Assessing upper extremity motor function in practice of virtual activities of daily living

Video-based assessments of activities of daily living: generating real-world evidence in pediatric rare diseases

INTRODUCTION

Preserving function and independence to perform activities of daily living (ADL) is critical for patients and carers to manage burden of care and improve quality of life. In children living with rare diseases, video recording ADLs offer the opportunity to collect the patients' experience in a real-life setting and accurately reflect treatment effectiveness on outcomes that matter to patients and families.

AREAS COVERED

We reviewed the measurement of ADL in pediatric rare diseases and the use of video to develop at home electronic clinical outcome assessments (eCOA) by leveraging smartphone apps and artificial intelligence-based analysis. We broadly searched PubMed using Boolean combinations of the following MeSH terms "Rare Diseases, 'Quality of Life,' 'Activities of Daily Living,' 'Child,' 'Video Recording,' 'Outcome Assessment, Healthcare,' 'Intellectual disability' and 'Genetic Diseases, Inborn.' Non-controlled vocabulary was used to include human pose estimation in movement analysis.Expert opinion: Broad uptake of video eCOA in drug development is linked to the generation of technical and clinical validation evidence to confidently assess patient's functional abilities. Software platforms handling video data must align to quality regulations to ensure data integrity, security and privacy. Regulatory flexibility and optimized validation processes should facilitate video eCOA to support benefit/risk drug assessment.

Extended reality to assess post-stroke manual dexterity: contrasts between the classic box and block test, immersive virtual reality with controllers, with hand-tracking, and mixed-reality tests

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. Secondary objectives were to evaluate reliability, usability and to define arm kinematics measures.

METHODS

A sample of 21 healthy control participants (HCP) and 21 stroke individuals with hemiparesis (IHP) completed three trials of the traditional BBT, the BBT-VR-C, BBT-VR-HT and MD-MR. Content validity of the different tests were evaluated by asking five healthcare professionals to rate the difficulty of performing each test in comparison to the traditional BBT. Convergent validity was evaluated through correlations between the scores of the traditional BBT and the XR tests. Test-retest reliability was assessed through correlations between the second and third trial and usability was assessed using the System Usability Scale (SUS). Lastly, upper limb movement smoothness (SPARC) was compared between IHP and HCP for both BBT-VR test versions.

RESULTS

For content validity, healthcare professionals rated the BBT-VR-HT (0[0-1]) and BBT-MR (0[0-1]) as equally difficult to the traditional BBT, whereas they rated BBT-VR-C as more difficult than the traditional BBT (1[0-2]). For IHP convergent validity, the Pearson tests demonstrated larger correlations between the scores of BBT and BBT-VR-HT (r = 0.94;p < 0.001), and BBT and MD-MR (r = 0.95;p < 0.001) than BBT and BBT-VR-C (r = 0.65;p = 0.001). BBT-VR-HT and MD-MR usability were both rated as excellent, with median SUS scores of 83[57.5-91.3] and 83[53.8-92.5] respectively. Excellent reliability was found for the BBT-VR-C (ICC = 0.96;p < 0.001), BBT-VR-HT (ICC = 0.96;p < 0.001) and BBT-MR (ICC = 0.99;p < 0.001). The usability of the BBT-VR-C was rated as good with a median SUS of 70[43.8-83.8]. Upper limb movements of HCP were significantly smoother than for IHP when completing either the BBT-VR-C (t = 2.05;p = 0.043) and the BBT-VR-HT (t = 5.21;p < 0.001).

CONCLUSION

The different XR manual tests are valid, short-term reliable and usable tools to assess post-stroke manual dexterity.

TRIAL REGISTRATION

https://clinicaltrials.gov/ct2/show/NCT04694833 ; Unique identifier: NCT04694833, Date of registration: 11/24/2020.

