Application of Commercial Games for Home-Based Rehabilitation for People with Hemiparesis: Challenges and Lessons Learned.

OBJECTIVE: To identify the factors that influence the use of an at-home virtual rehabilitation gaming system from the perspective of therapists, engineers, and adults and adolescents with hemiparesis secondary to stroke, brain injury, and cerebral palsy. MATERIALS AND METHODS: This study reports on qualitative findings from a study, involving seven adults (two female; mean age: 65 ± 8 years) and three adolescents (one female; mean age: 15 ± 2 years) with hemiparesis, evaluating the feasibility and clinical effectiveness of a home-based custom-designed virtual rehabilitation system over 2 months. Thematic analysis was used to analyze qualitative data from therapists' weekly telephone interview notes, research team documentation regarding issues raised during technical support interactions, and the transcript of a poststudy debriefing session involving research team members and collaborators. RESULTS: Qualitative themes that emerged suggested that system use was associated with three key factors as follows: (1) the technology itself (e.g., characteristics of the games and their clinical implications, system accessibility, and hardware and software design); (2) communication processes (e.g., preferences and effectiveness of methods used during the study); and (3) knowledge and training of participants and therapists on the technology's use (e.g., familiarity with Facebook, time required to gain competence with the system, and need for clinical observations during remote therapy). Strategies to address these factors are proposed. CONCLUSION: Lessons learned from this study can inform future clinical and implementation research using commercial videogames and social media platforms. The capacity to track compensatory movements, clinical considerations in game selection, the provision of kinematic and treatment progress reports to participants, and effective communication and training for therapists and participants may enhance research success, system usability, and adoption.

Data sample size needed for analysis of kinematic and muscle synergies in healthy and stroke populations.

Multiple studies have suggested the central nervous system (CNS) generates motions by using modular control of muscles and joints (synergies). However, the synergies reported by these studies are task dependent and might not reflect the true control strategies adopted by the CNS. Studying exploratory motions (EMs) can reveal biomechanical constraints and motor control strategies in healthy and clinical populations. The first logical step to consider EMs in study of motor synergies is to determine how much data is required to reliably and fully profile the motion patterns of an individual. Here we present how the quality of motor synergies analysis depends on the amount of EM data included in the analysis. We recruited 10 healthy and 10 post-stroke participants and collected electromyography (EMG) and joint motion data of their arms as they completed a motor exploration task. We compared the effects of clinical status and limb strength/dominance on the amount of data required to identify synergies. Clinical status had a significant elïect on the required amount of data for both datasets. Limb strength had a significant effect only for kinematic data. We determined the upper bound 95% confidence interval to set the amount of data required for synergy analysis in both populations: 235 sec for EMG data and 265 sec for kinematic data. Our results provide an important step toward using motor exploration in the study of healthy motor synergies and how stroke alters them.

On identifying kinematic and muscle synergies: a comparison of matrix factorization methods using experimental data from the healthy population.

Human motor behavior is highly goal directed, requiring the central nervous system to coordinate different aspects of motion generation to achieve the motion goals. The concept of motor synergies provides an approach to quantify the covariation of joint motions and of muscle activations, i.e., elemental variables, during a task. To analyze goal-directed movements, factorization methods can be used to reduce the high dimensionality of these variables while accounting for much of the variance in large data sets. Three factorization methods considered in this paper are principal component analysis (PCA), nonnegative matrix factorization (NNMF), and independent component analysis (ICA). Bilateral human reaching data sets are used to compare the methods, and advantages of each are presented and discussed. PCA and NNMF had a comparable performance on both EMG and joint motion data and both outperformed ICA. However, NNMF's nonnegativity condition for activation of basis vectors is a useful attribute in identifying physiologically meaningful synergies, making it a more appealing method for future studies. A simulated data set is introduced to clarify the approaches and interpretation of the synergy structures returned by the three factorization methods. NEW & NOTEWORTHY: Literature on comparing factorization methods in identifying motor synergies using numerically generated, simulation, and muscle activation data from animal studies already exists. We present an empirical evaluation of the performance of three of these methods on muscle activation and joint angles data from human reaching motion: principal component analysis, nonnegative matrix factorization, and independent component analysis. Using numerical simulation, we also studied the meaning and differences in the synergy structures returned by each method. The results can be used to unify approaches in identifying and interpreting motor synergies.

