Test-retest reliability of Kinect's measurements for the evaluation of upper body recovery of stroke patients

Literature review of stroke assessment for upper-extremity physical function via EEG, EMG, kinematic, and kinetic measurements and their reliability

BACKGROUND

Significant clinician training is required to mitigate the subjective nature and achieve useful reliability between measurement occasions and therapists. Previous research supports that robotic instruments can improve quantitative biomechanical assessments of the upper limb, offering reliable and more sensitive measures. Furthermore, combining kinematic and kinetic measurements with electrophysiological measurements offers new insights to unlock targeted impairment-specific therapy. This review presents common methods for analyzing biomechanical and neuromuscular data by describing their validity and reporting their reliability measures.

METHODS

This paper reviews literature (2000-2021) on sensor-based measures and metrics for upper-limb biomechanical and electrophysiological (neurological) assessment, which have been shown to correlate with clinical test outcomes for motor assessment. The search terms targeted robotic and passive devices developed for movement therapy. Journal and conference papers on stroke assessment metrics were selected using PRISMA guidelines. Intra-class correlation values of some of the metrics are recorded, along with model, type of agreement, and confidence intervals, when reported.

RESULTS

A total of 60 articles are identified. The sensor-based metrics assess various aspects of movement performance, such as smoothness, spasticity, efficiency, planning, efficacy, accuracy, coordination, range of motion, and strength. Additional metrics assess abnormal activation patterns of cortical activity and interconnections between brain regions and muscle groups; aiming to characterize differences between the population who had a stroke and the healthy population.

CONCLUSION

Range of motion, mean speed, mean distance, normal path length, spectral arc length, number of peaks, and task time metrics have all demonstrated good to excellent reliability, as well as provide a finer resolution compared to discrete clinical assessment tests. EEG power features for multiple frequency bands of interest, specifically the bands relating to slow and fast frequencies comparing affected and non-affected hemispheres, demonstrate good to excellent reliability for populations at various stages of stroke recovery. Further investigation is needed to evaluate the metrics missing reliability information. In the few studies combining biomechanical measures with neuroelectric signals, the multi-domain approaches demonstrated agreement with clinical assessments and provide further information during the relearning phase. Combining the reliable sensor-based metrics in the clinical assessment process will provide a more objective approach, relying less on therapist expertise. This paper suggests future work on analyzing the reliability of metrics to prevent biasedness and selecting the appropriate analysis.

Placement Recommendations for Single Kinect-Based Motion Capture System in Unilateral Dynamic Motion Analysis

Low-cost, portable, and easy-to-use Kinect-based systems achieved great popularity in out-of-the-lab motion analysis. The placement of a Kinect sensor significantly influences the accuracy in measuring kinematic parameters for dynamics tasks. We conducted an experiment to investigate the impact of sensor placement on the accuracy of upper limb kinematics during a typical upper limb functional task, the drinking task. Using a 3D motion capture system as the golden standard, we tested twenty-one Kinect positions with three different distances and seven orientations. Upper limb joint angles, including shoulder flexion/extension, shoulder adduction/abduction, shoulder internal/external rotation, and elbow flexion/extension angles, are calculated via our developed Kinect kinematic model and the UWA kinematic model for both the Kinect-based system and the 3D motion capture system. We extracted the angles at the point of the target achieved (PTA). The mean-absolute-error (MEA) with the standard represents the Kinect-based system's performance. We conducted a two-way repeated measure ANOVA to explore the impacts of distance and orientation on the MEAs for all upper limb angles. There is a significant main effect for orientation. The main effects for distance and the interaction effects do not reach statistical significance. The post hoc test using LSD test for orientation shows that the effect of orientation is joint-dependent and plane-dependent. For a complex task (e.g., drinking), which involves body occlusions, placing a Kinect sensor right in front of a subject is not a good choice. We suggest that place a Kinect sensor at the contralateral side of a subject with the orientation around 30∘ to 45∘ for upper limb functional tasks. For all kinds of dynamic tasks, we put forward the following recommendations for the placement of a Kinect sensor. First, set an optimal sensor position for capture, making sure that all investigated joints are visible during the whole task. Second, sensor placement should avoid body occlusion at the maximum extension. Third, if an optimal location cannot be achieved in an out-of-the-lab environment, researchers could put the Kinect sensor at an optimal orientation by trading off the factor of distance. Last, for those need to assess functions of both limbs, the users can relocate the sensor and re-evaluate the functions of the other side once they finish evaluating functions of one side of a subject.

