Discernment on assistive technology for the care and support requirements of older adults and differently-abled individuals.

Assistive technology for the differently abled and older adults has made remarkable achievements in providing rehabilitative, adaptive, and assistive devices. It provides huge assistance for people with physical impairments to lead a better self-reliant daily life, in terms of mobility, education, rehabilitation, etc. This technology ranges from simple hand-held devices to complex robotic accessories which promote the individual's independence. This study aimed at identifying the assistance required by differently-abled individuals, and the solutions proposed by different researchers, and reviewed their merits and demerits. It provides a detailed discussion on the state of art assistive technologies, their applications, challenges, types, and their usage for rehabilitation. The study also identifies different unexplored research areas related to assistive technology that can improve the daily life of individuals and advance the field. Despite their high usage, assistive technologies have some limitations which have been briefly described in the study. This review, therefore, can help understand the utilization, and pros and cons of assistive devices in rehabilitation engineering and assistive technologies.

Mini-review: Rehabilitation engineering: Research priorities and trends.

Rehabilitation Engineering is the use of engineering principles applied to rehabilitation, disability, and independent living. Google Scholar is a searchable resource that allows people from around the world to create profiles of their interests and collaborations, and it provides a means to search the broad scientific and technical literature. Google Scholar was used to identify the 150 most cited people who listed Rehabilitation Engineering in their profile. Research impact, characteristics, and areas of research of the most cited rehabilitation engineers were examined. Furthermore, gender and geographical differences in research metrics of the highest citied rehabilitation engineers were investigated. Consumer priorities in rehabilitation engineering were identified using a voice of consumer (VoC) survey and recent literature based on VoC studies. Gaps between research publication and activities and consumer priorities were identified to recommend seven areas of research with high demand and opportunity for growth and innovation. Implications.

Salzburg Visual Field Trainer (SVFT): A virtual reality device for (the evaluation of) neuropsychological rehabilitation.

OBJECTIVE: "Visual Restitution Therapies" (VRT) claim to ameliorate visual field defects of neurological patients by repeated visual light stimulation, leading to training-related neuroplasticity and resulting in reconnection of lesioned neurons in early cortical areas. Because existing systems are stationary, uncomfortable, and unreliable, we developed a training instrument based on virtual reality goggles. The goal of the "Salzburg Visual Field Trainer" (SVFT) is twofold: (1) The device facilitates the clinical evaluation of established neuropsychological rehabilitation approaches, such as VRT. (2) The device enables patients to independently perform VRT based (or other) neuropsychological training methodologies flexibly and comfortably. METHODS AND ANALYSIS: The SVFT was developed on the principles of VRT. Individual configuration of the SVFT is based on perimetric data of the respective patient's visual field. To validate the utmost important aspect of neuropsychological rehabilitation methodologies-that is displaying stimuli precisely in desired locations in the user's visual field-two steps were conducted in this proof-of-concept study: First, we assessed the individual "blind spots" location and extent of 40 healthy, normal sighted participants. This was done with the help of our recently developed perimetric methodology "Eye Tracking Based Visual Field Analysis" (EFA). Second, depending on the individual characteristics of every participant's blind spots, we displayed-by means of the SVFT-15 stimuli in the respective locations of every participants' blind spots and 85 stimuli in the surrounding, intact visual area. The ratio between visible and non-visible stimuli, which is reflected in the behavioral responses (clicks on a remote control) of the 40 participants, provides insight into the accuracy of the SVFT to display training stimuli in areas desired by the investigator. As the blind spot is a naturally occurring, absolute scotoma, we utilized this blind area as an objective criterion and a "simulated" visual field defect to evaluate the theoretical applicability of the SVFT. RESULTS: Outcomes indicate that the SVFT is highly accurate in displaying training stimuli in the desired areas of the user's visual field with an accuracy of 99.0%. Data analysis further showed a sensitivity of .98, specificity of .99, a positive predictive value of .96, a negative predictive value of .996, a hit rate of .99, a random hit rate of .74 and a RATZ-Index of .98. This translates to 14.7% correct non-reactions, 0.7% false non-reactions, 0.3% false reactions and 84.3% correct reactions to displayed test stimuli during the evaluation study. Reports from participants further indicate that the SVFT is comfortable to wear and intuitive to use. CONCLUSIONS: The SVFT can help to investigate the true effects of VRT based methodologies (or other neuropsychological approaches) and the underlying mechanisms of training-related neuroplasticity in the visual cortex in neurological patients suffering from visual field defects.

