Towards a Platform for Robot-Assisted Minimally-Supervised Therapy of Hand Function: Design and Pilot Usability Evaluation

Closing the loop in minimally supervised human-robot interaction: formative and summative feedback

Human instructors fluidly communicate with hand gestures, head and body movements, and facial expressions, but robots rarely leverage these complementary cues. A minimally supervised social robot with such skills could help people exercise and learn new activities. Thus, we investigated how nonverbal feedback from a humanoid robot affects human behavior. Inspired by the education literature, we evaluated formative feedback (real-time corrections) and summative feedback (post-task scores) for three distinct tasks: positioning in the room, mimicking the robot's arm pose, and contacting the robot's hands. Twenty-eight adults completed seventy-five 30-s-long trials with no explicit instructions or experimenter help. Motion-capture data analysis shows that both formative and summative feedback from the robot significantly aided user performance. Additionally, formative feedback improved task understanding. These results show the power of nonverbal cues based on human movement and the utility of viewing feedback through formative and summative lenses.

Evaluating tactile feedback in addition to kinesthetic feedback for haptic shape rendering: a pilot study

In current virtual reality settings for motor skill training, only visual information is usually provided regarding the virtual objects the trainee interacts with. However, information gathered through cutaneous (tactile feedback) and muscle mechanoreceptors (kinesthetic feedback) regarding, e.g., object shape, is crucial to successfully interact with those objects. To provide this essential information, previous haptic interfaces have targeted to render either tactile or kinesthetic feedback while the effectiveness of multimodal tactile and kinesthetic feedback on the perception of the characteristics of virtual objects still remains largely unexplored. Here, we present the results from an experiment we conducted with sixteen participants to evaluate the effectiveness of multimodal tactile and kinesthetic feedback on shape perception. Using a within-subject design, participants were asked to reproduce virtual shapes after exploring them without visual feedback and with either congruent tactile and kinesthetic feedback or with only kinesthetic feedback. Tactile feedback was provided with a cable-driven platform mounted on the fingertip, while kinesthetic feedback was provided using a haptic glove. To measure the participants' ability to perceive and reproduce the rendered shapes, we measured the time participants spent exploring and reproducing the shapes and the error between the rendered and reproduced shapes after exploration. Furthermore, we assessed the participants' workload and motivation using well-established questionnaires. We found that concurrent tactile and kinesthetic feedback during shape exploration resulted in lower reproduction errors and longer reproduction times. The longer reproduction times for the combined condition may indicate that participants could learn the shapes better and, thus, were more careful when reproducing them. We did not find differences between conditions in the time spent exploring the shapes or the participants' workload and motivation. The lack of differences in workload between conditions could be attributed to the reported minimal-to-intermediate workload levels, suggesting that there was little room to further reduce the workload. Our work highlights the potential advantages of multimodal congruent tactile and kinesthetic feedback when interacting with tangible virtual objects with applications in virtual simulators for hands-on training applications.

Unsupervised robot-assisted rehabilitation after stroke: feasibility, effect on therapy dose, and user experience

BACKGROUND

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

METHODS

Subacute stroke patients underwent a four-week protocol composed of daily 45 min-sessions of robot-assisted therapy. The first week consisted of supervised therapy, where a therapist explained how to interact with the device. The second week was minimally supervised, i.e., the therapist was present but intervened only if needed. After this phase, if participants learnt how to use the device, they proceeded to two weeks of fully unsupervised training. Feasibility, dose of robot-assisted therapy achieved during unsupervised use, user experience, and usability of the device were evaluated. Questionnaires to evaluate usability and user experience were performed after the minimally supervised week and at the end of the study, to evaluate the impact of therapists' absence.

RESULTS

Unsupervised robot-assisted therapy was found to be feasible, as 12 out of the 13 recruited participants could progress to unsupervised training. During the two weeks of unsupervised therapy participants on average performed an additional 360 min of robot-assisted rehabilitation. Participants were satisfied with the device usability (mean System Usability Scale scores > 79), and no adverse events or device deficiencies occurred.

CONCLUSIONS

We demonstrated that unsupervised robot-assisted therapy in a clinical setting with an actuated device for the upper limb was feasible and can lead to a meaningful increase in therapy dose. These results support the application of unsupervised robot-assisted therapy as a complement to usual care in clinical settings and pave the way to its application in home settings.

TRIAL REGISTRATION

Registered on 13.05.2020 on clinicaltrials.gov (NCT04388891).