A Machine Learning App for Monitoring Physical Therapy at Home

Shoulder rehabilitation is a process that requires physical therapy sessions to recover the mobility of the affected limbs. However, these sessions are often limited by the availability and cost of specialized technicians, as well as the patient's travel to the session locations. This paper presents a novel smartphone-based approach using a pose estimation algorithm to evaluate the quality of the movements and provide feedback, allowing patients to perform autonomous recovery sessions. This paper reviews the state of the art in wearable devices and camera-based systems for human body detection and rehabilitation support and describes the system developed, which uses MediaPipe to extract the coordinates of 33 key points on the patient's body and compares them with reference videos made by professional physiotherapists using cosine similarity and dynamic time warping. This paper also presents a clinical study that uses QTM, an optoelectronic system for motion capture, to validate the methods used by the smartphone application. The results show that there are statistically significant differences between the three methods for different exercises, highlighting the importance of selecting an appropriate method for specific exercises. This paper discusses the implications and limitations of the findings and suggests directions for future research.

Ecologically valid virtual reality-based technologies for assessment and rehabilitation of acquired brain injury: a systematic review

Purpose

A systematic review was conducted to examine the state of the literature regarding using ecologically valid virtual environments and related technologies to assess and rehabilitate people with Acquired Brain Injury (ABI).

Materials and methods

A literature search was performed following the PRISMA guidelines using PubMed, Web of Science, ACM and IEEE databases. The focus was on assessment and intervention studies using ecologically valid virtual environments (VE). All studies were included if they involved individuals with ABI and simulated environments of the real world or Activities of Daily Living (ADL).

Results

Seventy out of 363 studies were included in this review and grouped and analyzed according to the nature of its simulation, prefacing a total of 12 kitchens, 11 supermarkets, 10 shopping malls, 16 streets, 11 cities, and 10 other everyday life scenarios. These VE were mostly presented on computer screens, HMD's and laptops and patients interacted with them primarily via mouse, keyboard, and joystick. Twenty-five out of 70 studies had a non-experimental design.

Conclusion

Evidence about the clinical impact of ecologically valid VE is still modest, and further research with more extensive samples is needed. It is important to standardize neuropsychological and motor outcome measures to strengthen conclusions between studies.

Systematic review registration

identifier CRD42022301560, https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=301560.

Telehealth-Guided Virtual Reality for Recovery of Upper Extremity Function Following Stroke

This rater-blinded, randomized control trial (RCT) investigated the effectiveness of a Glove Rehabilitation Application for Stroke Patients (GRASP) virtual reality home exercise program (HEP) for upper extremity (UE) motor recovery following stroke. The GRASP system facilitates the use of the affected UE in simulated instrumental activities of daily living (IADLs). Participants were asked to use the system at home in asynchronous telehealth sessions 4 times per week over 8 weeks. A non-blinded occupational therapist (OT) provided synchronous telehealth visits biweekly. Analysis comparing pre- and post-assessment results for the Fugl-Meyer UE assessment (FMUE) shows a clinically important and statistically significant between-group difference for participants completing the GRASP HEP protocol compared with usual and customary care controls. Statistically significant and clinically important differences were also found in Motor Activity Log (MAL) scores. This evidence provides support for the effectiveness of home-based, IADL-focused, virtual reality therapy with telehealth support.

Concurrent Validity of Measures of Upper Extremity Function Derived from Videogame-Based Motion Capture for Children with Hemiplegia

Objective: Pediatric hemiplegia is associated with wide-ranging deficits in arm and hand motor function, neg-atively impacting participation in daily occupations and quality of life. This study investigated whether performance measures generated during therapy videogame play by children with hemiplegia can be valid indicators of upper extremity motor function. Materials and Methods: Ten children with hemiplegia used a custom therapy game system alternatively using their affected and non-affected hand to provide motion capture data that spans a wide range of motor function status. The children also completed a series of standardized outcome measure assessments with each hand, including the Quality of Upper Extremity Skills Test, the Jebsen Taylor Hand Function Test, and the Wolf Motor Function Test. Results: Statistical analysis using the nonparametric Spearman rank correlation revealed high and significant correlation between videogame-derived motion capture measures, characterizing the speed and smoothness of movements, and the standardized outcome measure assessments. Conclusion: The results suggest that a low-cost motion capture system can be used to monitor a child's motor function status and progress during a therapy program.

Digital Devices for Assessing Motor Functions in Mobility-Impaired and Healthy Populations: Systematic Literature Review

Background

With the advent of smart sensing technology, mobile and wearable devices can provide continuous and objective monitoring and assessment of motor function outcomes.

Objective

We aimed to describe the existing scientific literature on wearable and mobile technologies that are being used or tested for assessing motor functions in mobility-impaired and healthy adults and to evaluate the degree to which these devices provide clinically valid measures of motor function in these populations.

