Enhancing Locomotion-Mode Recognition and Transition Prediction with (Bio)Mechanical Sensor Fusion for Intelligent Prosthetic Knees.

The ability to continuously recognize locomotion modes and accurately predict transition intentions is essential for intelligent prosthetic knees. In this study, an innovative framework for locomotion recognition and transition prediction was introduced based on fusing mechanical (inertial measurement unit (IMU)) and biomechanical (force myography (FMG)) signals. This framework integrated an FMG-IMU dual-modal sensing system implemented on a prosthetic knee, enabling simultaneous acquisition of FMG-IMU fusion signals from transfemoral amputees during dynamic walking.

Reducing Upper-Limb Muscle Effort with Model-Based Gravity Compensation During Robot-Assisted Movement.

Clinical research has demonstrated that stroke patients benefit from active participation during robot-assisted training. However, the weight of the arm impedes the execution of tasks and movements due to the functional disability. The purpose of this paper is to develop a gravity compensation strategy for an end-effector upper limb rehabilitation robot based on an arm dynamics model to reduce the arm's muscle activation level.

Research on target localization and adaptive scrubbing of intelligent bathing assistance system.

Introduction: Bathing is a primary daily activity. Existing bathing systems are limited by their lack of intelligence and adaptability, reliance on caregivers, and the complexity of their control algorithms. Although visual sensors are widely used in intelligent systems, current intelligent bathing systems do not effectively process depth information from these sensors.

Enhancing and Shaping Closed-Loop Co-Adaptive Myoelectric Interfaces With Scenario-Guided Adaptive Incremental Learning.

Virtual environments have been employed in the myoelectric prosthetics field as effective training and assessment tools to enhance intrinsic motivation, thereby encouraging sustained engagement in neuromuscular rehabilitation. However, motivating amputees to maintain consistent participation and perseverance in long-term training remains a critical challenge. To address this, we propose a scenario-guided adaptive incremental learning strategy that leverages contextual information in unknown environments to improve pseudo-label prediction accuracy.

Lateral Walking Gait Recognition and Hip Angle Prediction Using a Dual-Task Learning Framework.

Lateral walking exercise is beneficial for the hip abductor enhancement. Accurate gait recognition and continuous hip joint angle prediction are essential for the control of exoskeletons. We propose a dual-task learning framework, the "Twin Brother" model, which fuses convolutional neural network (CNN), long short-term memory (LSTM), neural networks (NNs), and the squeezing-elicited attention mechanism to classify the lateral gait stage and estimate the hip angle from electromyography (EMG) signals.

Enhancing and Optimizing User-Machine Closed-Loop Co-Adaptation in Dynamic Myoelectric Interface.

Co-adaptation interfaces, developed through user-machine collaboration, have the capacity to transform surface electromyography (sEMG) into control signals, thereby enabling external devices to facilitate or augment the sensory-motor capabilities of individuals with physical disabilities. However, the efficacy and reliability of myoelectric interfaces in untrained environments over extensive spatial range have not been thoroughly explored. We propose a user-machine closed-loop co-adaptation strategy, which consists of a multimodal progressive domain adversarial neural network (MPDANN), an augmented reality (AR) system and a scenario-based dynamic asymmetric training scheme.

Lateral walking gait phase recognition for hip exoskeleton by denoising autoencoder-LSTM.

Lateral resistance walk is an effective way to strengthen the abductor muscles of the hip. Accurate lateral walking gait recognition is the prerequisite for exoskeletons to be applied to lateral walking exercises. This paper proposes a denoising autoencoder-LSTM (DAE-LSTM) algorithm for lateral walking gait recognition.

Long-term care plan recommendation for older adults with disabilities: a bipartite graph transformer and self-supervised approach.

Background: With the global population aging and advancements in the medical system, long-term care in healthcare institutions and home settings has become essential for older adults with disabilities. However, the diverse and scattered care requirements of these individuals make developing effective long-term care plans heavily reliant on professional nursing staff, and even experienced caregivers may make mistakes or face confusion during the care plan development process. Consequently, there is a rigid demand for intelligent systems that can recommend comprehensive long-term care plans for older adults with disabilities who have stable clinical conditions.

Design of semi-open prosthetic socket with constant force for lower limb.

Background: Prosthetic socket is a key component of the prosthesis for clinical application; its performance directly affects the adaptation of the residual limb to the prosthetic socket. There are long-term and short-term volume fluctuation of the residual limb. The volume fluctuation of the residual limb will lead to the pressure mismatch at the interface of the residual limb and the prosthetic socket, which will cause a series of skin and fit problems.

Research on a novel flexible bionic artificial anal sphincter.

Background: Artificial anal sphincter is a novel method for the treatment of fecal incontinence. Aiming at the problems of complex mechanical structure, high mechanical failure rate, large volume and poor biocompatibility of existing artificial anal sphincters, this article proposes a novel flexible artificial anal sphincter with bionic structure.

Methods: A novel flexible artificial anal sphincter was proposed with bionic structure by analogy with the puborectalis, flexible transmission by flexible tendons, good biocompatibility by using thermoplastic urethane and medical silicone, small size and lightweight.

Resting-state fNIRS reveals changes in prefrontal cortex functional connectivity during TENS in patients with chronic pain.

Transcutaneous electrical nerve stimulation (TENS) has been used to treat chronic pain. However, the potential efficacy and mechanism of the effect of applying TENS for a short time in chronic pain patients remains unclear. To identify the effect of short-term TENS on chronic pain patients and to clarify the mechanism of the effect, we investigated abnormalities of functional connectivity (FC) within the prefrontal cortex (PFC) using resting-state functional near-infrared spectroscopy (rs-fNIRS).

