Quantification of upper limb position sense using an exoskeleton and a virtual reality display

A Study on the Effectiveness of VR Rehabilitation Training Content for Older Individuals with Total Knee Replacement: Pilot Study

There is a paucity of research applying fully immersive virtual reality (VR) training to older adults with degenerative joint disease. This study investigated the effects of a training program utilizing fully immersive VR games on proprioception and gait ability in older patients with degenerative arthritis who had undergone total knee arthroplasty. This randomized controlled trial enrolled patients aged ≥65 years who were diagnosed with knee joint arthritis and had undergone knee arthroplasty followed by physical therapy. Participants were randomly assigned to an experimental group (receiving training using fully immersive VR games along with regular physical therapy) and a control group (receiving only regular physical therapy). The intervention was conducted five times a week for four weeks. Knee joint proprioception was measured using Biodex before and after the intervention. Spatial-temporal gait variables were collected using OptoGait for gait assessment. There was a significant decrease in the absolute error values of proprioception after the intervention in the experimental group, compared to before (p < 0.05), indicating improvement in proprioception. Gait speed, step count, and stride length improved significantly (p < 0.05, p < 0.01), demonstrating an enhancement in gait ability. The experimental group showed significantly greater improvements in gait speed, step count, and stride length than the control group (p < 0.01). Training using a fully immersive VR exercise program may have potential benefits for improving proprioception and gait parameters in patients who have undergone total knee arthroplasty. Fully immersive VR game-based training can be utilized as an effective rehabilitation intervention for patients undergoing knee arthroplasty in the future.

Assessment of joint position sense in active and passive modes with various elbow flexion angles and movement speeds using an isokinetic dynamometer

BACKGROUND

Joint position sense is the ability to detect body segment position in space and is commonly used to represent proprioceptive performance. The isokinetic dynamometer is frequently used to evaluate elbow joint position sense during active and passive reproduction tasks with various testing protocols. However, few studies have reported the performance of joint position sense under different testing conditions.

OBJECTIVE

To compare elbow joint position sense between active and passive reproduction tasks under different matching speeds and reference targets.

DESIGN

A cross-sectional study.

METHODS

Twenty participants without a history of upper-extremity surgery or neuromuscular diseases that affect the joint position sense of the elbow. Active and passive ipsilateral matching tasks were performed at four movement speeds (0.5°/s, 1°/s, 2°/s, and 4°/s) and three reference targets (elbow flexion at 0°-15°, 45°-60°, and 75°-90°), using an isokinetic dynamometer. The absolute and variable errors of each condition were calculated for comparison.

RESULTS

In active matching task with elbow flexion of 0°-15°, the absolute error at 0.5°/s was significantly larger than that at 2°/s and 4°/s, while the variable error at 1°/s was significantly larger than that at 2°/s. However, no differences were found at elbow flexion angles of 45°-60° and 75°-90°. Larger absolute errors were found at 4°/s with three testing angles in passive matching task.

CONCLUSIONS

This study compared the joint position sense errors under various testing conditions in the active and passive reproduction tasks. The movement speeds and target position effects should be considered during evaluation.

Impaired proprioception and magnified scaling of proprioceptive error responses in chronic stroke

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.

METHODS

Stroke (N = 25) and controls (N = 21) completed a robotic proprioception test that varied movement speed and distance. Participants mirror-matched various reference movement speeds (0.1-0.4 m/s) and distances (7.5-17.5 cm). Spatial and temporal parameters known to quantify proprioception were used to determine group differences in proprioceptive accuracy, and whether patterns of proprioceptive error were consistent across testing conditions within and across groups.

RESULTS

Overall, we found that stroke participants had impaired proprioception compared to controls. Proprioceptive errors related to tested reference movement scaled similarly to controls, but some errors showed amplified scaling (e.g., significantly overshooting or undershooting reference speed). Further, interaction effects were present for speed and distance reference combinations at the extremes of the testing distribution.

CONCLUSIONS

We found that stroke participants have impaired proprioception and that some proprioceptive errors were dependent on characteristics of the movement (e.g., speed) and that reference movements at the extremes of the testing distribution resulted in significantly larger proprioceptive errors for the stroke group. Understanding how sensory information is utilized across a broad spectrum of movements after stroke may aid design of rehabilitation programs.