Dissociating Sensorimotor Recovery and Compensation During Exoskeleton Training Following Stroke

The quality of arm movements typically improves in the sub-acute phase of stroke affecting the upper extremity. Here, we used whole arm kinematic analysis during reaching movements to distinguish whether these improvements are due to true recovery or to compensation. Fifty-three participants with post-acute stroke performed ∼80 reaching movement tests during 4 weeks of training with the ArmeoSpring exoskeleton. All participants showed improvements in end-effector performance, as measured by movement smoothness. Four ArmeoSpring angles, shoulder horizontal (SH) rotation, shoulder elevation (SE), elbow rotation, and forearm rotation, were recorded and analyzed. We first characterized healthy joint coordination patterns by performing a sparse principal component analysis on these four joint velocities recorded during reaching tests performed by young control participants. We found that two dominant joint correlations [SH with elbow rotation and SE with forearm rotation] explained over 95% of variance of joint velocity data. We identified two clusters of stroke participants by comparing the evolution of these two correlations in all tests. In the "Recoverer" cluster (N = 19), both joint correlations converged toward the respective correlations for control participants. Thus, Recoverers relearned how to generate smooth end-effector movements while developing joint movement patterns similar to those of control participants. In the "Compensator" cluster (N = 34), at least one of the two joint correlations diverged from the corresponding correlation of control participants. Compensators relearned how to generate smooth end-effector movements by discovering various new compensatory movement patterns dissimilar to those of control participants. New compensatory patterns included atypical decoupling of the SE and forearm joints, and atypical coupling of the SH rotation and elbow joints. There was no difference in clinical impairment level between the two groups either at the onset or at the end of training as assessed with the Upper Extremity Fugl-Meyer scale. However, at the start of training, the Recoverers showed significantly faster improvements in end-effector movement smoothness than the Compensators. Our analysis can be used to inform neurorehabilitation clinicians on how to provide movement feedback during practice and suggest avenues for refining exoskeleton robot therapy to reduce compensatory patterns.

Multiple Kinect based system to monitor and analyze key performance indicators of physical training

Using a single Kinect device for human skeleton tracking and motion tracking lacks of reliability required in sports medicine and rehabilitation domains. Human joints reconstructed from non-standard poses such as squatting, sitting and lying are asymmetric and have unnatural lengths while their recognition error exceeds the error of recognizing standard poses. In order to achieve higher accuracy and usability for practical smart health applications we propose a practical solution for human skeleton tracking and analysis that performs the fusion of skeletal data from three Kinect devices to provide a complete 3D spatial coverage of a subject. The paper describes a novel data fusion algorithm using algebraic operations in vector space, the deployment of the system using three Kinect units, provides analysis of dynamic characteristics (position of joints, speed of movement, functional working envelope, body asymmetry and the rate of fatigue) of human motion during physical exercising, and evaluates intra-session reliability of the system using test–retest reliability metrics (intra-class correlation, coefficient of variation and coefficient of determination). Comparison of multi-Kinect system vs single-Kinect system shows an improvement in accuracy of 15.7%, while intra-session reliability is rated as excellent.

Upper Limb Physical Rehabilitation Using Serious Videogames and Motion Capture Systems: A Systematic Review

The use of videogames and motion capture systems in rehabilitation contributes to the recovery of the patient. This systematic review aimed to explore the works related to these technologies. The PRISMA method (Preferred Reporting Items for Systematic reviews and Meta-Analyses) was used to search the databases Scopus, PubMed, IEEE Xplore, and Web of Science, taking into consideration four aspects: physical rehabilitation, the use of videogames, motion capture technologies, and upper limb rehabilitation. The literature selection was limited to open access works published between 2015 and 2020, obtaining 19 articles that met the inclusion criteria. The works reported the use of inertial measurement units (37%), a Kinect sensor (48%), and other technologies (15%). It was identified that 26% used commercial products, while 74% were developed independently. Another finding was that 47% of the works focus on post-stroke motor recovery. Finally, diverse studies sought to support physical rehabilitation using motion capture systems incorporating inertial units, which offer precision and accessibility at a low cost. There is a clear need to continue generating proposals that confront the challenges of rehabilitation with technologies which offer precision and healthcare coverage, and which, additionally, integrate elements that foster the patient's motivation and participation.