Nonimmersive Virtual Reality as Complementary Rehabilitation on Functional Mobility and Gait in Cerebral Palsy: A Randomized Controlled Clinical Trial.

Objective: This study aimed to investigate the effects of nonimmersive virtual reality (VR) as complementary rehabilitation on functional mobility and gait in children with mild unilateral cerebral palsy (CP). Methods: Prospective, randomized, controlled, clinical trial. Twenty-two children with unilateral CP were randomized into two groups: intervention group (IG) (n = 11) and control group (n = 11). After baseline assessments, the participants either started the VR intervention (IG) associated with conventional therapy, or continued conventional physical therapy (control group). Participants in the IG attended 45-minute training sessions twice a week for 8 weeks (total: 16 sessions and 12 hours of training). Participants in the control group underwent standard therapy for 50 minutes, twice a week. Timed Up and Go test (TUG), gait spatiotemporal variables, and pelvic angles were measured at baseline and after treatment sessions. Results: When compared with the control group, the IG performed the following activities in decreased time: TUG, and stride time. Also, the IG increased the velocity of walking and the pelvis retroversion, and decreased the pelvis interval/external rotations and amplitude of pelvis rotation while walking. Conclusions: A rehabilitative approach based on a nonimmersive VR as complementary rehabilitation may improve functional mobility and change joint mobility functions during gait of children with mild unilateral CP. The results of the study demonstrate that the insertion of a therapy based on VR may help in better strategies in the gait of children with CP. Thus, rehabilitation professionals can use this tool combined with conventional therapy.

Effects of pulmonary rehabilitation training based on WeChat App on pulmonary function, adverse mood and quality of life of COVID-19 patients: A protocol for systematic review and meta-analysis.

BACKGROUND: Coronavirus disease 2019 (COVID-19) as a fatal epidemic has swept across the world, especially in India where the epidemic situation is the most serious. For COVID-19 patients, pulmonary rehabilitation training plays a significant role. However, it is still a controversial issue regarding the efficacy of WeChat APP-based pulmonary rehabilitation training in improving lung function, quality of life and bad mood of COVID-19 patients. To clarify this issue, a meta-analysis was conducted in this present study, so as to provide a basis for rehabilitation guidance of COVID-19 patients. METHODS: We systematically searched PubMed, medRxiv, Web of Science, Scopus, Chinese Science Citation Database, China National Knowledge Infrastructure, Chinese Biomedical Literature Database, Chinese Scientific Journal Database, and Wan-fang databases in May 2021 to identify randomized controlled trials and evaluate the effects of WeChat APP-based pulmonary rehabilitation training for COVID-19. Two researchers independently carried out data extraction. On the other hand, literature quality evaluation on the quality and meta-analysis of the included literature was performed with Revman5.3 software. RESULTS: The results of this meta-analysis will be submitted to a peer-reviewed journal for publication. CONCLUSION: This study will provide reliable evidence-based evidence on the effects of WeChat APP-based pulmonary rehabilitation training on lung function, bad mood, and quality of life in patients with COVID-19. ETHICS AND DISSEMINATION: Ethical approval was not required for this study. The systematic review will be published in a peer-reviewed journal, presented at conferences, and shared on social media platforms. OSF REGISTRATION NUMBER: DOI 10.17605/OSF.IO/MKXCH.

Development and Application of Medicine-Engineering Integration in the Rehabilitation of Traumatic Brain Injury.

The rapid progress of the combination of medicine and engineering provides better chances for the clinical treatment and healthcare engineering. Traumatic brain injury (TBI) and its related symptoms have become a major global health problem. At present, these techniques has been widely used in the rehabilitation of TBI. In this review article, we summarizes the progress of the combination of medicine and industry in the rehabilitation of traumatic brain injury in recent years, mainly from the following aspects: artificial intelligence (AI), brain-computer interfaces (BCI), noninvasive brain stimulation (NIBS), and wearable-assisted devices. We believe the summary of this article can improve insight into the combination of medicine and industry in the rehabilitation of traumatic brain injury.

Development of the Ultralight Hybrid Pneumatic Artificial Muscle: Modelling and optimization.