Methods

A systematic literature review was conducted by searching Embase, MEDLINE, CENTRAL (January 1, 2015, to June 24, 2020), the United States and European Union clinical trial registries, and the United States Food and Drug Administration website using predefined study selection criteria. Study selection, data extraction, and quality assessment were performed by 2 independent reviewers.

Results

A total of 91 publications representing 87 unique studies were included. The most represented clinical conditions were Parkinson disease (n=51 studies), followed by stroke (n=5), Huntington disease (n=5), and multiple sclerosis (n=2). A total of 42 motion-detecting devices were identified, and the majority (n=27, 64%) were created for the purpose of health care–related data collection, although approximately 25% were personal electronic devices (eg, smartphones and watches) and 11% were entertainment consoles (eg, Microsoft Kinect or Xbox and Nintendo Wii). The primary motion outcomes were related to gait (n=30), gross motor movements (n=25), and fine motor movements (n=23). As a group, sensor-derived motion data showed a mean sensitivity of 0.83 (SD 7.27), a mean specificity of 0.84 (SD 15.40), a mean accuracy of 0.90 (SD 5.87) in discriminating between diseased individuals and healthy controls, and a mean Pearson r validity coefficient of 0.52 (SD 0.22) relative to clinical measures. We did not find significant differences in the degree of validity between in-laboratory and at-home sensor-based assessments nor between device class (ie, health care–related device, personal electronic devices, and entertainment consoles).

Conclusions

Sensor-derived motion data can be leveraged to classify and quantify disease status for a variety of neurological conditions. However, most of the recent research on digital clinical measures is derived from proof-of-concept studies with considerable variation in methodological approaches, and much of the reviewed literature has focused on clinical validation, with less than one-quarter of the studies performing analytical validation. Overall, future research is crucially needed to further consolidate that sensor-derived motion data may lead to the development of robust and transformative digital measurements intended to predict, diagnose, and quantify neurological disease state and its longitudinal change.

Recognition and Analysis of an Age-Friendly Intelligent Sofa Design Based on Skeletal Key-Points

The aging population has a higher level of consumption willingness, higher quality of life demands, and more diversified spiritual pursuits. In recent years, age-friendly industries have entered a 'blue ocean of development'; intelligent recreation and age-friendly industries have become new growth points in the double-cycle situation; however, the current generalized design of the market is not enough to meet the needs of its elderly users. Through an extensive research and demand analysis focused on the highly-frequent use of sofas by elderly individuals, an AHP analysis showed that smart sofa design guidelines are among the most important functional indicators; user 'pain points' focused on low seat surfaces caused by the difficulty in getting up. To further refine this action behavior, a Kinect-based experimental device was used to capture the behavior of the elderly user during the sit-to-stand transition. The experimental data were collected from 25 key skeletal points in the human body and further investigated by converting the skeletal points into 12 key joint angles to refine the joint transition threshold risk during the sit-to-stand transition for the elderly user. The test results show that the most important joint angle affecting the sit-to-stand transition process is the trunk thigh angle was θ5-2, with an important value of 0.122. The two-dimensional body data of the elderly user was mapped to the joint angles under the three-dimensional activity threshold to build a comfort model of the elderly user's sofa, providing a theoretical basis for the design parameters of the aging sofa. In response to the research results, an intelligent age-friendly sofa with three forms was designed and prototyped independently, meeting the universal size of elderly users in terms of dimensional parameters, and iterating leisure and assisted standing transformation in terms of function (to reduce the risk levels of the sitting and standing transformations of elderly users).

Quantitative Assessment of Hand Motor Function for Post-Stroke Rehabilitation Based on HAGCN and Multimodality Fusion