A reliability assessment of constrained spherical deconvolution-based diffusion-weighted magnetic resonance imaging in individuals with chronic stroke.

BACKGROUND: Diffusion-weighted magnetic resonance imaging (DW-MRI) is commonly used to assess white matter properties after stroke. Novel work is utilizing constrained spherical deconvolution (CSD) to estimate complex intra-voxel fiber architecture unaccounted for with tensor-based fiber tractography. However, the reliability of CSD-based tractography has not been established in people with chronic stroke. NEW METHOD: Establishing the reliability of CSD-based DW-MRI in chronic stroke. High-resolution DW-MRI was performed in ten adults with chronic stroke during two separate sessions. Deterministic region of interest-based fiber tractography using CSD was performed by two raters. Mean fractional anisotropy (FA), apparent diffusion coefficient (ADC), tract number, and tract volume were extracted from reconstructed fiber pathways in the corticospinal tract (CST) and superior longitudinal fasciculus (SLF). Callosal fiber pathways connecting the primary motor cortices were also evaluated. Inter-rater and test-retest reliability were determined by intra-class correlation coefficients (ICCs). RESULTS: ICCs revealed excellent reliability for FA and ADC in ipsilesional (0.86-1.00; p<0.05) and contralesional hemispheres (0.94-1.00; p<0.0001), for CST and SLF fibers; and excellent reliability for all metrics in callosal fibers (0.85-1.00; p<0.05). ICC ranged from poor to excellent for tract number and tract volume in ipsilesional (-0.11 to 0.92; p≤0.57) and contralesional hemispheres (-0.27 to 0.93; p≤0.64), for CST and SLF fibers. COMPARISON WITH EXISTING METHOD: Like other select DW-MRI approaches, CSD-based tractography is a reliable approach to evaluate FA and ADC in major white matter pathways, in chronic stroke. CONCLUSION: Future work should address the reproducibility and utility of CSD-based metrics of tract number and tract volume.

Evaluating the User Experience of Exercising Reaching Motions With a Robot That Predicts Desired Movement Difficulty.

The notion of an optimal difficulty during practice has been articulated in many areas of cognitive psychology: flow theory, the challenge point framework, and desirable difficulties. Delivering exercises at a participant's desired difficulty has the potential to improve both motor learning and users' engagement in therapy. Motivation and engagement are among the contributing factors to the success of exercise programs. The authors previously demonstrated that error amplification can be used to introduce levels of challenge into a robotic reaching task, and that machine-learning algorithms can dynamically adjust difficulty to the desired level with 85% accuracy. Building on these findings, we present the results of a proof-of-concept study investigating the impacts of practicing under desirable difficulty conditions. A control condition with a predefined random order for difficulty levels was deemed more suitable for this study (compared to constant or continuously increasing difficulty). By practicing the task at their desirable difficulties, participants in the experimental group perceived their performance at a significantly higher level and reported lower required effort to complete the task, in comparison to a control group. Moreover, based on self-reports, participants in the experimental group were willing, on average, to continue the training session for 4.6 more training blocks (∼45 min) compared to the control group's average. This study demonstrates the efficiency of delivering the exercises at the user's desired difficulty level to improve the user's engagement in exercise tasks. Future work will focus on clinical feasibility of this approach in increasing stroke survivors' engagement in their therapy programs.

Therapists' perceptions of social media and video game technologies in upper limb rehabilitation.