Designing for usability: development and evaluation of a portable minimally-actuated haptic hand and forearm trainer for unsupervised stroke rehabilitation

In stroke rehabilitation, simple robotic devices hold the potential to increase the training dosage in group therapies and to enable continued therapy at home after hospital discharge. However, we identified a lack of portable and cost-effective devices that not only focus on improving motor functions but also address sensory deficits. Thus, we designed a minimally-actuated hand training device that incorporates active grasping movements and passive pronosupination, complemented by a rehabilitative game with meaningful haptic feedback. Following a human-centered design approach, we conducted a usability study with 13 healthy participants, including three therapists. In a simulated unsupervised environment, the naive participants had to set up and use the device based on written instructions. Our mixed-methods approach included quantitative data from performance metrics, standardized questionnaires, and eye tracking, alongside qualitative feedback from semi-structured interviews. The study results highlighted the device's overall ease of setup and use, as well as its realistic haptic feedback. The eye-tracking analysis further suggested that participants felt safe during usage. Moreover, the study provided crucial insights for future improvements such as a more intuitive and comfortable wrist fixation, more natural pronosupination movements, and easier-to-follow instructions. Our research underscores the importance of continuous testing in the development process and offers significant contributions to the design of user-friendly, unsupervised neurorehabilitation technologies to improve sensorimotor stroke rehabilitation.

Robotic systems for upper-limb rehabilitation in multiple sclerosis: a SWOT analysis and the synergies with virtual and augmented environments

The robotics discipline is exploring precise and versatile solutions for upper-limb rehabilitation in Multiple Sclerosis (MS). People with MS can greatly benefit from robotic systems to help combat the complexities of this disease, which can impair the ability to perform activities of daily living (ADLs). In order to present the potential and the limitations of smart mechatronic devices in the mentioned clinical domain, this review is structured to propose a concise SWOT (Strengths, Weaknesses, Opportunities, and Threats) Analysis of robotic rehabilitation in MS. Through the SWOT Analysis, a method mostly adopted in business management, this paper addresses both internal and external factors that can promote or hinder the adoption of upper-limb rehabilitation robots in MS. Subsequently, it discusses how the synergy with another category of interaction technologies - the systems underlying virtual and augmented environments - may empower Strengths, overcome Weaknesses, expand Opportunities, and handle Threats in rehabilitation robotics for MS. The impactful adaptability of these digital settings (extensively used in rehabilitation for MS, even to approach ADL-like tasks in safe simulated contexts) is the main reason for presenting this approach to face the critical issues of the aforementioned SWOT Analysis. This methodological proposal aims at paving the way for devising further synergistic strategies based on the integration of medical robotic devices with other promising technologies to help upper-limb functional recovery in MS.

Progressive Transition From Supervised to Unsupervised Robot-Assisted Therapy After Stroke: Protocol for a Single-Group, Interventional Feasibility Study

BACKGROUND

Increasing the dose of therapy delivered to patients with stroke may improve functional outcomes and quality of life. Unsupervised technology-assisted rehabilitation is a promising way to increase the dose of therapy without dramatically increasing the burden on the health care system. Despite the many existing technologies for unsupervised rehabilitation, active rehabilitation robots have rarely been tested in a fully unsupervised way. Furthermore, the outcomes of unsupervised technology-assisted therapy (eg, feasibility, acceptance, and increase in therapy dose) vary widely. This might be due to the use of different technologies as well as to the broad range of methods applied to teach the patients how to independently train with a technology.

OBJECTIVE

This paper describes the study design of a clinical study investigating the feasibility of unsupervised therapy with an active robot and of a systematic approach for the progressive transition from supervised to unsupervised use of a rehabilitation technology in a clinical setting. The effect of unsupervised therapy on achievable therapy dose, user experience in this therapy setting, and the usability of the rehabilitation technology are also evaluated.

METHODS

Participants of the clinical study are inpatients of a rehabilitation clinic with subacute stroke undergoing a 4-week intervention where they train with a hand rehabilitation robot. The first week of the intervention is supervised by a therapist, who teaches participants how to interact and train with the device. The second week consists of minimally supervised therapy, where the therapist is present but intervenes only if needed as participants exercise with the device. If the participants properly learn how to train with the device, they proceed to the unsupervised phase and train without any supervision during the third and fourth weeks. Throughout the duration of the study, data on feasibility and therapy dose (ie, duration and repetitions) are collected. Usability and user experience are evaluated at the end of the second (ie, minimally supervised) and fourth (ie, unsupervised) weeks, allowing us to investigate the effect of therapist absence.