Depth Sensor-Based Assessment of Reachable Work Space for Visualizing and Quantifying Paretic Upper Extremity Motor Function in People With Stroke

BACKGROUND

Quantitative evaluation of upper extremity (UE) motor function is important in people with hemiparetic stroke. A depth sensor-based assessment of reachable work space (RWS) was applied to visualize and quantify paretic UE motor function.

OBJECTIVE

The objectives of this study were to examine the characteristics of RWS and to assess its validity, reliability, measurement error, and responsiveness in people with hemiparetic stroke.

DESIGN

This was a descriptive, repeated-measures, observational study.

METHODS

Fifty-eight people with stroke participated. RWS was assessed on both paretic and nonparetic UEs, and the RWS ratio was determined by dividing the RWS of the paretic UE by that of the nonparetic UE. The concurrent validity of the RWS was determined by examining the relationship with the Fugl-Meyer Assessment UE motor score. Test-retest reproducibility was examined in 40 participants. Responsiveness was determined by examining the RWS results before and after 3 weeks of intensive training of the paretic UE in 32 participants.

RESULTS

The lower area of RWS bordering shoulder was significantly larger than the upper area, and the medial-lower area of RWS bordering shoulder was significantly larger than the lateral-lower area. The RWS ratio was highly correlated with the Fugl-Meyer Assessment UE motor score (r = 0.81). The RWS ratio showed good intrarater relative reliability (intraclass correlation coefficient = 0.94) and no fixed or proportional bias. The minimal detectable change of the RWS ratio was 16.6. The responsiveness of the RWS ratio was large (standardized response mean = 0.83).

LIMITATIONS

Interexaminer reliability was not assessed.

CONCLUSIONS

The RWS assessment showed sufficient validity, reliability, and responsiveness in people with hemiparetic stroke. A depth sensor-based RWS evaluation is useful for visualizing and quantifying paretic UE motor function in the clinical setting.

An interactive motion-tracking system for home-based assessing and training reach-to-target tasks in stroke survivors-a preliminary study

Quantitative evaluation and training of the reach-to-target ability in stroke patients are needed for postdischarge rehabilitation, which can be achieved using a motion-tracking system. However, most of these systems are either costly, involve sophisticated parameter interpretation, or are not designed for rehabilitation. We developed an interactive reach-to-target assessment and training system (IRTATS) based on a camera and three marker straps to detect tracking signals. IRTATS supports audiovisual feedback, personal goal setting, and use in a small clinic or home without the internet. This study aims to evaluate the reliability, validity of IRTATS, and its measurement accuracy of the range of motion (ROM). Ninety-nine stroke patients and 20 healthy adults were recruited for the study. Kinematic variables and active joint ROM (AROM) were assessed using IRTATS. The AROM was measured by a universal goniometer, and scores from multiple clinical scales concerning motor and activity capability were calculated. Although the AROMs measured by IRTATS and the goniometer did not agree, IRTATS has clinically acceptable reliability and validity. Three variables in IRTATS could discriminate the motor performance of patients and healthy subjects. IRTATS may provide a new supplement to conventional physiotherapy in the assessment of the reach-to-target ability in stroke patients. Graphical abstract System configuration • The system is based on an infrared camera and the adjustable marker straps as a sensor module. • It is portable and compact, and has clinically acceptable reliability and validity. • It supports audiovisual feedback, personal goal setting, and use in regions without the internet. • It can be used as an adjunct to conventional physiotherapy in the assessment of the reach-to-target ability.

Analysis of Upper-Limb and Trunk Kinematic Variability: Accuracy and Reliability of an RGB-D Sensor

In the field of motion analysis, the gold standard devices are marker-based tracking systems. Despite being very accurate, their cost, stringent working environments, and long preparation time make them unsuitable for small clinics as well as for other scenarios such as industrial application. Since human-centered approaches have been promoted even outside clinical environments, the need for easy-to-use solutions to track human motion is topical. In this context, cost-effective devices, such as RGB-Depth (RBG-D) cameras have been proposed, aiming at a user-centered evaluation in rehabilitation or of workers in industry environment. In this paper, we aimed at comparing marker-based systems and RGB-D cameras for tracking human motion. We used a Vicon system (Vicon Motion Systems, Oxford, UK) as a gold standard for the analysis of accuracy and reliability of the Kinect V2 (Microsoft, Redmond, WA, USA) in a variety of gestures in the upper limb workspace—targeting rehabilitation and working applications. The comparison was performed on a group of 15 adult healthy subjects. Each subject had to perform two types of upper-limb movements (point-to-point and exploration) in three workspace sectors (central, right, and left) that might be explored in rehabilitation and industrial working scenarios. The protocol was conceived to test a wide range of the field of view of the RGB-D device. Our results, detailed in the paper, suggest that RGB-D sensors are adequate to track the upper limb for biomechanical assessments, even though relevant limitations can be found in the assessment and reliability of some specific degrees of freedom and gestures with respect to marker-based systems.

