A Novel Soft Robotic Supernumerary Hand for Severely Affected Stroke Patients

Quantifying patient experiences with therapeutic neurorehabilitation technologies: a scoping review

PURPOSE

Neurorehabilitation technologies are a novel approach to providing rehabilitation for patients with neurological conditions. There is a need to explore patient experiences. This study aimed; 1) To identify available questionnaires that assess patients' experiences with neurorehabilitation technologies, and 2) where reported, to document the psychometric properties of the identified questionnaires.

MATERIALS AND METHODS

Four databases were searched (Medline, Embase, Emcare and PsycInfo). The inclusion criteria were all types of primary data collection that included neurological patients of all ages who had experienced therapy with neurorehabilitation technologies and completed questionnaires to assess these experiences.

RESULTS

Eighty-eight publications were included. Fifteen different questionnaires along with many self-developed scales were identified. These were categorised as; 1) self-developed tools, 2) specific questionnaire for a particular technology, and 3) generic questionnaires originally developed for a different purpose. The questionnaires were used to assess various technologies, including virtual reality, robotics, and gaming systems. Most studies did not report any psychometric properties.

CONCLUSION

Many tools have been used to evaluate patient experiences, but few were specifically developed for neurorehabilitation technologies and psychometric data was limited. A preliminary recommendation would be use of the User Satisfaction Evaluation Questionnaire to evaluate patient experience with virtual reality systems.

EMG-Based Control Strategies of a Supernumerary Robotic Hand for the Rehabilitation of Sub-Acute Stroke Patients: Proof of Concept

One of the most frequent and severe aftermaths of a stroke is the loss of upper limb functionality. Therapy started in the sub-acute phase proved more effective, mainly when the patient participates actively. Recently, a novel set of rehabilitation and support robotic devices, known as supernumerary robotic limbs, have been introduced. This work investigates how a surface electromyography (sEMG) based control strategy would improve their usability in rehabilitation, limited so far by input interfaces requiring to subjects some level of residual mobility. After briefly introducing the phenomena hindering post-stroke sEMG and its use to control robotic hands, we describe a framework to acquire and interpret muscle signals of the forearm extensors. We applied it to drive a supernumerary robotic limb, the SoftHand-X, to provide Task-Specific Training (TST) in patients with sub-acute stroke. We propose and describe two algorithms to control the opening and closing of the robotic hand, with different levels of user agency and therapist control. We experimentally tested the feasibility of the proposed approach on four patients, followed by a therapist, to check their ability to operate the hand. The promising preliminary results indicate sEMG-based control as a viable solution to extend TST to sub-acute post-stroke patients.

A soft supernumerary hand for rehabilitation in sub-acute stroke: a pilot study

In patients with subacute stroke, task specific training (TST) has been shown to accelerate functional recovery of the upper limb. However, many patients do not have sufficient active extension of the fingers to perform this treatment. In these patients, here we propose a new rehabilitation technique in which TST is performed through a soft robotic hand (SoftHand-X). In short, the extension of the robotic fingers is controlled by the patient through his residual, albeit minimal, active extension of the fingers or wrist, while the patient was required to relax the muscles to achieve full flexion of the robotic fingers. TST with SoftHand-X was attempted in 27 subacute stroke patients unable to perform TST due to insufficient active extension of the fingers. Four patients (14.8%) were able to perform the proposed treatment (10 daily sessions of 60 min each). They reported an excellent level of participation. After the treatment, both clinical score of spasticity and its electromyographic correlate (stretch reflex) decreased. In subacute stroke patients, TST using SoftHand-X is a well-accepted treatment, resulting in a decrease of spasticity. At present, it can be applied only in a small proportion of the patients who cannot perform conventional TST, though extensions are possible.

