Design of a Breakaway Utensil Attachment for Enhanced Safety in Robot-Assisted Feeding.

Robot-assisted feeding systems enhance the independence of individuals with motor impairments and alleviate caregiver burden. While existing systems predominantly rely on software-based safety features to mitigate risks during unforeseen collisions, this study explores the use of a mechanical fail-safe to improve safety. We designed a breakaway utensil attachment that decouples forces exerted by the robot on the user when excessive forces occur.

Muscle Activation and Postural Sway in Response to Task Complexity: A Study of Balance Control in Older Adults.

In this study, we investigate muscle activation patterns and postural sway in older adults across different stance conditions with varying challenges. Muscle activity from lower limb and trunk muscles was recorded in seven older adults during four stance tasks: double stance, tandem stance, tandem stance with a cognitive task, and tandem stance with combined cognitive and motor tasks (TSCM). We analyzed CoP (centre of pressure) features, EMG (electromyography) patterns, and the coherence between EMG-CoP, to gain insights into neuromuscular coordination and balance control.

Design and Evaluation of a Single-Sided Mobility Assistive Exoskeleton (SMAEXO) for Hemiplegia.

This study presents the Single-Sided Mobility Assistive Exoskeleton (SMAEXO), a novel, single-sided, multijoint device designed to enhance mobility and rehabilitation for individuals with hemiplegia. SMAEXO provides active assistance at the hip and knee, combined with a passive, flexible ankle joint to prevent foot drop, ensuring comprehensive support throughout the gait cycle. Its innovative design optimizes reaction force support and weight distribution, promoting balance and reducing strain on the affected side.

Simulating Safe Bite Transfer in Robot-Assisted Feeding with a Soft Head and Articulated Jaw.

Ensuring safe and comfortable bite transfer during robot-assisted feeding is challenging due to the close physical human-robot interaction required. This paper presents a novel approach to modeling physical human-robot interaction in a physics-based simulator (MuJoCo) using soft-body dynamics. We integrate a flexible head model with a rigid skeleton while accounting for internal dynamics, enabling the flexible model to be actuated by the skeleton.

Establishing normative pinch and grip strengths across adult age groups in Singapore.

Background: Pinch and grip strengths are vital indicators of upper limb function, musculoskeletal health, and general health. While most research has focused on older individuals, it is crucial to build normative data for younger populations. This cross-sectional study was conducted to determine the normative values for lateral pinch strength (LPS) and hand grip strength (HGS) in healthy adult Singaporeans.

Relearning Upper Limb Proprioception After Stroke Through Robotic Therapy: A Feasibility Analysis.

Motor learning can occur through active reaching with the arm hidden from view, leading to improvements in somatosensory acuity and modulation of functional connectivity in sensorimotor and reward networks. In this proof-of-principle study, we assess if the same paradigm benefits stroke survivors using a compact end-effector robot with integrated gaming elements. Nine community-dwelling chronic hemiplegic stroke survivors with persistent somatosensory deficits participated in 15 training sessions, each lasting 1 h.

Towards Clinical Application of Enhanced Timed Up and Go with Markerless Motion Capture and Machine Learning for Balance and Gait Assessment.

Balance and gait impairments play a key role in falls among the elderly. Traditional clinical scales such as the Berg Balance Scale (BBS) to assess fall risk are often subjective, time consuming, and does not assess gait performance. Shorter assessments such as Timed Up and Go (TUG) are available, but most clinicians only look into the completion time.

Real-time isolation of physiological tremor using recursive singular spectrum analysis and random vector functional link for surgical robotics.

Hand-held robotic instruments enhance precision in microsurgery by mitigating physiological tremor in real time. Current tremor filtering algorithms in these instruments often employ nonlinear phase prefilters to isolate the tremor signal. However, these filters introduce phase distortion in the filtered tremor, compromising accuracy.

Multi-Camera Calibration Using Far-Range Dual-LED Wand and Near-Range Chessboard Fused in Bundle Adjustment.

This paper presents a calibration approach for multiple synchronized global-shutter RGB cameras surrounding a large capture volume for 3D application. The calibration approach uses an active wand with two LED-embedded markers waved manually within the target capture volume. Data from the waving wand are combined with chessboard images taken at close range during each camera's intrinsic calibration, optimizing camera parameters via our proposed bundle adjustment method.

Biomechanical differences of Asian knee osteoarthritis patients during standing and walking using statistical parametric mapping: A cross-sectional study.

Background: Biomechanics of knee osteoarthritis (KOA) patients have been extensively studied using motion capture systems, but less have explored standing knee joint angles with the walking parameters, particularly in Asians. We aim to determine gait biomechanical differences between healthy and KOA participants in an Asian population using One-dimensional Statistical Parametric Mapping (SPM1D) and explore if they are associated with standing joint angles.

Methods: A total of 20 KOA and 24 healthy stood upright and walked 10 m at self-selected speeds.

ExTraCT - Explainable trajectory corrections for language-based human-robot interaction using textual feature descriptions.

Introduction: In human-robot interaction (HRI), understanding human intent is crucial for robots to perform tasks that align with user preferences. Traditional methods that aim to modify robot trajectories based on language corrections often require extensive training to generalize across diverse objects, initial trajectories, and scenarios. This work presents ExTraCT, a modular framework designed to modify robot trajectories (and behaviour) using natural language input.

Anatomical-Marker-Driven 3D Markerless Human Motion Capture.