Deep Learning-Based Upper Limb Functional Assessment Using a Single Kinect v2 Sensor

We develop a deep learning refined kinematic model for accurately assessing upper limb joint angles using a single Kinect v2 sensor. We train a long short-term memory recurrent neural network using a supervised machine learning architecture to compensate for the systematic error of the Kinect kinematic model, taking a marker-based three-dimensional motion capture system (3DMC) as the golden standard. A series of upper limb functional task experiments were conducted, namely hand to the contralateral shoulder, hand to mouth or drinking, combing hair, and hand to back pocket. Our deep learning-based model significantly improves the performance of a single Kinect v2 sensor for all investigated upper limb joint angles across all functional tasks. Using a single Kinect v2 sensor, our deep learning-based model could measure shoulder and elbow flexion/extension waveforms with mean CMCs >0.93 for all tasks, shoulder adduction/abduction, and internal/external rotation waveforms with mean CMCs >0.8 for most of the tasks. The mean deviations of angles at the point of target achieved and range of motion are under 5° for all investigated joint angles during all functional tasks. Compared with the 3DMC, our presented system is easier to operate and needs less laboratory space.

Reliability and validity analyzes of Kinect V2 based measurement system for shoulder motions

Telerehabilitation systems provide some advantages against the classic rehabilitation methods. The ability of the shoulders depends on active motion range of them to do activities in daily life and to do sports. To evaluate the shoulder motions, range of motion (ROM) measurement is a basic method. Clinical goniometer and digital goniometer are the most commonly used measurement tools. However, these measurement tools have some deficiencies and difficulties. In this paper, we consider a Kinect One Sensor (Kinect V2) based measurement system for shoulder motions as an alternative method. The aim of this study is to examine the reliability and validity analyzes of the proposed shoulder measurement system. Three systems were used to evaluate validity of the Kinect V2 to measure shoulder motions: Kinect V2 based system, clinical goniometer and digital goniometer. One expert physical therapist measured shoulder abduction, flexion, external rotation, internal rotation and extension ROM values using a clinical goniometer and a digital goniometer in 40 healthy volunteers (22 males, 18 females, and 19-33 years old). All poses for each shoulder motion were captured with the Kinect V2 based system again and the ROM values were calculated. These procedures were carried out with all of the volunteer participants in three repetitions. In reliability for Kinect V2 based shoulder motion measurement system, we used the intraclass correlation coefficients (ICC), standard error of the measure (SEM), minimal detectable change (MDC). The validity test includes the 95% limits of agreement (LOA) and mean difference between the Kinect V2 based system and the both of the goniometer systems for measuring shoulder motions. The high ICC values show that the Kinect V2 based shoulder motion measurement system has very good intra-rater reliability for abduction, flexion, external rotation, internal rotation shoulder poses. For extension pose, it has good reliability result according to the ICC value. The validity analysis gives good results for all shoulder poses except internal rotation between Kinect V2 and clinical/digital goniometer. As a result, Kinect V2 based measurement system is a reliable and valid alternative telerehabilitation tool for shoulder motions.

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.

Can Kinect aid motor learning in sportsmen? A study for three standing techniques in judo

Our objective was to examine how exercises with the second generation of the Microsoft Kinect sensor may aid in the process of motor learning in young judo practitioners. We addressed improvements in spatio-temporal accuracy during execution of three standing techniques in judo, in a simple paradigm designed to study short-term practice effects. Two groups of judokas, 12 athletes each—one aided with Kinect and our dedicated software vs a group of controls—were asked to mimic previously recorded master-level performances of the three techniques, established as benchmarks by a two times world champion in judo. In five training sessions, athletes of the aided group used a virtual-reality setup in which they trained with a virtual representation of the master displayed on a large screen with a simultaneous real-time visualisation of their own movements in the form of an avatar based on body joint localisation, as determined by Kinect, which also measured their performance. The control group used Kinect in the 1st and 5th session, which was necessary for the measurements that constituted the basis for subsequent statistical comparisons, whereas the 2nd, 3rd, and 4th session in this group was guided by a coach, without the use of the Kinect setup. In addition, athletes of the two groups had unrestricted access to a video recording of the master performing the three throws. We found statistically significant improvements (p < 0.05) in the accuracy of executing the three techniques between the 1st and the 5th training session for the aided group but not for the control group. We conclude that incorporating Kinect based exercises into a judo training programme may be a useful means to supporting motor learning, therefore enhancing training efficiency, and thus improving performance.