More than surgical tools: a systematic review of robots as didactic tools for the education of professionals in health sciences

Within the field of robots in medical education, most of the work done during the last years has focused on surgeon training in robotic surgery, practicing surgery procedures through simulators. Apart from surgical education, robots have also been widely employed in assistive and rehabilitation procedures, where education has traditionally focused in the patient. Therefore, there has been extensive review bibliography in the field of medical robotics focused on surgical and rehabilitation and assistive robots, but there is a lack of survey papers that explore the potential of robotics in the education of healthcare students and professionals beyond their training in the use of the robotic system. The scope of the current review are works in which robots are used as didactic tools for the education of professionals in health sciences, investigating the enablers and barriers that affect the use of robots as learning facilitators. Systematic literature searches were conducted in WOS and Scopus, yielding a total of 3812 candidate papers. After removing duplicates, inclusion criteria were defined and applied, resulting in 171 papers. An in-depth quality assessment was then performed leading to 26 papers for qualitative synthesis. Results show that robots in health sciences education are still developed with a roboticist mindset, without clearly incorporating aspects of the teaching/learning process. However, they have proven potential to be used in health sciences as they allow to parameterize procedures, autonomously guide learners to achieve greater engagement, or enable collective learning including patients and instructors "in the loop". Although there exist documented added-value benefits, further research and efforts needs to be done to foster the inclusion of robots as didactic tools in the curricula of health sciences professionals. On the one hand, by analyzing how robotic technology should be developed to become more flexible and usable to support both teaching and learning processes in health sciences education, as final users are not necessarily well-versed in how to use it. On the other, there continues to be a need to develop effective and standard robotic enhanced learning evaluation tools, as well good quality studies that describe effective evaluation of robotic enhanced education for professionals in health sciences. As happens with other technologies when applied to the health sciences field, studies often fail to provide sufficient detail to support transferability or direct future robotic health care education programs.

Predictive nomogram for soft robotic hand rehabilitation of patients with intracerebral hemorrhage

Background

Few studies focused on the risk factors for hand rehabilitation of intracerebral hemorrhage (ICH) using of soft robotic hand therapy (SRHT). The aim of this study was to establish a predictive nomogram for soft robotic hand rehabilitation in patients with ICH.

Methods

According to the Brunnstrom motor recovery (BMR) stage, the patients were grouped into poor and good motor function groups. The data of patient demographic information and serum level of C-terminal Agrin Fragment (CAF), S100B and neurofilament light (NfL) were collected. The logistic regression was used to analyze the risk factors for poor hand function.

Results

Finally, we enrolled 102 and 103 patients in the control and SRHT groups. For the SRHT group, there were 17 and 86 cases with poor and good motor function at 6-months follow-up respectively. In the good motor function group, the Fugl-Meyer Assessment-Wrist and Hand (FMA-WH score) and BMR score at admission were all better than that in the poor motor function group respectively (p < 0.001). The mean serum level of CAF, S100B and NfL in the good motor function group were 2.5 ± 0.82 ng/mL, 286.6 ± 236.4 ng/L and 12.1 ± 10.4 pg/mL respectively, which were lower than that in the poor motor function group (p < 0.001, Table 3). The multivariate logistic regression showed that hematoma volume (OR = 1.47, p = 0.007), FMA-WH score admission (OR = 0.78, p = 0.02), S100B (OR = 1.32, p = 0.04), and NfL (OR = 1.24, p = 0.003) were all significant predictors of poor motor function.

Conclusions

We found that Soft robotic hands therapy benefited in hand function in patients with ICH and hematoma volume, FMA-WH score admission, S100B, and NfL were all significant predictors for poor motor function of patients with ICH.

Wearable Supernumerary Robotic Limb System Using a Hybrid Control Approach Based on Motor Imagery and Object Detection