Pneumatic artificial muscles (PAMs) are one of the key technologies in soft robotics, and they enable actuation in mobile robots, in wearable devices and exoskeletons for assistive and rehabilitative purposes. While they recently showed relevant improvements, they still present quite low payload, limited bandwidth, and lack of repeatability, controllability and robustness. Vacuum-based actuation has been recently demonstrated as a very promising solution, and many challenges are still open, like generating at the same time a large contraction ratio, and a high blocking force with enhanced axial stiffness. In this paper, a novel Ultralight Hybrid PAM (UH-PAM), based on bellow-type elastomeric skin and vacuum actuation, is presented. In particular, open-cell foam is exploited as a structural backbone, together with plastic rings, all embedded in a thin skin. The design and optimization combine numerical, analytical, and experimental data. Both static and dynamic analysis are performed. The weight of the optimized actuator is only 20 g. Nevertheless, a contraction ratio up to 50% and a maximum payload of 3 kg can be achieved. From a dynamic point of view, a rise time of 0.5 s for the contraction phase is observed. Although hysteresis is significant when using the whole contraction span, it can be reduced (down to 11.5%) by tuning both the vacuum range and the operating frequency for cyclic movements. Finally, to demonstrate the potentiality of this soft actuation approach, a 3 DoFs Stewart platform is built. The feasibility of performing smooth movements by exploiting open-loop control is shown through simple and more complex handwriting figures projected on the XY plane.

Mechatronics design and testing of a cable-driven upper limb rehabilitation exoskeleton with variable stiffness.

In this paper, we present a cable-driven exoskeleton with variable stiffness for upper limb rehabilitation. Adjustable stiffness of the cable-driven exoskeleton is achieved by attaching a novel variable stiffness module (VSM) to each driving cable. The module is able to vary stiffness in a large range through changing cable tension. In this paper, a stiffness model is developed for a cable-driven exoskeleton to reveal the stiffness performance of the exoskeleton with the influence of VSMs. Based on the stiffness model, a controller with stiffness-oriented strategy is proposed to vary the stiffness of the exoskeleton. Experiments on a prototype of a cable-driven exoskeleton are conducted to validate the controller.

Adaptive sliding-mode controller of a lower limb mobile exoskeleton for active rehabilitation.

This study describes the design, instrumentation and control of an exoskeleton for lower limb children rehabilitation with nine degrees of freedom. Three degrees of freedom in each leg exert the movements of hip, knee and ankle in the sagittal plane, and three control the drive track system composed by a caterpillar-like robot. The control scheme presents a model free decentralized output feedback adaptive high-order sliding mode control to solve the trajectory tracking problem in each degree of freedom of the exoskeleton. A high order sliding mode differentiator estimates the unmeasured states and, by means of a dynamical state extension, it approximates the unknown dynamical model of the exoskeleton. A second-order adaptive sliding mode controller based on the super-twisting algorithm drives the exoskeleton articulations to track the proposed reference trajectories, inducing an ultimate boundedness for the tracking error. Numerical and experimental simulation results demonstrate the effect of the adaptive gain on the super-twisting control design. Such evaluations confirmed the superior tracking performance forced by the adaptive law for the controller with a smaller chattering amplitude and smaller mean tracking error.

Evaluation of Patient Motivation and Satisfaction During Technology-Assisted Rehabilitation: An Experiential Review.

Objective: The aim of this experiential review is to explore the state of the art of the literature regarding the evaluation tools available for assessment of patient motivation and satisfaction during technology-assisted rehabilitation (robot rehabilitation, virtual reality rehabilitation, and serious games rehabilitation). Materials and Methods: A systematic search of the peer-reviewed literature published from January 1990 to August 2019 was conducted. The protocol for this review was registered in PROSPERO and carried out in accordance with the PRISMA recommendations. Results: The search of PubMed, PsycINFO, Scopus, and Web of Science databases identified a total of 333 records. After adjusting for duplicates and other inclusion criteria, 69 studies were selected for inclusion in the review. We found that authors used a wide range of dedicated questionnaires and, in about 50% of studies, a few validated tools to assess motivation and satisfaction during technology-assisted rehabilitation. The instruments most used were the Intrinsic Motivation Inventory (IMI), Quebec User Evaluation of Satisfaction with Assistive Technology (QUEST 2.0), and the Usefulness, Satisfaction, and Ease of use (USE) scale. Motivation and satisfaction were generally portrayed as multidimensional concepts; overall, 29 domains were assessed by 9 different tools. Conclusion: The tools used in the current literature to assess patient motivation and satisfaction during technology-assisted rehabilitation are quite variegated, but we would recommend use of the IMI and USE questionnaires based on their widespread diffusion. However, the choice of domains explored and number of items calls for harmonization. Ideally, this should be a joint task for the whole scientific community.

Novel adaptive impedance control for exoskeleton robot for rehabilitation using a nonlinear time-delay disturbance observer.