The Clinical Utility of Virtual Reality in Neurorehabilitation: A Systematic Review

Background:

Virtual reality (VR) experiences (through games and virtual environments) are increasingly being used in physical, cognitive, and psychological interventions. However, the impact of VR as an approach to rehabilitation is not fully understood, and its advantages over traditional rehabilitation techniques are yet to be established.

Method:

We present a systematic review which was conducted according to Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA). During February and March of 2018, we conducted searches on PubMed (Medline), Virtual Health Library Search Portal databases (BVS), Web of Science (WOS), and Embase for all VR-related publications in the past 4 years (2015, 2016, 2017, and 2018). The keywords used in the search were “neurorehabilitation” AND “Virtual Reality” AND “devices.”

Results:

We summarize the literature which highlights that a range of effective VR approaches are available. Studies identified were conducted with poststroke patients, patients with cerebral palsy, spinal cord injuries, and other pathologies. Healthy populations have been used in the development and testing of VR approaches meant to be used in the future by people with neurological disorders. A range of benefits were associated with VR interventions, including improvement in motor functions, greater community participation, and improved psychological and cognitive function.

Conclusions:

The results from this review provide support for the use of VR as part of a neurorehabilitation program in maximizing recovery.

Assessment of a markerless motion analysis system for manual wheelchair application

BACKGROUND

Wheelchair biomechanics research advances accessibility and clinical care for manual wheelchair users. Standardized outcome assessments are vital tools for tracking progress, but there is a strong need for more quantitative methods. A system offering kinematic, quantitative detection, with the ease of use of a standardized outcome assessment, would be optimal for repeated, longitudinal assessment of manual wheelchair users' therapeutic progress, but has yet to be offered.

RESULTS

This work evaluates a markerless motion analysis system for manual wheelchair mobility in clinical, community, and home settings. This system includes Microsoft® Kinect® 2.0 sensors, OpenSim musculoskeletal modeling, and an automated detection, processing, and training interface. The system is designed to be cost-effective, easily used by caregivers, and capable of detecting key kinematic metrics involved in manual wheelchair propulsion. The primary technical advancements in this research are the software components necessary to detect and process the upper extremity kinematics during manual wheelchair propulsion, along with integration of the components into a complete system. The study defines and evaluates an adaptable systems methodology for processing kinematic data using motion capture technology and open-source musculoskeletal models to assess wheelchair propulsion pattern and biomechanics, and characterizes its accuracy, sensitivity and repeatability. Inter-trial repeatability of spatiotemporal parameters, joint range of motion, and musculotendon excursion were all found to be significantly correlated (p < 0.05).

CONCLUSIONS

The system is recommended for use in clinical settings for frequent wheelchair propulsion assessment, provided the limitations in precision are considered. The motion capture-model software bridge methodology could be applied in the future to any motion-capture system or specific application, broadening access to detailed kinematics while reducing assessment time and cost.

Person-Generated Health Data in Simulated Rehabilitation Using Kinect for Stroke: Literature Review

BACKGROUND

Person- or patient-generated health data (PGHD) are health, wellness, and clinical data that people generate, record, and analyze for themselves. There is potential for PGHD to improve the efficiency and effectiveness of simulated rehabilitation technologies for stroke. Simulated rehabilitation is a type of telerehabilitation that uses computer technologies and interfaces to allow the real-time simulation of rehabilitation activities or a rehabilitation environment. A leading technology for simulated rehabilitation is Microsoft's Kinect, a video-based technology that uses infrared to track a user's body movements.

OBJECTIVE

This review attempts to understand to what extent Kinect-based stroke rehabilitation systems (K-SRS) have used PGHD and to what benefit.