Motor disorder of upper limbs has seriously affected the daily life of the patients with hemiplegia after stroke. We developed a wearable supernumerary robotic limb (SRL) system using a hybrid control approach based on motor imagery (MI) and object detection for upper-limb motion assistance. SRL system included an SRL hardware subsystem and a hybrid control software subsystem. The system obtained the patient's motion intention through MI electroencephalogram (EEG) recognition method based on graph convolutional network (GCN) and gated recurrent unit network (GRU) to control the left and right movements of SRL, and the object detection technology was used together for a quick grasp of target objects to compensate for the disadvantages when using MI EEG alone like fewer control instructions and lower control efficiency. Offline training experiment was designed to obtain subjects' MI recognition models and evaluate the feasibility of the MI EEG recognition method; online control experiment was designed to verify the effectiveness of our wearable SRL system. The results showed that the proposed MI EEG recognition method (GCN+GRU) could effectively improve the MI classification accuracy (90.04% ± 2.36%) compared with traditional methods; all subjects were able to complete the target object grasping tasks within 23 seconds by controlling the SRL, and the highest average grasping success rate achieved 90.67% in bag grasping task. The SRL system can effectively assist people with upper-limb motor disorder to perform upper-limb tasks in daily life by natural human-robot interaction, and improve their ability of self-help and enhance their confidence of life.

Integrated Gait Triggered Mixed Reality and Neurophysiological Monitoring as a Framework for Next-Generation Ambulatory Stroke Rehabilitation

Brain stroke affects millions of people in the world every year, with 50 to 60 percent of stroke survivors suffering from functional disabilities, for which early and sustained post-stroke rehabilitation is highly recommended. However, approximately one third of stroke patients do not receive early in hospital rehabilitation programs due to insufficient medical facilities or lack of motivation. Gait triggered mixed reality (GTMR) is a cognitive-motor dual task with multisensory feedback tailored for lower-limb post-stroke rehabilitation, which we propose as a potential method for addressing these rehabilitation challenges. Simultaneous gait and EEG data from nine stroke patients was recorded and analyzed to assess the applicability of GTMR to different stroke patients, determine any impacts of GTMR on patients, and better understand brain dynamics as stroke patients perform different rehabilitation tasks. Walking cadence improved significantly for stroke patients and lower-limb movement induced alpha band power suppression during GTMR tasks. The brain dynamics and gait performance across different severities of stroke motor deficits was also assessed; the intensity of walking induced event related desynchronization (ERD) was found to be related to motor deficits, as classified by Brunnstrom stage. In particular, stronger lower-limb movement induced ERD during GTMR rehabilitation tasks was found for patients with moderate motor deficits (Brunnstrom stage IV). This investigation demonstrates the efficacy of the GTMR paradigm for enhancing lower-limb rehabilitation, explores the neural activities of cognitive-motor tasks in different stages of stroke, and highlights the potential for joining enhanced rehabilitation and real-time neural monitoring for superior stroke rehabilitation.

Analysis of Compensatory Movements Using a Supernumerary Robotic Hand for Upper Limb Assistance

Recently, extratheses, aka Supernumerary Robotic Limbs (SRLs), are emerging as a new trend in the field of assistive and rehabilitation devices. We proposed the SoftHand X, a system composed of an anthropomorphic soft hand extrathesis, with a gravity support boom and a control interface for the patient. In preliminary tests, the system exhibited a positive outlook toward assisting impaired people during daily life activities and fighting learned-non-use of the impaired arm. However, similar to many robot-aided therapies, the use of the system may induce side effects that can be detrimental and worsen patients' conditions. One of the most common is the onset of alternative grasping strategies and compensatory movements, which clinicians absolutely need to counter in physical therapy. Before embarking in systematic experimentation with the SoftHand X on patients, it is essential that the system is demonstrated not to lead to an increase of compensation habits. This paper provides a detailed description of the compensatory movements performed by healthy subjects using the SoftHand X. Eleven right-handed healthy subjects were involved within an experimental protocol in which kinematic data of the upper body and EMG signals of the arm were acquired. Each subject executed tasks with and without the robotic system, considering this last situation as reference of optimal behavior. A comparison between two different configurations of the robotic hand was performed to understand if this aspect may affect the compensatory movements. Results demonstrated that the use of the apparatus reduces the range of motion of the wrist, elbow and shoulder, while it increases the range of the trunk and head movements. On the other hand, EMG analysis indicated that muscle activation was very similar among all the conditions. Results obtained suggest that the system may be used as assistive device without causing an over-use of the arm joints, and opens the way to clinical trials with patients.