RESULTS

As of April 2023, 13 patients were recruited and completed the protocol, with no reported adverse events.

CONCLUSIONS

This study will inform on the feasibility of fully unsupervised rehabilitation with an active rehabilitation robot in a clinical setting and its effect on therapy dose. Furthermore, if successful, the proposed systematic approach for a progressive transition from supervised to unsupervised technology-assisted rehabilitation could serve as a benchmark to allow for easier comparisons between different technologies. This approach could also be extended to the application of such technologies in the home environment, as the supervised and minimally supervised sessions could be performed in the clinic, followed by unsupervised therapy at home after discharge.

TRIAL REGISTRATION

ClinicalTrials.gov NCT04388891; https://clinicaltrials.gov/study/NCT04388891.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID)

DERR1-10.2196/48485.

Efficacy of Robot-Assisted Training on Rehabilitation of Upper Limb Function in Patients With Stroke: A Systematic Review and Meta-analysis

OBJECTIVE

To systematically evaluate the effect of robot-assisted training (RAT) on upper limb function recovery in patients with stroke, providing the evidence-based medical basis for the clinical application of RAT.

DATA SOURCES

We searched online electronic databases up to June 2022, including PubMed, The Cochrane Library, Scopus, Web of Science, EMBASE, WanFang Data, CNKI, and VIP full-text databases.

STUDY SELECTION

Randomized controlled trials of the effect of RAT on upper extremity functional recovery in patients with stroke.

DATA EXTRACTION

The Cochrane Collaboration Tool for Assessing the Risk of Bias was used to assess study quality and risk of bias.

DATA SYNTHESIS

Fourteen randomized controlled trials involving 1275 patients were included for review. Compared with the control group, RAT significantly improved upper limb motor function and daily living ability. The overall differences were statistically significant, Fugl-Meyer Assessment for the Upper Extremity (FMA-UE; standard mean difference=0.69; 95% confidence interval, 0.34, 1.05; P=.0001), modified Barthel Index (standard mean difference=0.95; 95% confidence interval, 0.75, 1.15; P<.00001), whereas the differences in modified Ashworth Scale, FIM, and Wolf Motor Function Test scores were not statistically significant.

SUBGROUP ANALYSIS

Compared with the control group, the differences between FMA-UE and modified Barthel Index at 4 and 12 weeks of RAT, there were statistically significant, the differences of FMA-UE and modified Ashworth Scale in patients with stroke in the acute and chronic phases were statistically significant.

CONCLUSION

The present study showed that RAT can significantly enhance the upper limb motor function and activities of daily life in patients with stroke undergoing upper limb rehabilitation.

Current Topics in Technology-Enabled Stroke Rehabilitation and Reintegration: A Scoping Review and Content Analysis

BACKGROUND

There is a worldwide health crisis stemming from the rising incidence of various debilitating chronic diseases, with stroke as a leading contributor. Chronic stroke management encompasses rehabilitation and reintegration, and can require decades of personalized medicine and care. Information technology (IT) tools have the potential to support individuals managing chronic stroke symptoms.

OBJECTIVES

This scoping review identifies prevalent topics and concepts in research literature on IT technology for stroke rehabilitation and reintegration, utilizing content analysis, based on topic modelling techniques from natural language processing to identify gaps in this literature.

ELIGIBILITY CRITERIA

Our methodological search initially identified over 14,000 publications of the last two decades in the Web of Science and Scopus databases, which we filter, using keywords and a qualitative review, to a core corpus of 1062 documents.

RESULTS

We generate a 3-topic, 4-topic and 5-topic model and interpret the resulting topics as four distinct thematics in the literature, which we label as Robotics, Software, Functional and Cognitive. We analyze the prevalence and distinctiveness of each thematic and identify some areas relatively neglected by the field. These are mainly in the Cognitive thematic, especially for systems and devices for sensory loss rehabilitation, tasks of daily living performance and social participation.

CONCLUSION

The results indicate that IT-enabled stroke literature has focused on Functional outcomes and Robotic technologies, with lesser emphasis on Cognitive outcomes and combined interventions. We hope this review broadens awareness, usage and mainstream acceptance of novel technologies in rehabilitation and reintegration among clinicians, carers and patients.