BACKGROUND: The application of technologies, such as video gaming and social media for rehabilitation, is garnering interest in the medical field. However, little research has examined clinicians' perspectives regarding technology adoption by their clients. OBJECTIVE: The objective of our study was to explore therapists' perceptions of how young people and adults with hemiplegia use gaming and social media technologies in daily life and in rehabilitation, and to identify barriers to using these technologies in rehabilitation. METHODS: We conducted two focus groups comprised of ten occupational therapists/physiotherapists who provide neurorehabilitation to individuals with hemiplegia secondary to stroke or cerebral palsy. Data was analyzed using inductive thematic analysis. The diffusion of innovations theory provided a framework to interpret emerging themes. RESULTS: Therapists were using technology in a limited capacity. They identified barriers to using social media and gaming technology with their clients, including a lack of age appropriateness, privacy issues with social media, limited transfer of training, and a lack of accessibility of current systems. Therapists also questioned their role in the context of technology-based interventions. The opportunity for social interaction was perceived as a major benefit of integrated gaming and social media. CONCLUSIONS: This study reveals the complexities associated with adopting new technologies in clinical practice, including the need to consider both client and clinician factors. Despite reporting several challenges with applying gaming and social media technology with clinical populations, therapists identified opportunities for increased social interactions and were willing to help shape the development of an upper limb training system that could more readily meet the needs of clients with hemiplegia. By considering the needs of both therapists and clients, technology developers may increase the likelihood that clinicians will adopt innovative technologies.

Perceptions of Technology and Its Use for Therapeutic Application for Individuals With Hemiparesis: Findings From Adult and Pediatric Focus Groups.

BACKGROUND: Digital technology is becoming an increasingly popular means of delivering meaningful therapy to individuals with neurological impairments. An understanding of clients' technology use and their perspectives on incorporating technology into rehabilitation can provide researchers and designers with valuable information to inform development of technologies and technology-based rehabilitation programs. OBJECTIVE: This study was designed to establish the current use and perceptions of gaming, social media, and robotics technologies for rehabilitative purposes from the perspective of adults and children with upper limb impairments to identify barriers and enablers to their adoption and use. METHODS: We conducted three focus groups consisting of pediatric (n=7, mean age 11.0 years) and adult (n=8, mean age 60.8 years) participants with hemiparesis affecting their upper limb. We applied thematic analysis methods to the resulting data. RESULTS: We identified three key themes: (1) clients' use of technology in everyday life and rehabilitation, (2) barriers to use, and (3) enablers to therapy. Participants had limited exposure to technology for therapeutic purposes, but all acknowledged the potential benefits in providing motivation and interest for the performance of repetitive task practice. Adult participants requested efficacious, simple, and easy-to-use technology for rehabilitation with programs that could be individualized for them and expressed that they wanted these programs to provide a motivating means of repeated practice of therapeutic movements. In contrast, pediatric participants emphasized a desire for technology for rehabilitation that offered opportunities for social interaction and interactive games involving their whole body and not only their affected limb. Perceived safety and privacy were concerns for both groups. CONCLUSIONS: Our findings highlight that all participants were open to the integration of technology into rehabilitation. Adult participants were more pragmatically motivated by potential recovery gains, whereas pediatric participants were more intrinsically motivated by access to games.

Usability testing of gaming and social media applications for stroke and cerebral palsy upper limb rehabilitation.

As part of the FEATHERS (Functional Engagement in Assisted Therapy Through Exercise Robotics) project, two motion tracking and one social networking applications were developed for upper limb rehabilitation of stroke survivors and teenagers with cerebral palsy. The project aims to improve the engagement of clients during therapy by using video games and a social media platform. The applications allow users to control a cursor on a personal computer through bimanual motions, and to interact with their peers and therapists through the social media. The tracking applications use either a Microsoft Kinect or a PlayStation Eye camera, and the social media application was developed on Facebook. This paper presents a usability testing of these applications that was conducted with therapists from two rehabilitation clinics. The "Cognitive Walkthrough" and "Think Aloud" methods were used. The objectives of the study were to investigate the ease of use and potential issues or improvements of the applications, as well as the factors that facilitate and impede the adoption of technology in current rehabilitation programs.

Physiological responses to error amplification in a robotic reaching adaptation task.