Quantitative assessment of hand function can assist therapists in providing appropriate rehabilitation strategies, which plays an essential role in post-stroke rehabilitation. Conventionally, the assessment process relies heavily on clinical experience and lacks quantitative analysis. To quantitatively assess the hand motor function of patients with post-stroke hemiplegia, this study proposes a novel multi-modality fusion assessment framework. This framework includes three components: the kinematic feature extraction based on a graph convolutional network (HAGCN), the surface electromyography (sEMG) signal processing based on a multi-layer long short term memory (LSTM) network, and the quantitative assessment based on the multi-modality fusion. To the best of the authors' knowledge, this is the first study of applying a graph convolution network to assess the hand motor function. We also collect the kinematic data and sEMG data from 70 subjects who completed 28 types of hand movements. Therapists first graded patients using traditional motor assessment scales (Brunnstrom Scale and Fugl-Meyer Assessment Scale) and further refined the patient's motor assessment result by their experience. Then, we trained the HAGCN and LSTM networks and quantitatively assessed each patient based on the proposed assessment framework. Finally, the Spearman correlation coefficient (SC) between the assessment result of this study and the traditional scale are 0.908 and 0.967, demonstrating a significant correlation between the proposed assessment and the traditional scale scores. In addition, the SC value between the score of this study and the refined hand motor function is 0.997, indicating the "ceiling effect" of some traditional scales can be avoided.

Using Medical Device Standards for Design and Risk Management of Immersive Virtual Reality for At-Home Therapy and Remote Patient Monitoring

Numerous virtual reality (VR) systems have received regulatory clearance as therapeutic medical devices for in-clinic and at-home use. These systems enable remote patient monitoring of clinician-prescribed rehabilitation exercises, although most of these systems are nonimmersive. With the expanding availability of affordable and easy-to-use head-mounted display (HMD)-based VR, there is growing interest in immersive VR therapies. However, HMD-based VR presents unique risks. Following standards for medical device development, the objective of this paper is to demonstrate a risk management process for a generic immersive VR system for remote patient monitoring of at-home therapy. Regulations, standards, and guidance documents applicable to therapeutic VR design are reviewed to provide necessary background. Generic requirements for an immersive VR system for home use and remote patient monitoring are identified using predicate analysis and specified for both patients and clinicians using user stories. To analyze risk, failure modes and effects analysis, adapted for medical device risk management, is performed on the generic user stories and a set of risk control measures is proposed. Many therapeutic applications of VR would be regulated as a medical device if they were to be commercially marketed. Understanding relevant standards for design and risk management early in the development process can help expedite the availability of innovative VR therapies that are safe and effective.

A comparison of two personalization and adaptive cognitive rehabilitation approaches: a randomized controlled trial with chronic stroke patients

BACKGROUND

Paper-and-pencil tasks are still widely used for cognitive rehabilitation despite the proliferation of new computer-based methods, like VR-based simulations of ADL's. Studies have established construct validity of VR assessment tools with their paper-and-pencil version by demonstrating significant associations with their traditional construct-driven measures. However, VR rehabilitation intervention tools are mostly developed to include mechanisms such as personalization and adaptation, elements that are disregarded in their paper-and-pencil counterparts, which is a strong limitation of comparison studies. Here we compare the clinical impact of a personalized and adapted paper-and-pencil training and a content equivalent and more ecologically valid VR-based ADL's simulation.

METHODS

We have performed a trial with 36 stroke patients comparing Reh@City v2.0 (adaptive cognitive training through everyday tasks VR simulations) with Task Generator (TG: content equivalent and adaptive paper-and-pencil training). The intervention comprised 12 sessions, with a neuropsychological assessment pre, post-intervention and follow-up, having as primary outcomes: general cognitive functioning (assessed by the Montreal Cognitive Assessment - MoCA), attention, memory, executive functions and language specific domains.

RESULTS

A within-group analysis revealed that the Reh@City v2.0 improved general cognitive functioning, attention, visuospatial ability and executive functions. These improvements generalized to verbal memory, processing speed and self-perceived cognitive deficits specific assessments. TG only improved in orientation domain on the MoCA, and specific processing speed and verbal memory outcomes. However, at follow-up, processing speed and verbal memory improvements were maintained, and a new one was revealed in language. A between-groups analysis revealed Reh@City v2.0 superiority in general cognitive functioning, visuospatial ability, and executive functions on the MoCA.

CONCLUSIONS

The Reh@City v2.0 intervention with higher ecological validity revealed higher effectiveness with improvements in different cognitive domains and self-perceived cognitive deficits in everyday life, and the TG intervention retained fewer cognitive gains for longer.

TRIAL REGISTRATION

The trial is registered at ClinicalTrials.gov, number NCT02857803. Registered 5 August 2016, .