An online method to monitor hand muscle tone during robot-assisted rehabilitation

Introduction: Robot-assisted neurorehabilitation is becoming an established method to complement conventional therapy after stroke and provide intensive therapy regimes in unsupervised settings (e.g., home rehabilitation). Intensive therapies may temporarily contribute to increasing muscle tone and spasticity, especially in stroke patients presenting tone alterations. If sustained without supervision, such an increase in muscle tone could have negative effects (e.g., functional disability, pain). We propose an online perturbation-based method that monitors finger muscle tone during unsupervised robot-assisted hand therapy exercises. Methods: We used the ReHandyBot, a novel 2 degrees of freedom (DOF) haptic device to perform robot-assisted therapy exercises training hand grasping (i.e., flexion-extension of the fingers) and forearm pronosupination. The tone estimation method consisted of fast (150 ms) and slow (250 ms) 20 mm ramp-and-hold perturbations on the grasping DOF, which were applied during the exercises to stretch the finger flexors. The perturbation-induced peak force at the finger pads was used to compute tone. In this work, we evaluated the method performance in a stiffness identification experiment with springs (0.97 and 1.57 N/mm), which simulated the stiffness of a human hand, and in a pilot study with subjects with increased muscle tone after stroke and unimpaired, which performed one active sensorimotor exercise embedding the tone monitoring method. Results: The method accurately estimates forces with root mean square percentage errors of 3.8% and 11.3% for the soft and stiff spring, respectively. In the pilot study, six chronic ischemic stroke patients [141.8 (56.7) months after stroke, 64.3 (9.5) years old, expressed as mean (std)] and ten unimpaired subjects [59.9 (6.1) years old] were tested without adverse events. The average reaction force at the level of the fingertip during slow and fast perturbations in the exercise were respectively 10.7 (5.6) N and 13.7 (5.6) N for the patients and 5.8 (4.2) N and 6.8 (5.1) N for the unimpaired subjects. Discussion: The proposed method estimates reaction forces of physical springs accurately, and captures online increased reaction forces in persons with stroke compared to unimpaired subjects within unsupervised human-robot interactions. In the future, the identified range of muscle tone increase after stroke could be used to customize therapy for each subject and maintain safety during intensive robot-assisted rehabilitation.

Design and Preliminary Evaluation of a Robot-assisted Assessment-driven Finger Proprioception Therapy

Neurological injuries such as stroke often lead to motor and somatosensory impairments of the hand. Deficits in somatosensation, especially proprioception, result in difficulties performing activities of daily living involving fine motor tasks. However, it is challenging to accurately detect those impairments due to the limitations of clinical assessments. Hence therapies rarely focus on proprioception specifically, while such training could promote functional benefits. In this work we propose and preliminarily evaluate a robot-assisted, assessment-driven therapy of finger proprioception. We designed and implemented two therapeutic exercises, one targeting passive and the other active position sense. The difficulty level of the therapy exercises was adapted to each patient's proprioceptive impairment. We evaluated the exercises and their usability with 7 stroke participants and 8 clinicians in a 45-minutes protocol. We found that the exercises were feasible for stroke participants, as 5 individuals progressed in difficulty levels over multiple exercise repetitions, indicating adequacy of the adaptation algorithm. Moreover, usability was rated mostly as satisfactory by the patients (System Usability Scale = 73), and they also found the exercises interesting. Clinicians rated the exercises as difficult but clinically meaningful. Overall, these promising preliminary results pave the way for further development and validation of the proposed therapy approach.

Automatic and Personalized Adaptation of Therapy Parameters for Unsupervised Robot-Assisted Rehabilitation: a Pilot Evaluation

Growing evidence shows that increasing the dose of upper limb therapy after stroke might improve functional outcomes and unsupervised robot-assisted therapy may be a solution to achieve such an increase without adding workload on therapists. However, most of existing robotic devices still need frequent supervision by trained personnel and are currently not designed or ready for unsupervised use. One reason for this is that most rehabilitation devices are not capable of delivering and adapting personalized therapy without external intervention. Here we present a set of clinically-inspired algorithms that automatically adapt therapy parameters in a personalized way and guide the course of robot-assisted therapy sessions. We implemented these algorithms on a robotic device for hand rehabilitation and tested them in a pilot study with 5 subacute stroke subjects over 10 robot-assisted therapy sessions, some of which unsupervised. Results show that our algorithms could adapt the therapy difficulty throughout the whole study without requiring external intervention, maintaining performance around a predefined 70% target value (mean performance for all the subjects over all the sessions: 64.5%). Moreover, the algorithms could guide patients through the therapy sessions, minimizing the number of actions that subjects had to learn and perform. These results open the door to the use of robotic devices in an unsupervised setting to increase therapy dose after stroke.