Evaluation of Reliability of the Luna EMG Rehabilitation Robot to Assess Proprioception in the Upper Limbs in 102 Healthy Young Adults

BACKGROUND Proprioception, the body's ability to perceive its own position and movement, is fundamental for motor control and coordination. Reliable assessment tools are essential, particularly for conditions affecting proprioceptive function. This study aimed to evaluate the external and internal compliance of the Luna EMG -multifunction robotic device in assessing proprioception. MATERIAL AND METHODS The study involved 102 healthy students (31 men and 71 women; mean age 22.2±1.46 years), assessing proprioception using the Luna EMG for the upper limbs. Two investigators conducted measurements, which were repeated after 2 weeks under identical conditions. RESULTS Based on the identified values of the interclass correlation coefficient (ICC) (ICC=0.969-0.997), which is a key measure of agreement between 2 assessments, the study shows a high agreement of measurements both between investigators (for right hand: P=0.3484 [Exam 1]; P=1.0000 [Exam 2]; for left hand: P=0.1092 [Exam 1]; P=0.7706 [Exam 2]) and between the examinations (for right hand: 0.1127 [Investigator 1]; 0.2113 [Investigator 2]; for left hand: P=0.0087 [Investigator 1]; P=0.1466 [Investigator 2]). The Bland-Altman analysis showed very small inter-rater deviations, approximately 0.05° in the first examination for the left side and 0.04° for the right side. The highest deviation between the examinations, amounting to 0.08°, was identified for the left side. CONCLUSIONS The study shows that the Luna EMG multifunction robotic device enables a reliable evaluation of upper limb proprioception. Measurements performed using this device show high internal and external consistency in the assessment of the proprioceptive senses of the upper limb in 102 healthy young adults.

The use of machine learning and deep learning techniques to assess proprioceptive impairments of the upper limb after stroke

BACKGROUND

Robots can generate rich kinematic datasets that have the potential to provide far more insight into impairments than standard clinical ordinal scales. Determining how to define the presence or absence of impairment in individuals using kinematic data, however, can be challenging. Machine learning techniques offer a potential solution to this problem. In the present manuscript we examine proprioception in stroke survivors using a robotic arm position matching task. Proprioception is impaired in 50-60% of stroke survivors and has been associated with poorer motor recovery and longer lengths of hospital stay. We present a simple cut-off score technique for individual kinematic parameters and an overall task score to determine impairment. We then compare the ability of different machine learning (ML) techniques and the above-mentioned task score to correctly classify individuals with or without stroke based on kinematic data.

METHODS

Participants performed an Arm Position Matching (APM) task in an exoskeleton robot. The task produced 12 kinematic parameters that quantify multiple attributes of position sense. We first quantified impairment in individual parameters and an overall task score by determining if participants with stroke fell outside of the 95% cut-off score of control (normative) values. Then, we applied five machine learning algorithms (i.e., Logistic Regression, Decision Tree, Random Forest, Random Forest with Hyperparameters Tuning, and Support Vector Machine), and a deep learning algorithm (i.e., Deep Neural Network) to classify individual participants as to whether or not they had a stroke based only on kinematic parameters using a tenfold cross-validation approach.

RESULTS

We recruited 429 participants with neuroimaging-confirmed stroke (< 35 days post-stroke) and 465 healthy controls. Depending on the APM parameter, we observed that 10.9-48.4% of stroke participants were impaired, while 44% were impaired based on their overall task score. The mean performance metrics of machine learning and deep learning models were: accuracy 82.4%, precision 85.6%, recall 76.5%, and F1 score 80.6%. All machine learning and deep learning models displayed similar classification accuracy; however, the Random Forest model had the highest numerical accuracy (83%). Our models showed higher sensitivity and specificity (AUC = 0.89) in classifying individual participants than the overall task score (AUC = 0.85) based on their performance in the APM task. We also found that variability was the most important feature in classifying performance in the APM task.

CONCLUSION

Our ML models displayed similar classification performance. ML models were able to integrate more kinematic information and relationships between variables into decision making and displayed better classification performance than the overall task score. ML may help to provide insight into individual kinematic features that have previously been overlooked with respect to clinical importance.