METHODS

The review is conducted in two parts. In part 1, aspects of relevance for PGHD were searched for in existing systematic reviews on K-SRS. The following databases were searched: IEEE Xplore, Association of Computing Machinery Digital Library, PubMed, Biomed Central, Cochrane Library, and Campbell Collaboration. In part 2, original research papers that presented or used K-SRS were reviewed in terms of (1) types of PGHD, (2) patient access to PGHD, (3) PGHD use, and (4) effects of PGHD use. The search was conducted in the same databases as part 1 except Cochrane and Campbell Collaboration. Reference lists on K-SRS of the reviews found in part 1 were also included in the search for part 2. There was no date restriction. The search was closed in June 2017. The quality of the papers was not assessed, as it was not deemed critical to understanding PGHD access and use in studies that used K-SRS.

RESULTS

In part 1, 192 papers were identified, and after assessment only 3 papers were included. Part 1 showed that previous reviews focused on technical effectiveness of K-SRS with some attention on clinical effectiveness. None of those reviews reported on home-based implementation or PGHD use. In part 2, 163 papers were identified and after assessment, 41 papers were included. Part 2 showed that there is a gap in understanding how PGHD use may affect patients using K-SRS and a lack of patient participation in the design of such systems.

CONCLUSIONS

This paper calls specifically for further studies of K-SRS-and for studies of technologies that allow patients to generate their own health data in general-to pay more attention to how patients' own use of their data may influence their care processes and outcomes. Future studies that trial the effectiveness of K-SRS outside the clinic should also explore how patients and carers use PGHD in home rehabilitation programs.

Accurate estimation of joint motion trajectories for rehabilitation using Kinect

Kinect as an effective tool for clinical assessment and rehabilitation, suffers from drawbacks of lower accuracy of measuring human body kinematic data when compared to clinical gold standard motion capture devices. The accuracy of time-varying 3D locations of a fixed number of body joints obtained from Kinect skeletal tracking utility is affected by the presence of noise and precision limits of the Kinect depth sensor. In this paper, a framework for improving accuracy of Kinect skeletal tracking is proposed, that uses a set of parametric models to represent and track the human body. Each of the models represents the 3D geometric properties of a body segment connecting two adjacent joints. The temporal trajectories of the joints are recovered via particle filter-based motion tracking of each model. The proposed method was evaluated on Active Range of Motion exercises by 7 healthy subjects. The joint motion trajectories obtained using the proposed framework exhibit a greater motion smoothness (by 36%) along with reduced coefficient of variation of radius (by 34%), and lower value of root-mean-squared-error (by 53%), when compared to Kinect joint trajectories. This indicates an improvement in accuracy of joint motion trajectories using Kinect device, rendering it more suitable for clinical assessment and rehabilitation.

Reported use of technology in stroke rehabilitation by physical and occupational therapists

PURPOSE

With the patient care experience being a healthcare priority, it is concerning that patients with stroke reported boredom and a desire for greater fostering of autonomy, when evaluating their rehabilitation experience. Technology has the potential to reduce these shortcomings by engaging patients through entertainment and objective feedback. Providing objective feedback has resulted in improved outcomes and may assist the patient in learning how to self-manage rehabilitation. Our goal was to examine the extent to which physical and occupational therapists use technology in clinical stroke rehabilitation home exercise programs.

MATERIALS AND METHODS

Surveys were sent via mail, email and online postings to over 500 therapists, 107 responded.

RESULTS

Conventional equipment such as stopwatches are more frequently used compared to newer technology like Wii and Kinect games. Still, less than 25% of therapists' report using a stopwatch five or more times per week. Notably, feedback to patients is based upon objective data less than 50% of the time by most therapists. At the end of clinical rehabilitation, patients typically receive a written home exercise program and non-technological equipment, like theraband and/or theraputty to continue rehabilitation efforts independently.

CONCLUSIONS

The use of technology is not pervasive in the continuum of stroke rehabilitation. Implications for Rehabilitation The patient care experience is a priority in healthcare, so when patients report feeling bored and desiring greater fostering of autonomy in stroke rehabilitation, it is troubling. Research examining the use of technology has shown positive results for improving motor performance and engaging patients through entertainment and use of objective feedback. Physical and occupational therapists do not widely use technology in stroke rehabilitation. Therapists should consider using technology in stroke rehabilitation to better meet the needs of the patient.