Marker-based motion capture (mocap) is a conventional method used in biomechanics research to precisely analyze human movement. However, the time-consuming marker placement process and extensive post-processing limit its wider adoption. Therefore, markerless mocap systems that use deep learning to estimate 2D keypoint from images have emerged as a promising alternative, but annotation errors in training datasets used by deep learning models can affect estimation accuracy.

Wireless Pressure Sensor Array Module for Sensorized Object.

To complement rehabilitation assessments that involve hand-object interaction with additional information on the grasping parameters, we sensorized an object with a pressure sensor array module that can generate a pressure distribution map. The module can be customized for cylindrical and cuboid objects with up to 1024 sensing elements and it supports the efficient transfer of data wirelessly at more than 30 Hz. Although the module uses inexpensive materials, it is sensitive to changes in pressure distribution.

Real-time Tracking of Handheld Object from Color or Depth Images.

Object tracking during rehabilitation could help a therapist to evaluate a patient's movement and progress. Hence, we present an image-based method for real-time tracking of handheld objects due to its ease of use and availability of color or depth cameras. We use an efficient projective point correspondence method and generalize the use of precomputed spare viewpoint information to allow real-time tracking of a rigid object.

Adaptive Gravity Compensation Framework Based on Human Upper Limb Model for Assistive Robotic Arm Extender.

The Assistive Robotic Arm Extender (ARAE) is an upper limb assistive and rehabilitation robot that belongs to the end-effector type, enabling it to assist patients with upper limb movement disorders in three-dimensional space. However, the problem of gravity compensation for the human upper limb with this type of robot is crucial, which directly affects the deployment of the robot in the assistive or rehabilitation field. This paper presents an adaptive gravity compensation framework that calculates the compensated force based on the estimated human posture in 3D space.

Creation and Evaluation of Human Models with Varied Walking Ability from Motion Capture for Assistive Device Development.

As the world ages, rehabilitation and assistive devices will play a key role in improving mobility. However, designing controllers for these devices presents several challenges, from varying degrees of impairment to unique adaptation strategies of users. To use computer simulation to address these challenges, simulating human motions is required.

Safety-Based Speed Control of a Wheelchair Using Robust Adaptive Model Predictive Control.

Electric-powered wheelchairs play a vital role in ensuring accessibility for individuals with mobility impairments. The design of controllers for tracking tasks must prioritize the safety of wheelchair operation across various scenarios and for a diverse range of users. In this study, we propose a safety-oriented speed tracking control algorithm for wheelchair systems that accounts for external disturbances and uncertain parameters at the dynamic level.

Learning-Based Motion-Intention Prediction for End-Point Control of Upper-Limb-Assistive Robots.

The lack of intuitive and active human-robot interaction makes it difficult to use upper-limb-assistive devices. In this paper, we propose a novel learning-based controller that intuitively uses onset motion to predict the desired end-point position for an assistive robot. A multi-modal sensing system comprising inertial measurement units (IMUs), electromyographic (EMG) sensors, and mechanomyography (MMG) sensors was implemented.

Mobile Robotic Balance Assistant (MRBA): a gait assistive and fall intervention robot for daily living.

Background: Aging degrades the balance and locomotion ability due to frailty and pathological conditions. This demands balance rehabilitation and assistive technologies that help the affected population to regain mobility, independence, and improve their quality of life. While many overground gait rehabilitation and assistive robots exist in the market, none are designed to be used at home or in community settings.

Versatile clinical movement analysis using statistical parametric mapping in MovementRx.

Clinical gait analysis is an important biomechanics field that is often influenced by subjectivity in time-varying analysis leading to type I and II errors. Statistical Parametric Mapping can operate on all time-varying joint dynamics simultaneously, thereby overcoming subjectivity errors. We present MovementRx, the first gait analysis modelling application that correctly models the deviations of joints kinematics and kinetics both in 3 and 1 degrees of freedom; presented with easy-to-understand color maps for clinicians with limited statistical training.

A Modified Prandtl-Ishlinskii Hysteresis Model for Modeling and Compensating Asymmetric Hysteresis of Piezo-Actuated Flexure-Based Systems.

Piezo-actuated flexure-based systems are widely used in applications with high accuracy requirements, but the intrinsic hysteresis has a detrimental effect on the performance which should be compensated. Conventional models were presented to model this undesired effect using additional dead-zone operators. This paper presents a new approach using two sets of operators with a distributed compensator to model and compensate for the asymmetric system hysteresis based on inversion calculation with a simplified digitized representation.

Current clinical practice in managing somatosensory impairments and the use of technology in stroke rehabilitation.

Stroke-induced somatosensory impairments seem to be clinically overlooked, despite their prevalence and influence on motor recovery post-stroke. Interest in technology has been gaining traction over the past few decades as a promising method to facilitate stroke rehabilitation. This questionnaire-based cross-sectional study aimed to identify current clinical practice and perspectives on the management of somatosensory impairments post-stroke and the use of technology in assessing outcome measures and providing intervention.

Identification of Secondary Biomechanical Abnormalities in the Lower Limb Joints after Chronic Transtibial Amputation: A Proof-of-Concept Study Using SPM1D Analysis.

SPM is a statistical method of analysis of time-varying human movement gait signal, depending on the random field theory (RFT). MovementRx is our inhouse-developed decision-support system that depends on SPM1D Python implementation of the SPM (spm1d.org).