The effects of supervised and non-supervised upper limb virtual reality exercises on upper limb sensory-motor functions in patients with idiopathic Parkinson's disease

BACKGROUND

Impairments of upper limb (UL) sensory-motor functions are common in Parkinson's disease (PD). Virtual reality exercises may improve sensory-motor functions in a safe environment and can be used in tele-rehabilitation. This study aimed to investigate the effects of supervised and non-supervised UL virtual reality exercises (ULVRE) on UL sensory-motor functions in patients with idiopathic PD.

METHODS

In this clinical trial study, 45 patients with idiopathic PD (29 male) by mean ± SD age of 58.64 ± 8.69 years were randomly allocated to either the control group (conventional rehabilitation exercises), supervised ULVRE or non-supervised ULVRE. Interventions were 24 sessions, 3 sessions/week. Before/after of interventions and follow-up period all assessment was done. Hand Active Sensation Test and Wrist Position Sense Test were used for assessing UL sensory function. Gross and fine manual dexterity were assessed by Box-Block Test and Nine-Hole Peg Test, respectively. Grip and pinch strength were evaluated by a dynamometer and pinch gauge, respectively.

RESULTS

The results showed significant improvement in discriminative sensory function (HAST-weight and HAST-total), wrist proprioception, gross manual dexterity and grip strength of both less and more affected hands as well as fine manual dexterity of the more affected hand in the three groups in patients with idiopathic PD (P < 0.05).

CONCLUSION

The results of this study indicated that both supervised and non-supervised ULVRE using the Kinect device might potentially improve some aspects of UL sensory-motor functions in patients with PD. Therefore, ULVRE using the Kinect device can be used in tele-rehabilitation, especially in the current limitations induced by the COVID-19 pandemic, for improving UL functions in patients with PD.

New technologies promoting active upper limb rehabilitation after stroke: an overview and network meta-analysis

INTRODUCTION

The primary aim of this work was to summarize and compare the effects of active rehabilitation assisted by new technologies (virtual reality [VR], robot-assisted therapy [RAT] and telerehabilitation [TR)) on upper limb motor function and everyday living activity during the subacute and chronic phases of stroke. The secondary aims were to compare the effects of these technologies according to the intervention design (in addition to or in substitution of conventional therapy), the duration of active rehabilitation and the severity of patients' motor impairments.

EVIDENCE ACQUISITION

Several databases, namely PubMed, Scopus, Embase and Cochrane Library, were searched. Studies were included if they were meta-analyses with a moderate to high level of confidence (assessed with AMSTAR-2) that compared the effects of a new technology promoting active rehabilitation to that of a conventional therapy program among patients with stroke. Network meta-analyses were conducted to compare the effects of the new technologies.

EVIDENCE SYNTHESIS

Eighteen different meta-analyses were selected and fifteen included in the quantitative analysis. In total these 15 meta-analyses were based on 189 different randomized controlled trials. VR (SMD≥0.25; P<0.05), RAT (SMD≥0.29; P≤0.29) and TR (SMD≥-0.08; P≤0.64) were found to be at least as effective as conventional therapy. During the subacute phase, RAT's greatest effect was observed for patients with severe-moderate impairments whereas VR and TR's greatest effects were observed for patients with mild impairments. During the chronic phase, the highest effects were observed for patients with mild impairments, for all studies technologies. Network meta-analyses showed that VR and RAT were both significantly superior to TR in improving motor function during the chronic phase but revealed no significant difference between VR, RAT and TR effectiveness on both motor function (during the subacute phase) and activity (during both chronic and subacute phase).

CONCLUSIONS

This overview provides low-to-moderate evidence that rehabilitation assisted with technologies are at least as effective as conventional therapy for patients with stroke. While VR and RAT seem to be more efficient during the subacute phase, all technologies seem to be as efficient as one another in the chronic phase.

Multisensory Integration in Stroke Patients: A Theoretical Approach to Reinterpret Upper-Limb Proprioceptive Deficits and Visual Compensation