Design and Analysis of Cloud Upper Limb Rehabilitation System Based on Motion Tracking for Post-Stroke Patients

In order to improve the convenience and practicability of home rehabilitation training for post-stroke patients, this paper presents a cloud-based upper limb rehabilitation system based on motion tracking. A 3-dimensional reachable workspace virtual game (3D-RWVG) was developed to achieve meaningful home rehabilitation training. Five movements were selected as the criteria for rehabilitation assessment. Analysis was undertaken of the upper limb performance parameters: relative surface area (RSA), mean velocity (MV), logarithm of dimensionless jerk (LJ) and logarithm of curvature (LC). A two-headed convolutional neural network (TCNN) model was established for the assessment. The experiment was carried out in the hospital. The results show that the RSA, MV, LC and LJ could reflect the upper limb motor function intuitively from the graphs. The accuracy of the TCNN models is 92.6%, 80%, 89.5%, 85.1% and 87.5%, respectively. A therapist could check patient training and assessment information through the cloud database and make a diagnosis. The system can realize home rehabilitation training and assessment without the supervision of a therapist, and has the potential to become an effective home rehabilitation system.

Upper Extremity Function Assessment Using a Glove Orthosis and Virtual Reality System

Hand motor control deficits following stroke can diminish the ability of patients to participate in daily activities. This study investigated the criterion validity of upper extremity (UE) performance measures automatically derived from sensor data during manual practice of simulated instrumental activities of daily living (IADLs) within a virtual environment. A commercial glove orthosis was specially instrumented with motion tracking sensors to enable patients to interact, through functional UE movements, with a computer-generated virtual world using the SaeboVR software system. Fifteen stroke patients completed four virtual IADL practice sessions, as well as a battery of gold-standard assessments of UE motor and hand function. Statistical analysis using the nonparametric Spearman rank correlation reveals high and significant correlation between virtual world-derived measures and the gold-standard assessments. The results provide evidence that performance measures generated during manual interactions with a virtual environment can provide a valid indicator of UE motor status.

Effects of robot-assisted training on upper limb functional recovery during the rehabilitation of poststroke patients

BACKGROUND

The study aims to determine the effectiveness of robot-assisted training in the recovery of stroke-affected arms using an exoskeleton robot Armeo Spring.

OBJECTIVE

To identify the effect of robot training on functional recovery of the arm.

METHODS

A total of 34 stroke patients were divided into either an experimental group (EG; n= 17) or a control group (n= 17). EG was also trained to use the Armeo Spring during occupational therapy. Both groups were clinically assessed before and after treatment. Statistical comparison methods (i.e. one-tailed t-tests for differences between two independent means and the simplest test) were conducted to compare motor recovery using robot-assisted training or conventional therapy.

RESULTS

Patients assigned to the EG showed a statistically significant improvement in upper extremity motor function when compared to the CG by FIM (P< 0.05) and ACER (P< 0.05). The calculated treatment effect in the EG and CG was meaningful for shoulder and elbow kinematic parameters.

CONCLUSIONS

The findings show the benefits of robot therapy in two areas of functional recovery. Task-oriented robotic training in rehabilitation setting facilitates recovery not only of the motor function of the paretic arm but also of the cognitive abilities in stroke patients.

Smoothness Metrics in Complex Movement Tasks

Smoothness is a main characteristic of goal-directed human movements. The suitability of approaches quantifying movement smoothness is dependent on the analyzed signal's structure. Recently, activities of daily living (ADL) received strong interest in research on aging and neurorehabilitation. Such tasks have complex signal structures and kinematic parameters need to be adapted. In the present study we examined four different approaches to quantify movement smoothness in ADL. We tested the appropriateness of these approaches, namely the number of velocity peaks per meter (NoP), the spectral arc length (SAL), the speed metric (SM) and the log dimensionless jerk (LDJ), by comparing movement signals from eight healthy elderly (67.1a ± 7.1a) with eight healthy young (26.9a ± 2.1a) participants performing an activity of daily living (making a cup of tea). All approaches were able to identify group differences in smoothness (Cohen's d NoP = 2.53, SAL = 1.95, SM = 1.69, LDJ = 4.19), three revealed high to very high sensitivity (z-scores: NoP = 1.96 ± 0.55, SAL = 1.60 ± 0.64, SM = 3.41 ± 3.03, LDJ = 5.28 ± 1.52), three showed low within-group variance (NoP = 0.72, SAL = 0.60, SM = 0.11, LDJ = 0.71), two showed strong correlations between the first and the second half of the task execution (intra-trial R2s: NoP = 0.22 n.s., SAL = 0.33, SM = 0.36, LDJ = 0.91), and one was independent of other kinematic parameters (SM), while three showed strong models of multiple linear regression (R2s: NoP = 0.61, SAL = 0.48, LDJ = 0.70). Based on our results we make suggestion toward use examined smoothness measures. In total the log dimensionless jerk proved to be the most appropriate in ADL, as long as trial durations are controlled.

