Journal of Neuroengineering and Rehabilitation

BACKGROUND: Incorporating instrument measurements into clinical assessments can improve the accuracy of results when assessing mobility related to activities of daily living. This can assist clinicians in making evidence-based decisions. In this context, kinematic measures are considered essential for the assessment of sensorimotor recovery after stroke. The aim of this study was to assess the validity of using an Android device to evaluate kinematic data during the performance of a standardized mobility test in people with chronic stroke and hemiparesis...

A systematic review was conducted to determine the trends in devices and parameters used for brain photobiomodulation (PBM). The revised studies included clinical and cadaveric approaches, in which light stimuli were applied to the head and/or neck. PubMed, Scopus, Web of Science and Google Scholar databases were used for the systematic search. A total of 2133 records were screened, from which 97 were included in this review. The parameters that were extracted and analysed in each article were the device design, actuation area, actuation site, wavelength, mode of operation, power density, energy density, power output, energy per session and treatment time...

BACKGROUND: Previous work has shown that ~ 50-60% of individuals have impaired proprioception after stroke. Typically, these studies have identified proprioceptive impairments using a narrow range of reference movements. While this has been important for identifying the prevalence of proprioceptive impairments, it is unknown whether these error responses are consistent for a broad range of reference movements. The objective of this study was to characterize proprioceptive accuracy as function of movement speed and distance in stroke...

BACKGROUND: Unsupervised robot-assisted rehabilitation is a promising approach to increase the dose of therapy after stroke, which may help promote sensorimotor recovery without requiring significant additional resources and manpower. However, the unsupervised use of robotic technologies is not yet a standard, as rehabilitation robots often show low usability or are considered unsafe to be used by patients independently. In this paper we explore the feasibility of unsupervised therapy with an upper limb rehabilitation robot in a clinical setting, evaluate the effect on the overall therapy dose, and assess user experience during unsupervised use of the robot and its usability...

BACKGROUND: The pendulum test is a quantitative method used to assess knee extensor spasticity in humans with spinal cord injury (SCI). Yet, the clinical implementation of this method remains limited. The goal of our study was to develop an objective and portable system to assess knee extensor spasticity during the pendulum test using inertial measurement units (IMU). METHODS: Spasticity was quantified by measuring the first swing angle (FSA) using a 3-dimensional optical tracking system (with external markers over the iliotibial band, lateral knee epicondyle, and lateral malleolus) and two wireless IMUs (positioned over the iliotibial band and mid-part of the lower leg) as well as a clinical exam (Modified Ashworth Scale, MAS)...

BACKGROUND: Non-invasive techniques such as central intermittent theta burst stimulation (iTBS) and repetitive peripheral magnetic stimulation (rPMS) have shown promise in improving motor function for patients with stroke. However, the combined efficacy of rPMS and central iTBS has not been extensively studied. This randomized controlled trial aimed to investigate the synergistic effects of rPMS and central iTBS in patients with stroke. METHOD: In this study, 28 stroke patients were randomly allocated to receive either 1200 pulses of real or sham rPMS on the radial nerve of the affected limb, followed by 1200 pulses of central iTBS on the ipsilesional hemisphere...

BACKGROUND: This research focused on the development of a motor imagery (MI) based brain-machine interface (BMI) using deep learning algorithms to control a lower-limb robotic exoskeleton. The study aimed to overcome the limitations of traditional BMI approaches by leveraging the advantages of deep learning, such as automated feature extraction and transfer learning. The experimental protocol to evaluate the BMI was designed as asynchronous, allowing subjects to perform mental tasks at their own will...

Decoding movement intentions from motor unit (MU) activities to represent neural drive information plays a central role in establishing neural interfaces, but there remains a great challenge for obtaining precise MU activities during sustained muscle contractions. In this paper, we presented an online muscle force prediction method driven by individual MU activities that were decomposed from prolonged surface electromyogram (SEMG) signals in real time. In the training stage of the proposed method, a set of separation vectors was initialized for decomposing MU activities...

We present an overview of the Conference on Transformative Opportunities for Modeling in Neurorehabilitation held in March 2023. It was supported by the Disability and Rehabilitation Engineering (DARE) program from the National Science Foundation's Engineering Biology and Health Cluster. The conference brought together experts and trainees from around the world to discuss critical questions, challenges, and opportunities at the intersection of computational modeling and neurorehabilitation to understand, optimize, and improve clinical translation of neurorehabilitation...

BACKGROUND: Knee osteoarthritis (KOA) is an irreversible degenerative disease that characterized by pain and abnormal gait. Radiography is typically used to detect KOA but has limitations. This study aimed to identify changes in plantar pressure that are associated with radiological knee osteoarthritis (ROA) and to validate them using machine learning algorithms. METHODS: This study included 92 participants with variable degrees of KOA. A modified Kellgren-Lawrence scale was used to classify participants into non-ROA and ROA groups...

