), Radial Basis Function (RBFNNs), forms significantly contribute patient-specific by enabling adaptive learning personalized therapy. CNNs motion intention estimation accuracy, while LSTM capture temporal muscle activity patterns real-time rehabilitation. RBFNNs human–robot interaction adapting individual movement patterns, leading more efficient highlights potential revolutionize limb rehabilitation, improving motor recovery patient outcomes both clinical home-based settings. It also recommends future direction customizing existing applications.

Language: Английский

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Artificial Intelligence in Public Health: Current Trends and Future Possibilities

International Journal of Environmental Research and Public Health, Journal Year: 2022, Volume and Issue: 19(19), P. 11907 - 11907

Published: Sept. 21, 2022

Artificial intelligence (AI) is a discipline that studies whether and how intelligent computer systems can simulate the capacity behaviour of human thought be created [...]

Language: Английский

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Soft Hand Exoskeletons for Rehabilitation: Approaches to Design, Manufacturing Methods, and Future Prospects

Robotics, Journal Year: 2024, Volume and Issue: 13(3), P. 50 - 50

Published: March 15, 2024

Stroke, the third leading cause of global disability, poses significant challenges to healthcare systems worldwide. Addressing restoration impaired hand functions is crucial, especially amid workforce shortages. While robotic-assisted therapy shows promise, cost and community concerns hinder adoption exoskeletons. However, recent advancements in soft robotics digital fabrication, particularly 3D printing, have sparked renewed interest this area. This review article offers a thorough exploration current landscape exoskeletons, emphasizing alternative designs. It surveys previous reviews field examines relevant aspects anatomy pertinent wearable rehabilitation devices. Furthermore, investigates design requirements for exoskeletons provides detailed various exoskeleton gloves, categorized based on their principles. The discussion encompasses simulation-supported methods, affordability considerations, future research directions. aims benefit researchers, clinicians, stakeholders by disseminating latest advances technology, ultimately enhancing stroke outcomes patient care.

Language: Английский

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The Use of Sports Rehabilitation Robotics to Assist in the Recovery of Physical Abilities in Elderly Patients with Degenerative Diseases: A Literature Review

Healthcare, Journal Year: 2023, Volume and Issue: 11(3), P. 326 - 326

Published: Jan. 21, 2023

The increase in the number of elderly patients with degenerative diseases has brought additional medical and financial pressures, which are adding to burden on society. development sports rehabilitation robotics (SRR) is becoming increasingly sophisticated at technical level its application; however, few studies have analyzed how it works effective aiding rehabilitation, fewer individualized exercise programs been developed for patients. purpose this study was analyze working methods effects different types SRR then suggest feasibility applying enhance physical abilities diseases. researcher’s team searched 633 English-language journal articles, had published over past five years, they selected 38 them a narrative literature review. Our summary found following: (1) current generally classified as end-effector robots, smart walkers, intelligent robotic rollators, exoskeleton robots—exoskeleton robots were be most widely used. (2) include assistant tools main intermediaries—i.e., assist participate; dominate sensors myoelectric-driven promote patient participation. (3) Better recovery perceived when using than achieved through traditional single-movement methods, especially strength, balance, endurance, coordination. However, there no significant improvement their speed or agility after SRR.

Language: Английский

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Intelligent rehabilitation in an aging population: empowering human-machine interaction for hand function rehabilitation through 3D deep learning and point cloud

Frontiers in Computational Neuroscience, Journal Year: 2025, Volume and Issue: 19

Published: May 2, 2025

Human-machine interaction and computational neuroscience have brought unprecedented application prospects to the field of medical rehabilitation, especially for elderly population, where decline recovery hand function become a significant concern. Responding special needs under context normalized epidemic prevention control aging trend this research proposes method based on 3D deep learning model process laser sensor point cloud data, aiming achieve non-contact gesture surface feature analysis in intelligent rehabilitation human-machine functions. By integrating key technologies such as collection clouds, local extraction, abstraction enhancement dimensional information, has constructed an accurate system. In terms experimental results, validated superior performance proposed recognizing with average accuracy 88.72%. The findings are importance promoting development technology functions enhancing safe comfortable methods patients.