A new adaptive impedance, augmented with backstepping control, time-delay estimation, and a disturbance observer, was designed to perform passive-assistive rehabilitation motion. This was done using a rehabilitation robot whereby humans' musculoskeletal conditions were considered. This control scheme aimed to mimic the movement behavior of the user and to provide an accurate compensation for uncertainties and torque disturbances. Such disturbances were excited by constraints of input saturation of the robot's actuators, friction forces and backlash, several payloads of the attached upper-limb of each patient, and time delay errors. The designed impedance control algorithm would transfer the stiffness of the human upper limb to the developed impedance model via the measured user force. In the proposed control scheme, active rejection of disturbances would be achieved through the direct connection between such disturbances from the observer's output and the control input via the feedforward loop of the system. Furthermore, the computed control input does not require any precise knowledge of the robot's dynamic model or any knowledge of built-in torque-sensing units to provide the desirable physiotherapy treatment. Experimental investigations performed by two subjects were exhibited to support the benefits of the designed approach.

Fall inducing movable platform (FIMP) for overground trips and slips.

BACKGROUND: The study of falls and fall prevention/intervention devices requires the recording of true falls incidence. However, true falls are rare, random, and difficult to collect in real world settings. A system capable of producing falls in an ecologically valid manner will be very helpful in collecting the data necessary to advance our understanding of the neuro and musculoskeletal mechanisms underpinning real-world falls events. METHODS: A fall inducing movable platform (FIMP) was designed to arrest or accelerate a subject's ankle to induce a trip or slip. The ankle was arrested posteriorly with an electromagnetic brake and accelerated anteriorly with a motor. A power spring was connected in series between the ankle and the brake/motor to allow freedom of movement (system transparency) when a fall is not being induced. A gait phase detection algorithm was also created to enable precise activation of the fall inducing mechanisms. Statistical Parametric Mapping (SPM1D) and one-way repeated measure ANOVA were used to evaluate the ability of the FIMP to induce a trip or slip. RESULTS: During FIMP induced trips, the brake activates at the terminal swing or mid swing gait phase to induce the lowering or skipping strategies, respectively. For the lowering strategy, the characteristic leg lowering and subsequent contralateral leg swing was seen in all subjects. Likewise, for the skipping strategy, all subjects skipped forward on the perturbed leg. Slip was induced by FIMP by using a motor to impart unwanted forward acceleration to the ankle with the help of friction-reducing ground sliding sheets. Joint stiffening was observed during the slips, and subjects universally adopted the surfing strategy after the initial slip. CONCLUSION: The results indicate that FIMP can induce ecologically valid falls under controlled laboratory conditions. The use of SPM1D in conjunction with FIMP allows for the time varying statistical quantification of trip and slip reactive kinematics events. With future research, fall recovery anomalies in subjects can now also be systematically evaluated through the assessment of other neuromuscular variables such as joint forces, muscle activation and muscle forces.

Head-Mounted Display-Based Application for Cognitive Training.

Virtual Reality (VR) has had significant advances in rehabilitation, due to the gamification of cognitive activities that facilitate treatment. On the other hand, Immersive Virtual Reality (IVR) produces outstanding results due to the interactive features with the user. This work introduces a VR application for memory rehabilitation by walking through a maze and using the Oculus Go head-mounted display (HMD) technology. The mechanics of the game require memorizing geometric shapes while the player progresses in two modes, autonomous or manual, with two levels of difficulty depending on the number of elements to remember. The application is developed in the Unity 3D video game engine considering the optimization of computational resources to improve the performance in the processing and maintaining adequate benefits for the user, while the generated data is stored and sent to a remote server. The maze task was assessed with 29 subjects in a controlled environment. The obtained results show a significant correlation between participants' response accuracy in both the maze task and a face-pair test. Thus, the proposed task is able to perform memory assessments.

Implementation of Wearable Sensing Technology for Movement: Pushing Forward into the Routine Physical Rehabilitation Care Field.

While the promise of wearable sensor technology to transform physical rehabilitation has been around for a number of years, the reality is that wearable sensor technology for the measurement of human movement has remained largely confined to rehabilitation research labs with limited ventures into clinical practice. The purposes of this paper are to: (1) discuss the major barriers in clinical practice and available wearable sensing technology; (2) propose benchmarks for wearable device systems that would make it feasible to implement them in clinical practice across the world and (3) evaluate a current wearable device system against the benchmarks as an example. If we can overcome the barriers and achieve the benchmarks collectively, the field of rehabilitation will move forward towards better movement interventions that produce improved function not just in the clinic or lab, but out in peoples' homes and communities.