For reaching and grasping, as well as for manipulating objects, optimal hand motor control arises from the integration of multiple sources of sensory information, such as proprioception and vision. For this reason, proprioceptive deficits often observed in stroke patients have a significant impact on the integrity of motor functions. The present targeted review attempts to reanalyze previous findings about proprioceptive upper-limb deficits in stroke patients, as well as their ability to compensate for these deficits using vision. Our theoretical approach is based on two concepts: first, the description of multi-sensory integration using statistical optimization models; second, on the insight that sensory information is not only encoded in the reference frame of origin (e.g., retinal and joint space for vision and proprioception, respectively), but also in higher-order sensory spaces. Combining these two concepts within a single framework appears to account for the heterogeneity of experimental findings reported in the literature. The present analysis suggests that functional upper limb post-stroke deficits could not only be due to an impairment of the proprioceptive system per se, but also due to deficiencies of cross-references processing; that is of the ability to encode proprioceptive information in a non-joint space. The distinction between purely proprioceptive or cross-reference-related deficits can account for two experimental observations: first, one and the same patient can perform differently depending on specific proprioceptive assessments; and a given behavioral assessment results in large variability across patients. The distinction between sensory and cross-reference deficits is also supported by a targeted literature review on the relation between cerebral structure and proprioceptive function. This theoretical framework has the potential to lead to a new stratification of patients with proprioceptive deficits, and may offer a novel approach to post-stroke rehabilitation.

Robotic Assessment of Wrist Proprioception During Kinaesthetic Perturbations: A Neuroergonomic Approach

Position sense refers to an aspect of proprioception crucial for motor control and learning. The onset of neurological diseases can damage such sensory afference, with consequent motor disorders dramatically reducing the associated recovery process. In regular clinical practice, assessment of proprioceptive deficits is run by means of clinical scales which do not provide quantitative measurements. However, existing robotic solutions usually do not involve multi-joint movements but are mostly applied to a single proximal or distal joint. The present work provides a testing paradigm for assessing proprioception during coordinated multi-joint distal movements and in presence of kinaesthetic perturbations: we evaluated healthy subjects' ability to match proprioceptive targets along two of the three wrist's degrees of freedom, flexion/extension and abduction/adduction. By introducing rotations along the pronation/supination axis not involved in the matching task, we tested two experimental conditions, which differed in terms of the temporal imposition of the external perturbation: in the first one, the disturbance was provided after the presentation of the proprioceptive target, while in the second one, the rotation of the pronation/ supination axis was imposed during the proprioceptive target presentation. We investigated if (i) the amplitude of the perturbation along the pronation/supination would lead to proprioceptive miscalibration; (ii) the encoding of proprioceptive target, would be influenced by the presentation sequence between the target itself and the rotational disturbance. Eighteen participants were tested by means of a haptic neuroergonomic wrist device: our findings provided evidence that the order of disturbance presentation does not alter proprioceptive acuity. Yet, a further effect has been noticed: proprioception is highly anisotropic and dependent on perturbation amplitude. Unexpectedly, the configuration of the forearm highly influences sensory feedbacks, and significantly alters subjects' performance in matching the proprioceptive targets, defining portions of the wrist workspace where kinaesthetic and proprioceptive acuity are more sensitive. This finding may suggest solutions and applications in multiple fields: from general haptics where, knowing how wrist configuration influences proprioception, might suggest new neuroergonomic solutions in device design, to clinical evaluation after neurological damage, where accurately assessing proprioceptive deficits can dramatically complement regular therapy for a better prediction of the recovery path.

Effects of an Immersive Virtual Reality Environment on Muscle Strength, Proprioception, Balance, and Gait of a Middle-Aged Woman Who Had Total Knee Replacement: A Case Report

BACKGROUND The purpose of this case study was to apply a training program using virtual reality to a middle-aged woman who had total knee replacement surgery and to investigate its effects on her muscle strength, proprioception, balance, and gait ability. CASE REPORT The subject who participated in this study was a 62-year-old woman, who had been diagnosed with moderate osteoarthritis and had a total knee replacement. Post-operative treatment consisted of virtual reality training along with range of motion exercise of the knee joint, light quadriceps isometric exercise, and conventional physical therapy. This also included thermal and electric therapy for pain control conducted on 10 occasions (5 times a week for 2 weeks). Total treatment time, which included 30 min of conventional physical therapy, was 60 min. Measurement of the subject's lower extremity muscle strength after intervention decreased to 9.43 s, and the error in proprioception decreased to 1.5°. In addition, balance score increased to 56 points, and the time taken to measure gait ability decreased to 9.87 s. CONCLUSIONS The patient responded positively to rehabilitation using virtual reality, and her muscle strength, proprioception, balance, and gait ability improved. These results suggest that the application of rehabilitative training through virtual reality for total knee replacement patients warrants further study and consideration.