BACKGROUND: Tracking gait and balance impairment in time is paramount in the care of older neurological patients. The Minimal Detectable Change (MDC), built upon the Standard Error of the Measurement (SEM), is the smallest modification of a measure exceeding the measurement error. Here, a novel method based on linear mixed-effects models (LMMs) is applied to estimate the standard error of the measurement from data collected before and after rehabilitation and calculate the MDC of gait and balance measures...

BACKGROUND: Conventional diagnostic methods for dysphagia have limitations such as long wait times, radiation risks, and restricted evaluation. Therefore, voice-based diagnostic and monitoring technologies are required to overcome these limitations. Based on our hypothesis regarding the impact of weakened muscle strength and the presence of aspiration on vocal characteristics, this single-center, prospective study aimed to develop a machine-learning algorithm for predicting dysphagia status (normal, and aspiration) by analyzing postprandial voice limiting intake to 3 cc...

BACKGROUND: Artificial intelligence is being used for rehabilitation, including monitoring exercise compliance through sensor technology. AI classification of shoulder exercise wearing an IMU sensor has only been reported in normal (i.e. painless) subjects. To prove the feasibility of monitoring exercise compliance, we aimed to classify 11 types of shoulder rehabilitation exercises using an AI (artificial intelligence) algorithm in patients with shoulder pain. We had the patients wear an IMU-based sensor, collected data during exercise, and determined the accuracy of exercise classification...

The visual system and associated skills are of particular importance in stroke rehabilitation. The process of neuroplasticity involved in restoring cognitive function during this period is mainly based on anatomical and physiological mechanisms. However, there is little evidence-based knowledge about the effects of visual skills training that could be used to improve therapeutic outcomes in cognitive rehabilitation. A computerized systematic literature search was conducted in the PubMed, Medline, and Web of Science databases from 1 January 1960 to 11 Febuary 2024...

BACKGROUND: Coronavirus 2019 (COVID-19) is an epidemic condition that compromises various consequences. The goal of this study was to investigate the effect of home-based pulmonary rehabilitation on exercise capacity in patients with post COVID-19 syndrome. METHODS: The study was designed as a randomized control trial. A total of sixty-eight patients with post COVID-19 syndrome complaining of fatigue, dyspnea, and exercise intolerance participated in this study...

BACKGROUND: Effective stroke rehabilitation requires high-dose, repetitive-task training, especially during the early recovery phase. However, the usability of upper-limb rehabilitation technology in acute and subacute stroke survivors remains relatively unexplored. In this study, we introduce subacute stroke survivors to MyoGuide, a mobile training platform that employs surface electromyography (sEMG)-guided neurofeedback training that specifically targets wrist extension. Notably, the study emphasizes evaluating the platform's usability within clinical contexts...

BACKGROUND: Temporal interference (TI) stimulation, an innovative non-invasive brain stimulation technique, has the potential to activate neurons in deep brain regions. The objective of this study was to evaluate the effects of repetitive TI stimulation targeting the lower limb motor control area (i.e., the M1 leg area) on lower limb motor function in healthy individuals, which could provide evidence for further translational application of non-invasive deep brain stimulation. METHODS: In this randomized, double-blinded, parallel-controlled trial, 46 healthy male adults were randomly divided into the TI or sham group...

BACKGROUND: Children with unilateral cerebral palsy (UCP) are encouraged to participate in the regular school curriculum. However, even when using the less-affected hand for handwriting, children with UCP still experience handwriting difficulties. Visual-motor integration (VMI) is a predictor of handwriting quality. Investigating VMI in children with UCP is important but still lacking. Conventional paper-based VMI assessments is subjective and use all-or-nothing scoring procedures, which may compromise the fidelity of VMI assessments...

BACKGROUND: Recent technological advancements present promising opportunities to enhance the frequency and objectivity of functional assessments, aligning with recent stroke rehabilitation guidelines. Within this framework, we designed and adapted different manual dexterity tests in extended reality (XR), using immersive virtual reality (VR) with controllers (BBT-VR-C), immersive VR with hand-tracking (BBT-VR-HT), and mixed-reality (MD-MR). OBJECTIVE: This study primarily aimed to assess and compare the validity of the BBT-VR-C, BBT-VR-HT and MD-MR to assess post-stroke manual dexterity...

BACKGROUND: Persons with a transfemoral amputation (TFA) often experience difficulties in daily-life ambulation, including an asymmetrical and less stable gait pattern and a greater cognitive demand of walking. However, it remains unclear whether this is effected by the prosthetic suspension, as eliminating the non-rigid prosthetic connection may influence stability and cortical activity during walking. Spatiotemporal and stability-related gait parameters, as well as cortical activity during walking, were evaluated between highly active individuals (MFC-level K3-4) with a TFA and able-bodied (AB) persons, and between persons with a bone-anchored prosthesis (BAP) and those with a socket-suspended prosthesis (SSP)...