Harnessing the potential of the Kinect sensor for psychiatric rehabilitation for stroke survivors

Dominques et al. in their recent article described how low-cost sensors, such as Microsoft Kinect could be utilized for the measurement of various anthropometric measures. With the recent advances in sensors and sensor based technology, along with the rapid advancement in E-health, Microsoft Kinect has been increasingly recognized by researchers and bioengineers to be a low-cost sensor that could help in the collation of various measurements and various data. A recent systematic review done by Da Gama et al. (2015) have looked into the potential of Kinect in terms of motor rehabilitation. The systematic review highlighted the tremendous potential of the sensors and has clearly stated that there is a need for further studies evaluating its potential for rehabilitation. Zhang et al. (2015) in their recent article have advocated several reasons as to why biosensors are pertinent for stroke rehabilitation. Of note, recent studies done by the World Health Organization have highlighted that stroke is a growing epidemic. Aside to the utilization of smartphone based sensors for stroke rehabilitation, as proposed by Zhang et al. (2015), researchers have also investigated the use of other low cost alternatives, such as Kinect, to facilitate the rehabilitation of stroke survivors. Whilst it may seemed like that has been quite extensive evaluation of the Kinect sensor for stroke rehabilitation, one core area that bio-engineers and researchers have not looked into is that of the psychiatric and mental health issues that might at times arise following a stroke. It is thus the aim of this letter to address how such a sensor could be tapped upon for psychiatric rehabilitation amongst stroke survivors. To this end, the authors have thus conceptualized a game that could help in the cognitive remediation for stroke survivors using low cost Kinect sensors.

Identifying Features of Bodily Expression As Indicators of Emotional Experience during Multimedia Learning

The importance of emotions experienced by learners during their interaction with multimedia learning systems, such as serious games, underscores the need to identify sources of information that allow the recognition of learners’ emotional experience without interrupting the learning process. Bodily expression is gaining in attention as one of these sources of information. However, to date, the question of how bodily expression can convey different emotions has largely been addressed in research relying on acted emotion displays. Following a more contextualized approach, the present study aims to identify features of bodily expression (i.e., posture and activity of the upper body and the head) that relate to genuine emotional experience during interaction with a serious game. In a multimethod approach, 70 undergraduates played a serious game relating to financial education while their bodily expression was captured using an off-the-shelf depth-image sensor (Microsoft Kinect). In addition, self-reports of experienced enjoyment, boredom, and frustration were collected repeatedly during gameplay, to address the dynamic changes in emotions occurring in educational tasks. Results showed that, firstly, the intensities of all emotions indeed changed significantly over the course of the game. Secondly, by using generalized estimating equations, distinct features of bodily expression could be identified as significant indicators for each emotion under investigation. A participant keeping their head more turned to the right was positively related to frustration being experienced, whereas keeping their head more turned to the left was positively related to enjoyment. Furthermore, having their upper body positioned more closely to the gaming screen was also positively related to frustration. Finally, increased activity of a participant’s head emerged as a significant indicator of boredom being experienced. These results confirm the value of bodily expression as an indicator of emotional experience in multimedia learning systems. Furthermore, the findings may guide developers of emotion recognition procedures by focusing on the identified features of bodily expression.

Accurate upper body rehabilitation system using kinect

The growing importance of Kinect as a tool for clinical assessment and rehabilitation is due to its portability, low cost and markerless system for human motion capture. However, the accuracy of Kinect in measuring three-dimensional body joint center locations often fails to meet clinical standards of accuracy when compared to marker-based motion capture systems such as Vicon. The length of the body segment connecting any two joints, measured as the distance between three-dimensional Kinect skeleton joint coordinates, has been observed to vary with time. The orientation of the line connecting adjoining Kinect skeletal coordinates has also been seen to differ from the actual orientation of the physical body segment. Hence we have proposed an optimization method that utilizes Kinect Depth and RGB information to search for the joint center location that satisfies constraints on body segment length and as well as orientation. An experimental study have been carried out on ten healthy participants performing upper body range of motion exercises. The results report 72% reduction in body segment length variance and 2° improvement in Range of Motion (ROM) angle hence enabling to more accurate measurements for upper limb exercises.

Targeted box and blocks test: Normative data and comparison to standard tests

Background

The Box and Block Test (BBT) is a functional outcome measure that is commonly used across multiple clinical populations due to its benefits of ease and speed of implementation; reliable, objective measurement; and repetition of motion. In this study, we introduce a novel outcome measure called the targeted BBT that allows for the study of initiation, grasping, and transport of objects, and also of object release. These modifications to the existing test may increase the ecological validity of the measure while still retaining the previously stated benefits of the standard BBT.