Analysis and Quantification of Repetitive Motion in Long-Term Rehabilitation

Objective assessment in long-term rehabilitation under real-life recording conditions is a challenging task. We propose a data-driven method to evaluate changes in motor function under uncontrolled, long-term conditions with the low-cost Microsoft Kinect sensor. Instead of using human ratings as ground truth data, we propose kinematic features of hand motion, healthy reference trajectories derived by principal component regression, and methods taken from machine learning to analyze the progression of motor function. We demonstrate the capability of this approach on datasets with repetitive unrestrained bi-manual drumming movements in three-dimensional space of stroke survivors, patients suffering of Parkinson's disease, and a healthy control group. We present processing steps to eliminate the influence of varying recording setups under real-life conditions and offer visualization methods to support clinicians in the evaluation of treatment effects.

Modifying Kinect placement to improve upper limb joint angle measurement accuracy

STUDY DESIGN

Repeated measures.

INTRODUCTION

The Kinect (Microsoft, Redmond, WA) is widely used for telerehabilitation applications including rehabilitation games and assessment.

PURPOSE OF THE STUDY

To determine effects of the Kinect location relative to a person on measurement accuracy of upper limb joint angles.

METHODS

Kinect error was computed as difference in the upper limb joint range of motion (ROM) during target reaching motion, from the Kinect vs 3D Investigator Motion Capture System (NDI, Waterloo, Ontario, Canada), and compared across 9 Kinect locations.

RESULTS

The ROM error was the least when the Kinect was elevated 45° in front of the subject, tilted toward the subject. This error was 54% less than the conventional location in front of a person without elevation and tilting. The ROM error was the largest when the Kinect was located 60° contralateral to the moving arm, at the shoulder height, facing the subject. The ROM error was the least for the shoulder elevation and largest for the wrist angle.

DISCUSSION

Accuracy of the Kinect sensor for detecting upper limb joint ROM depends on its location relative to a person.

CONCLUSION

This information facilitates implementation of Kinect-based upper limb rehabilitation applications with adequate accuracy.

LEVEL OF EVIDENCE

3b.

The impact of positive, negative and neutral stimuli in a virtual reality cognitive-motor rehabilitation task: a pilot study with stroke patients

Background

Virtual Reality (VR) based methods for stroke rehabilitation have mainly focused on motor rehabilitation, but there is increasing interest in integrating motor and cognitive training to increase similarity to real-world settings. Unfortunately, more research is needed for the definition of which type of content should be used in the design of these tools. One possibility is the use of emotional stimuli, which are known to enhance attentional processes. According to the Socioemotional Selectivity Theory, as people age, the emotional salience arises for positive and neutral, but not for negative stimuli.

Methods

For this study we developed a cognitive-motor VR task involving attention and short-term memory, and we investigated the impact of using emotional images of varying valence. The task consisted of finding a target image, shown for only two seconds, among fourteen neutral distractors, and selecting it through arm movements. After performing the VR task, a recall task took place and the patients had to identify the target images among a valence-matched number of distractors. Ten stroke patients participated in a within-subjects experiment with three conditions based on the valence of the images: positive, negative and neutral. Eye movements were recorded during VR task performance with an eye tracking system.

Results

Our results show decreased attention for negative stimuli in the VR task performance when compared to neutral stimuli. The recall task shows significantly more wrongly identified images (false memories) for negative stimuli than for neutral. Regression and correlation analyses with the Montreal Cognitive Assessment and the Geriatric Depression Scale revealed differential effects of cognitive function and depressive symptomatology in the encoding and recall of positive, negative and neutral images. Further, eye movement data shows reduced search patterns for wrongly selected stimuli containing emotional content.