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.

An LSTM-Based Prediction Method for Lower Limb Intention Perception by Integrative Analysis of Kinect Visual Signal.

Recently, computer vision and deep learning technology has been applied in various gait rehabilitation researches. Considering the long short-term memory (LSTM) network has been proved an excellent performance in learn sequence feature representations, we proposed a lower limb joint trajectory prediction method based on LSTM for conducting active rehabilitation on a rehabilitation robotic system. Our approach based on synergy theory exploits that the follow-up lower limb joint trajectory, i.e. limb intention, could be generated by joint angles of the previous swing process of upper limb which were acquired from Kinect platform, an advanced computer vision platform for motion tracking. A customize Kinect-Treadmill data acquisition platform was built for this study. With this platform, data acquisition on ten healthy subjects is processed in four different walking speeds to acquire the joint angles calculated by Kinect visual signals of upper and lower limb swing. Then, the angles of hip and knee in one side which were presented as lower limb intentions are predicted by the fore angles of the elbow and shoulder on the opposite side via a trained LSTM model. The results indicate that the trained LSTM model has a better estimation of predicting the lower limb intentions, and the feasibility of Kinect visual signals has been validated as well.

Improved Active Disturbance Rejection Control for Trajectory Tracking Control of Lower Limb Robotic Rehabilitation Exoskeleton.

Neurological disorders such as cerebral paralysis, spinal cord injuries, and strokes, result in the impairment of motor control and induce functional difficulties to human beings like walking, standing, etc. Physical injuries due to accidents and muscular weaknesses caused by aging affect people and can cause them to lose their ability to perform daily routine functions. In order to help people recover or improve their dysfunctional activities and quality of life after accidents or strokes, assistive devices like exoskeletons and orthoses are developed. Control strategies for control of exoskeletons are developed with the desired intention of improving the quality of treatment. Amongst recent control strategies used for rehabilitation robots, active disturbance rejection control (ADRC) strategy is a systematic way out from a robust control paradox with possibilities and promises. In this modern era, we always try to find the solution in order to have minimum resources and maximum output, and in robotics-control, to approach the same condition observer-based control strategies is an added advantage where it uses a state estimation method which reduces the requirement of sensors that is used for measuring every state. This paper introduces improved active disturbance rejection control (I-ADRC) controllers as a combination of linear extended state observer (LESO), tracking differentiator (TD), and nonlinear state error feedback (NLSEF). The proposed controllers were evaluated through simulation by investigating the sagittal plane gait trajectory tracking performance of two degrees of freedom, Lower Limb Robotic Rehabilitation Exoskeleton (LLRRE). This multiple input multiple output (MIMO) LLRRE has two joints, one at the hip and other at the knee. In the simulation study, the proposed controllers show reduced trajectory tracking error, elimination of random, constant, and harmonic disturbances, robustness against parameter variations, and under the influence of noise, with improvement in performance indices, indicates its enhanced tracking performance. These promising simulation results would be validated experimentally in the next phase of research.

Polymer Optical Fiber-Based Integrated Instrumentation in a Robot-Assisted Rehabilitation Smart Environment: A Proof of Concept.

Advances in robotic systems for rehabilitation purposes have led to the development of specialized robot-assisted rehabilitation clinics. In addition, advantageous features of polymer optical fiber (POF) sensors such as light weight, multiplexing capabilities, electromagnetic field immunity and flexibility have resulted in the widespread use of POF sensors in many areas. Considering this background, this paper presents an integrated POF intensity variation-based sensor system for the instrumentation of different devices. We consider different scenarios for physical rehabilitation, resembling a clinic for robot-assisted rehabilitation. Thus, a multiplexing technique for POF intensity variation-based sensors was applied in which an orthosis for flexion/extension movement, a modular exoskeleton for gait assistance and a treadmill were instrumented with POF angle and force sensors, where all the sensors were integrated in the same POF system. In addition, wearable sensors for gait analysis and physiological parameter monitoring were also proposed and applied in gait exercises. The results show the feasibility of the sensors and methods proposed, where, after the characterization of each sensor, the system was implemented with three volunteers: one for the orthosis on the flexion/extension movements, one for the exoskeleton for gait assistance and the other for the free gait analysis using the proposed wearable POF sensors. To the authors' best knowledge, this is the first time that optical fiber sensors have been used as a multiplexed and integrated solution for the simultaneous assessment of different robotic devices and rehabilitation protocols, where such an approach results in a compact, fully integrated and low-cost system, which can be readily employed in any clinical environment.