Analysis of physiological responses provides an objective measure of a person's affective state and has been proposed as a way to evaluate motivation and engagement of therapy clients during robot-assisted therapy regimens. This paper presents the analysis of three physiological responses to different levels of error amplification in a robotic reaching task to understand the feasibility of using physiological signals in order to modify therapy exercises to achieve higher participant attentiveness. In a pilot study with 22 healthy participants, we analyzed skin conductance, skin temperature, and respiration signals, with two main goals: 1) to compare physiological parameters between baseline (rest) and error-amplified reaching motion periods; and 2) to compare physiological parameters between reaching motion periods with different levels of error amplification. Results show that features extracted from skin conductance and respiration signals show significant differences between different error amplification levels. Features extracted from the skin temperature signal are not as reliable as measures of skin conductance and respiration, however they can provide supplementary information.

Video games and rehabilitation: using design principles to enhance engagement in physical therapy.

Patient nonadherence with therapy is a major barrier to rehabilitation. Recovery is often limited and requires prolonged, intensive rehabilitation that is time-consuming, expensive, and difficult. We review evidence for the potential use of video games in rehabilitation with respect to the behavioral, physiological, and motivational effects of gameplay. In this Special Interest article, we offer a method to evaluate effects of video game play on motor learning and their potential to increase patient engagement with therapy, particularly commercial games that can be interfaced with adapted control systems. We take the novel approach of integrating research across game design, motor learning, neurophysiology changes, and rehabilitation science to provide criteria by which therapists can assist patients in choosing games appropriate for rehabilitation. Research suggests that video games are beneficial for cognitive and motor skill learning in both rehabilitation science and experimental studies with healthy subjects. Physiological data suggest that gameplay can induce neuroplastic reorganization that leads to long-term retention and transfer of skill; however, more clinical research in this area is needed. There is interdisciplinary evidence suggesting that key factors in game design, including choice, reward, and goals, lead to increased motivation and engagement. We maintain that video game play could be an effective supplement to traditional therapy. Motion controllers can be used to practice rehabilitation-relevant movements, and well-designed game mechanics can augment patient engagement and motivation in rehabilitation. We recommend future research and development exploring rehabilitation-relevant motions to control games and increase time in therapy through gameplay.Video Abstract available (see Video, Supplemental Digital Content 1, http://links.lww.com/JNPT/A61) for more insights from the authors.

Adaptation of task difficulty in rehabilitation exercises based on the user's motor performance and physiological responses.

Although robot-assisted rehabilitation regimens are as effective, functionally, as conventional therapies, they still lack features to increase patients' engagement in the regimen. Providing rehabilitation tasks at a "desirable difficulty" is one of the ways to address this issue and increase the motivation of a patient to continue with the therapy program. Then the problem is to design a system that is capable of estimating the user's desirable difficulty, and ultimately, modifying the task based on this prediction. In this paper we compared the performance of three machine learning algorithms in predicting a user's desirable difficulty during a typical reaching motion rehabilitation task. Different levels of error amplification were used as different levels of task difficulty. We explored the usefulness of using participants' motor performance and physiological signals during the reaching task in prediction of their desirable difficulties. Results showed that a Neural Network approach gives higher prediction accuracy in comparison with models based on k-Nearest Neighbor and Discriminant Analysis methods.

Error amplification to promote motor learning and motivation in therapy robotics.

To study the effects of different feedback error amplification methods on a subject's upper-limb motor learning and affect during a point-to-point reaching exercise, we developed a real-time controller for a robotic manipulandum. The reaching environment was visually distorted by implementing a thirty degrees rotation between the coordinate systems of the robot's end-effector and the visual display. Feedback error amplification was provided to subjects as they trained to learn reaching within the visually rotated environment. Error amplification was provided either visually or through both haptic and visual means, each method with two different amplification gains. Subjects' performance (i.e., trajectory error) and self-reports to a questionnaire were used to study the speed and amount of adaptation promoted by each error amplification method and subjects' emotional changes. We found that providing haptic and visual feedback promotes faster adaptation to the distortion and increases subjects' satisfaction with the task, leading to a higher level of attentiveness during the exercise. This finding can be used to design a novel exercise regimen, where alternating between error amplification methods is used to both increase a subject's motor learning and maintain a minimum level of motivational engagement in the exercise. In future experiments, we will test whether such exercise methods will lead to a faster learning time and greater motivation to pursue a therapy exercise regimen.