Methods

19 able-bodied subjects performed the targeted BBT and two other standard tests. Using an integrated movement analysis framework based on motion capture and ground force data, quantitative information about how subjects completed these tests were captured. Kinematic parameters at the wrist, elbow, shoulder, thorax, and head, as well as measures of postural control, were calculated and statistically compared across the three tests.

Results

In general, the targeted BBT required significantly higher RoM at the elbow, shoulder, thorax and head when compared to standard tests. Peak angles at these joints were also higher during performance of the targeted BBT. Peak angles and RoM values for the targeted BBT were close to those found in studies of movements of able-bodied individuals performing activities of daily living.

Conclusion

The targeted BBT allows analysis of repetitive movements, and may more closely model common real-world object manipulation scenarios in which a user is required to control a movement from pick-up to release.

An Integrated Movement Analysis Framework to Study Upper Limb Function: A Pilot Study

The functional capabilities of individuals with upper limb disabilities are assessed throughout rehabilitation and treatment regimens using functional outcome measures. For the upper limb amputee population, there are none which quantitatively take into account the quality of movement while an individual is performing tasks. In this paper, we demonstrate the use of an integrated movement analysis framework, based on motion capture and ground reaction force data, to capture quantitative information about how subjects complete a commonly used functional outcome measure, the Box and Blocks Test (BBT). In order to test the usefulness of the integrated movement analysis framework in capturing the quality of movements during task performance, a motion restriction was induced in able-bodied participants that reproduces some of the limitations imposed by conventional prosthetics. Each subject performed the BBT under normal conditions and also under the motion restriction condition. The motion capture and ground force plates captured movement that significantly differed between the two conditions, with the largest differences seen in shoulder motion, in the range of motions of head tilt and elbow flexion, and in the area of the center of pressure trajectory. These preliminary results show the feasibility of incorporating standardized, quantitative movement analysis into the assessment of function for those with an upper limb disability.

Feasibility of Using Microsoft Kinect to Assess Upper Limb Movement in Type III Spinal Muscular Atrophy Patients

Although functional rating scales are being used increasingly as primary outcome measures in spinal muscular atrophy (SMA), sensitive and objective assessment of early-stage disease progression and drug efficacy remains challenging. We have developed a game based on the Microsoft Kinect sensor, specifically designed to measure active upper limb movement. An explorative study was conducted to determine the feasibility of this new tool in 18 ambulant SMA type III patients and 19 age- and gender-matched healthy controls. Upper limb movement was analysed elaborately through derived features such as elbow flexion and extension angles, arm lifting angle, velocity and acceleration. No significant differences were found in the active range of motion between ambulant SMA type III patients and controls. Hand velocity was found to be different but further validation is necessary. This study presents an important step in the process of designing and handling digital biomarkers as complementary outcome measures for clinical trials.

A New Adaptive Home-based Exercise Technology among Older Adults Living in Nursing Home: A Pilot Study on Feasibility, Acceptability and Physical Performance

OBJECTIVES

To explore the feasibility and acceptability of a new home-based exercise technology among older adults and to evaluate its efficacy on physical performance measures.

DESIGN

Longitudinal clinical trial.

SETTING

Oak Hammock at the University of Florida, a nursing home located in Gainesville, Florida.

PARTICIPANTS

Twelve pre-disabled older adults (≥75 years) living in a nursing home with a Short Physical Performance Battery (SPPB) score between 6 and 9 and no diagnosis of dementia.

INTERVENTION

Thirty minutes of light intensity exercise (aerobic, strength and balance) two times per week for four weeks using a home-based physical activity technology called Jintronix.

MEASUREMENTS

Feasibility and acceptability were assessed through a 9-item self-administered questionnaire and by exploring the percentage of quality of movements and time performing exercise which was calculated automatically by Jintronix technology. Physical performance measures were assessed through the SPPB score at baseline, after 4 weeks of intervention and after 3 months from the completion of the intervention.

RESULTS

Twelve older adults (80.5±4.2 years old) performed light intensity exercise with Jintronix for a total of 51.9±7.9 minutes per week. Participants reached 87% score of quality of movements in strength and balance exercises, a global appreciation score of 91.7% and a global difficulty score of 36%. Compared to baseline, there was a significant improvement in SPPB score at the end of the intervention and at 3 months following the completion of the exercise program (0.67±0.98 and 1.08±0.99 respectively, p-value <0.05).

CONCLUSION

Jintronix technology is feasible and acceptable among pre-disabled older adults without dementia living in nursing home and is beneficial in improving their physical performance.