Towards Unsupervised Rehabilitation: Development of a Portable Compliant Device for Sensorimotor Hand Rehabilitation

Sensorimotor impairments of the hand after stroke can drastically reduce the ability to perform activities of daily living. Recently, there has been an increased interest in minimally supervised and unsupervised rehabilitation to increase therapy dosage and to complement conventional therapy. Several devices have been developed that are simple to use and portable. Yet, they do not incorporate diversified somatosensory feedback, which has been suggested to promote sensorimotor recovery. Here we present the prototype of a portable one-degree-of-freedom hand trainer based on a novel compliant shell mechanism. Our solution is safe, intuitive, and can be used for various hand sizes. Importantly, it also provides rich sensory feedback through haptic rendering. We complement our device with a rehabilitation game, where we leverage interactive tangible game elements with diverse haptic characteristics to provide somatosensory training and foster recovery.

C. Moreira M, D. M. Pinheiro L, R. Pereira T, G. Carmona G, P. D. Freire J, A. I. Bastos J, Padilha Lanari Bo A. User-centered design and spatially-distributed sequential electrical stimulation in cycling for individuals with paraplegia

Background

In this work, we share the enhancements made in our system to take part in the CYBATHLON 2020 Global Edition Functional Electrical Stimulation (FES) Bike Race. Among the main improvements, firstly an overhaul, an overhaul of the system and user interface developed with User-centered design principles with remote access to enable telerehabilitation. Secondly, the implementation and experimental comparison between the traditional single electrode stimulation (SES) and spatially distributed sequential stimulation (SDSS) applied for FES Cycling.

Methods

We report on the main aspects of the developed system. To evaluate the user perception of the system, we applied a System Usability Scale (SUS) questionnaire. In comparing SDSS and SES, we collected data from one subject in four sessions, each simulating one race in the CYBATHLON format.

Results

User perception measured with SUS indicates a positive outcome in the developed system. The SDSS trials were superior in absolute and average values to SES regarding total distance covered and velocity. We successfully competed in the CYBATHLON 2020 Global Edition, finishing in 6th position in the FES Bike Race category.

Conclusions

The CYBATHLON format induced us to put the end-user in the center of our system design principle, which was well perceived. However, further improvements are required if the intention is to progress to a commercial product. FES Cycling performance in SDSS trials was superior when compared to SES trials, indicating that this technique may enable faster and possibly longer FES cycling sessions for individuals with paraplegia. More extensive studies are required to assess these aspects.

Neurorehabilitation From a Distance: Can Intelligent Technology Support Decentralized Access to Quality Therapy?

Current neurorehabilitation models primarily rely on extended hospital stays and regular therapy sessions requiring close physical interactions between rehabilitation professionals and patients. The current COVID-19 pandemic has challenged this model, as strict physical distancing rules and a shift in the allocation of hospital resources resulted in many neurological patients not receiving essential therapy. Accordingly, a recent survey revealed that the majority of European healthcare professionals involved in stroke care are concerned that this lack of care will have a noticeable negative impact on functional outcomes. COVID-19 highlights an urgent need to rethink conventional neurorehabilitation and develop alternative approaches to provide high-quality therapy while minimizing hospital stays and visits. Technology-based solutions, such as, robotics bear high potential to enable such a paradigm shift. While robot-assisted therapy is already established in clinics, the future challenge is to enable physically assisted therapy and assessments in a minimally supervized and decentralized manner, ideally at the patient’s home. Key enablers are new rehabilitation devices that are portable, scalable and equipped with clinical intelligence, remote monitoring and coaching capabilities. In this perspective article, we discuss clinical and technological requirements for the development and deployment of minimally supervized, robot-assisted neurorehabilitation technologies in patient’s homes. We elaborate on key principles to ensure feasibility and acceptance, and on how artificial intelligence can be leveraged for embedding clinical knowledge for safe use and personalized therapy adaptation. Such new models are likely to impact neurorehabilitation beyond COVID-19, by providing broad access to sustained, high-quality and high-dose therapy maximizing long-term functional outcomes.