Conclusions

The results of this study suggest that it is feasible to use emotional content in a VR based cognitive-motor task for attention and memory training after stroke. Stroke survivors showed less attention towards negative information, exhibiting reduced visual search patterns and more false memories. We have also shown that the use of emotional stimuli in a VR task can provide additional information regarding patient’s mood and cognitive status.

Upper Extremity Functional Evaluation by Fugl-Meyer Assessment Scoring Using Depth-Sensing Camera in Hemiplegic Stroke Patients

Virtual home-based rehabilitation is an emerging area in stroke rehabilitation. Functional assessment tools are essential to monitor recovery and provide current function-based rehabilitation. We developed the Fugl-Meyer Assessment (FMA) tool using Kinect (Microsoft, USA) and validated it for hemiplegic stroke patients. Forty-one patients with hemiplegic stroke were enrolled. Thirteen of 33 items were selected for upper extremity motor FMA. One occupational therapist assessed the motor FMA while recording upper extremity motion with Kinect. FMA score was calculated using principal component analysis and artificial neural network learning from the saved motion data. The degree of jerky motion was also transformed to jerky scores. Prediction accuracy for each of the 13 items and correlations between real FMA scores and scores using Kinect were analyzed. Prediction accuracies ranged from 65% to 87% in each item and exceeded 70% for 9 items. Correlations were high for the summed score for the 13 items between real FMA scores and scores obtained using Kinect (Pearson’s correlation coefficient = 0.873, P<0.0001) and those between total upper extremity scores (66 in full score) and scores using Kinect (26 in full score) (Pearson’s correlation coefficient = 0.799, P<0.0001). Log transformed jerky scores were significantly higher in the hemiplegic side (1.81 ± 0.76) compared to non-hemiplegic side (1.21 ± 0.43) and showed significant negative correlations with Brunnstrom stage (3 to 6; Spearman correlation coefficient = -0.387, P = 0.046). FMA using Kinect is a valid way to assess upper extremity function and can provide additional results for movement quality in stroke patients. This may be useful in the setting of unsupervised home-based rehabilitation.

Testing the concurrent validity of a naturalistic upper extremity reaching task

Point-to-point reaching has been widely used to study upper extremity motor control. We have been developing a naturalistic reaching task that adds tool manipulation and object transport to this established paradigm. The purpose of this study was to determine the concurrent validity of a naturalistic reaching task in a sample of healthy adults. This task was compared to the criterion measure of standard point-to-point reaching. Twenty-eight adults performed unconstrained out-and-back movements in three different directions relative to constant start location along midline using their nondominant arm. In the naturalistic task, participants manipulated a tool to transport objects sequentially between physical targets anchored to the planar workspace. In the standard task, participants moved a digital cursor sequentially between virtual targets, veridical to the planar workspace. In both tasks, the primary measure of performance was trial time, which indicated the time to complete 15 reaches (five cycles of three reaches/target). Two other comparator tasks were also designed to test concurrent validity when components of the naturalistic task were added to the standard task. Spearman's rank correlation coefficients indicated minimal relationship between the naturalistic and standard tasks due to differences in progressive task difficulty. Accounting for this yielded a moderate linear relationship, indicating concurrent validity. The comparator tasks were also related to both the standard and naturalistic task. Thus, the principles of motor control and learning that have been established by the wealth of point-to-point reaching studies can still be applied to the naturalistic task to a certain extent.

A Review on Technical and Clinical Impact of Microsoft Kinect on Physical Therapy and Rehabilitation

This paper reviews technical and clinical impact of the Microsoft Kinect in physical therapy and rehabilitation. It covers the studies on patients with neurological disorders including stroke, Parkinson's, cerebral palsy, and MS as well as the elderly patients. Search results in Pubmed and Google scholar reveal increasing interest in using Kinect in medical application. Relevant papers are reviewed and divided into three groups: (1) papers which evaluated Kinect's accuracy and reliability, (2) papers which used Kinect for a rehabilitation system and provided clinical evaluation involving patients, and (3) papers which proposed a Kinect-based system for rehabilitation but fell short of providing clinical validation. At last, to serve as technical comparison to help future rehabilitation design other sensors similar to Kinect are reviewed.