Language: Английский

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Simultaneous Estimation of Hand Configurations and Finger Joint Angles Using Forearm Ultrasound

IEEE Transactions on Medical Robotics and Bionics, Journal Year: 2023, Volume and Issue: 5(1), P. 120 - 132

Published: Jan. 18, 2023

With the advancement in computing and robotics, it is necessary to develop fluent intuitive methods for interacting with digital systems, augmented/virtual reality (AR/VR) interfaces, physical robotic systems. Hand motion recognition widely used enable these interactions. configuration classification metacarpophalangeal (MCP) joint angle detection important a comprehensive reconstruction of hand motion. Surface electromyography (sEMG) other technologies have been motions. Forearm ultrasound images provide musculoskeletal visualization that can be understand Recent work has shown classified using machine learning estimate discrete configurations. Estimating both MCP angles based on forearm not addressed literature. In this paper, we propose convolutional neural network (CNN) deep pipeline predicting angles. The results were compared by different algorithms. Support vector classifier kernels, multi-layer perceptron, proposed CNN classify into 11 configurations activities daily living. acquired from 6 subjects instructed move their hands according predefined Motion capture data was get finger corresponding movements at speeds (0.5 Hz, 1 & 2 Hz) index, middle, ring, pinky fingers. Average accuracy 82.7 ± 9.7% over 80% SVC kernels observed subset dataset. An average RMSE $7.35^{\circ }\pm 1.3$ ° obtained between predicted true A low latency (6.25 - 9.1 estimating aimed real-time control human-machine interfaces.

Language: Английский

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A Review of Wrist Rehabilitation Robots and Highlights Needed for New Devices

Machines, Journal Year: 2024, Volume and Issue: 12(5), P. 315 - 315

Published: May 3, 2024

Various conditions, including traffic accidents, sports injuries, and neurological disorders, can impair human wrist movements, underscoring the importance of effective rehabilitation methods. Robotic devices play a crucial role in this regard, particularly rehabilitation, given complexity joint, which encompasses three degrees freedom: flexion/extension, pronation/supination, radial/ulnar deviation. This paper provides comprehensive review devices, employing methodological approach based on primary articles sourced from PubMed, ScienceDirect, Scopus, IEEE, using keywords “wrist robot” 2007 onwards. The findings highlight diverse array systematically organized tabular format for enhanced comprehension. Serving as valuable resource researchers, enables comparative analyses robotic across various attributes, offering insights into future advancements. Particularly noteworthy is integration serious games with simplified signaling promising avenue enhancing outcomes. These lay groundwork development new or to make improvements existing prototypes incorporating forward-looking improve

Language: Английский

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Control strategy based on improved fuzzy algorithm for energy control of wrist rehabilitation robot

Alexandria Engineering Journal, Journal Year: 2023, Volume and Issue: 77, P. 634 - 644

Published: July 18, 2023

With the complex changes in social and demographic structure, problem of aging is becoming increasingly serious, demand for equipment field medical rehabilitation also increasing. Given above situation, various countries have proposed using robots to assist patients treatment, achieved certain results. The robot helps injured area gradually recover autonomous movement through repeated auxiliary actions, thereby achieving goal physical training. However, most configurations face insufficient energy power, as well bulky inflexible equipment. Based on issues, this article adopts an improved fuzzy algorithm control strategy optimize storage device applies system wrist training device. Firstly, a adaptive added traditional controller combine with operational status, precise dynamic adjustment allocation. research has filter optimization design, which improves accuracy effectiveness algorithms. Finally, establishes upper limb motion model configures relevant hardware systems. At same time, uses manufacturing materials that meet functional requirements construct results indicate can improve effect robots. It obvious advantages process

Language: Английский

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Ergonomic Hand Motion Assistance and AR Rehabilitation: Bridging the Gap in Tremor Disorder Therapies Through Mixed Reality

2022 IEEE Conference on Virtual Reality and 3D User Interfaces Abstracts and Workshops (VRW), Journal Year: 2024, Volume and Issue: unknown, P. 322 - 325

Published: March 16, 2024

This study introduces an innovative mixed reality intervention for managing tremor disorders, including essential and Parkinson's disease, which affect motor functions in millions globally. Our device uniquely integrates ergonomic hand motion assistance with augmented (AR) rehabilitation system, aligning Diversity, Equity, Inclusion (DEI) principles. It offers adaptive physical support various sizes patterns AR platform accessible via smartphone. provides personalized exercises includes interactive tutorials telehealth capabilities remote guidance from healthcare professionals. Employing iterative design process informed by feedback stakeholders, affected individuals, medical experts, specialists, the demonstrates significant improvements control task performance. Moreover, it enhances user autonomy satisfaction, bridging gap existing therapies synergizing stabilization virtual rehabilitation. DEI-focused innovation technology represents a substantial advancement comprehensive inclusive disorder treatment, offering versatile, user-friendly solution within XR landscape.

Language: Английский

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