A type-2 fuzzy inference-based approach enables walking speed estimation that adapts to inter-individual gait patterns.

Objectives: Individuals change walking speed by regulating step frequency (SF), stride length (SL), or a combination of both (FL combinations). However, existing methods of walking speed estimation ignore this regulatory mechanism. This paper aims to achieve accurate walking speed estimation while enabling adaptation to inter-individual speed regulation strategies.

Research on design and control methods of a lightweight upper limb joint isokinetic rehabilitation training equipment.

Introduction: Isokinetic exercise can improve joint muscle strength and stability, making it suitable for early rehabilitation of stroke patients. However, traditional isokinetic equipment is bulky and costly, and cannot effectively avoid external environmental interference.

Methods: This paper designed a lightweight upper limb joint isokinetic rehabilitation training equipment, with a control system that includes a speed planning strategy and speed control with disturbance rejection.

Experimental evaluation of an artificial anal sphincter based on biomechanical compatibility.

Background: The artificial anal sphincter is a device used to treat patients with fecal incontinence who are unable to control their bowel movements on their own. Long-term morphological changes in the tissue surrounding the artificial anal sphincter can cause biomechanical compatibility problems, which seriously affect the clinical application of the artificial anal sphincter.

Methods: In this paper, the superelasticity of shape memory alloys was utilized to design and fabricate a biomechanically compatible constant force clamping artificial anal sphincter.

A comprehensive study on Mecanum wheel-based mobility and suspension solutions for intelligent nursing wheelchairs.

Intelligent nursing wheelchairs significantly enhance mobility and independence for elderly individuals with disabilities. However, traditional designs often suffer from large turning radii that restrict their functionality in confined spaces. Addressing this critical challenge, this study introduces an innovative design utilizing a Mecanum wheel chassis that allows for omnidirectional movement, significantly improving maneuverability and stability.

[Research status of lower limb exoskeleton rehabilitation robot].

Lower limb exoskeleton rehabilitation robots are used to improve or restore the walking and movement ability of people with lower limb movement disorders. However, the required functions for patients differ based on various diseases. For example, patients with weak muscle strength require power assistance, patients with spinal cord injuries require motion compensation, patients with gait abnormalities require gait correction, and patients with strokes require neural rehabilitation.

Smart Nursing Wheelchairs: A New Trend in Assisted Care and the Future of Multifunctional Integration.

As a significant technological innovation in the fields of medicine and geriatric care, smart care wheelchairs offer a novel approach to providing high-quality care services and improving the quality of care. The aim of this review article is to examine the development, applications and prospects of smart nursing wheelchairs, with particular emphasis on their assistive nursing functions, multiple-sensor fusion technology, and human-machine interaction interfaces. First, we describe the assistive functions of nursing wheelchairs, including position changing, transferring, bathing, and toileting, which significantly reduce the workload of nursing staff and improve the quality of care.

State of the Art of Brain Function Detection Technologies in Robot-Assisted Lower Limb Rehabilitation.

With an aging population, the prevalence of neurological disorders is increasing, leading to a rise in lower limb movement disorders and, in turn, a growing need for rehabilitation training. Previous neuroimaging studies have shown a growing scientific interest in the study of brain mechanisms in robot-assisted lower limb rehabilitation (RALLR). This review aimed to determine differences in neural activity patterns during different RALLR tasks and the impact on neurofunctional plasticity.

Perception of defecation intent: applied methods and technology trends.

The aging population has led to a widening gap between the supply and demand for defecation care. To address this issue, the development of defecation care devices is the most direct and effective solution. Pre-defecation care devices offer a more personalized and comfortable alternative to the conventional post-defecation care devices currently available on the market.

Control strategies for trunk exoskeletons based on motion intent recognition: A review.

Background: Wearable trunk exoskeletons hold immense potential in fields such as healthcare and industry. Previous research has indicated that intention recognition control plays a crucial role in users' daily use of exoskeletons.

Objective: This review aims to discuss the characteristics of intention recognition control schemes for intelligent trunk exoskeletons under different control objectives over the past decade.

Research on multi-dimensional intelligent quantitative assessment of upper limb function based on kinematic parameters.

Background: Rehabilitation assessment is a critical component of rehabilitation treatment.

Objective: This study focuses on a comprehensive analysis of patients' movement performance using the upper limb rehabilitation robot. It quantitatively assessed patients' motor control ability and constructed an intelligent grading model of functional impairments.

A decision support system for upper limb rehabilitation robot based on hybrid reasoning with RBR and CBR.

The rehabilitation robot can assist hemiplegic patients to complete the training program effectively, but it only focuses on helping the patient's training process and requires the rehabilitation therapists to manually adjust the training parameters according to the patient's condition. Therefore, there is an urgent need for intelligent training prescription research of rehabilitation robots to promote the clinical applications. This study proposed a decision support system for the training of upper limb rehabilitation robot based on hybrid reasoning with rule-based reasoning (RBR) and case-based reasoning (CBR).

Current status and clinical perspectives of extended reality for myoelectric prostheses: review.

Training with "Extended Reality" or X-Reality (XR) systems can undoubtedly enhance the control of the myoelectric prostheses. However, there is no consensus on which factors improve the efficiency of skill transfer from virtual training to actual prosthesis abilities. This review examines the current status and clinical applications of XR in the field of myoelectric prosthesis training and analyses possible influences on skill migration.