Accelerometry-enabled measurement of walking performance with a robotic exoskeleton: a pilot study

Exoskeleton-Assisted Rehabilitation and Neuroplasticity in Spinal Cord Injury

Spinal cord injury (SCI) results in neurological deficits below the level of injury, causing motor dysfunction and various severe multisystem complications. Rehabilitative training plays a crucial role in the recovery of individuals with SCI, and exoskeleton serves as an emerging and promising tool for rehabilitation, especially in promoting neuroplasticity and alleviating SCI-related complications. This article reviews the classifications and research progresses of medical exoskeletons designed for SCI patients and describes their performances in practical application separately. Meanwhile, we discuss their mechanisms for enhancing neuroplasticity and functional remodeling, as well as their palliative impacts on secondary complications. The potential trends in exoskeleton design are raised according to current progress and requirements on SCI rehabilitation.

Use of Lower Limb Exoskeletons as an Assessment Tool for Human Motor Performance: A Systematic Review

Exoskeletons are a promising tool to support individuals with a decreased level of motor performance. Due to their built-in sensors, exoskeletons offer the possibility of continuously recording and assessing user data, for example, related to motor performance. The aim of this article is to provide an overview of studies that rely on using exoskeletons to measure motor performance. Therefore, we conducted a systematic literature review, following the PRISMA Statement guidelines. A total of 49 studies using lower limb exoskeletons for the assessment of human motor performance were included. Of these, 19 studies were validity studies, and six were reliability studies. We found 33 different exoskeletons; seven can be considered stationary, and 26 were mobile exoskeletons. The majority of the studies measured parameters such as range of motion, muscle strength, gait parameters, spasticity, and proprioception. We conclude that exoskeletons can be used to measure a wide range of motor performance parameters through built-in sensors, and seem to be more objective and specific than manual test procedures. However, since these parameters are usually estimated from built-in sensor data, the quality and specificity of an exoskeleton to assess certain motor performance parameters must be examined before an exoskeleton can be used, for example, in a research or clinical setting.

Efficacy of Robot-Assisted Gait Training Combined with Robotic Balance Training in Subacute Stroke Patients: A Randomized Clinical Trial

Recently, the use of robotic technology in gait and balance rehabilitation of stroke patients has been introduced, with positive results. The purpose of this study was to evaluate the effectiveness of robotic gait and trunk rehabilitation compared to robotic gait training alone on balance, activities, and participation measures in patients with subacute stroke. The study was a randomized, controlled, single blind, parallel group clinical trial. Thirty-six patients with first ischemic or hemorrhagic stroke event were enrolled, and they were randomized in two groups: Gait Group (GG), where they received only robotic treatment for gait rehabilitation through an end-effector system, and Gait/Trunk Group (GTG) where they performed end-effector gait rehabilitation and balance with a robotic platform, 3 times/week for 12 sessions/month. At the end of the study, there was an improvement in balance ability in both groups. Instead, the lower limb muscle strength and muscle tone significantly improved only in the GTG group, where we found a significant reduction in the trunk oscillations and displacement during dynamic exercises more than the GG group. The robotic platform which was added to the gait robotic treatment offers more intense and controlled training of the trunk that positively influences the tone and strength of lower limb muscles.

Overground robotic training effects on walking and secondary health conditions in individuals with spinal cord injury: systematic review

Overground powered lower limb exoskeletons (EXOs) have proven to be valid devices in gait rehabilitation in individuals with spinal cord injury (SCI). Although several articles have reported the effects of EXOs in these individuals, the few reviews available focused on specific domains, mainly walking. The aim of this systematic review is to provide a general overview of the effects of commercial EXOs (i.e. not EXOs used in military and industry applications) for medical purposes in individuals with SCI. This systematic review was conducted following the PRISMA guidelines and it referred to MED-LINE, EMBASE, SCOPUS, Web of Science and Cochrane library databases. The studies included were Randomized Clinical Trials (RCTs) and non-RCT based on EXOs intervention on individuals with SCI. Out of 1296 studies screened, 41 met inclusion criteria. Among all the EXO studies, the Ekso device was the most discussed, followed by ReWalk, Indego, HAL and Rex devices. Since 14 different domains were considered, the outcome measures were heterogeneous. The most investigated domain was walking, followed by cardiorespiratory/metabolic responses, spasticity, balance, quality of life, human–robot interaction, robot data, bowel functionality, strength, daily living activity, neurophysiology, sensory function, bladder functionality and body composition/bone density domains. There were no reports of negative effects due to EXOs trainings and most of the significant positive effects were noted in the walking domain for Ekso, ReWalk, HAL and Indego devices. Ekso studies reported significant effects due to training in almost all domains, while this was not the case with the Rex device. Not a single study carried out on sensory functions or bladder functionality reached significance for any EXO. It is not possible to draw general conclusions about the effects of EXOs usage due to the lack of high-quality studies as addressed by the Downs and Black tool, the heterogeneity of the outcome measures, of the protocols and of the SCI epidemiological/neurological features. However, the strengths and weaknesses of EXOs are starting to be defined, even considering the different types of adverse events that EXO training brought about. EXO training showed to bring significant improvements over time, but whether its effectiveness is greater or less than conventional therapy or other treatments is still mostly unknown. High-quality RCTs are necessary to better define the pros and cons of the EXOs available today. Studies of this kind could help clinicians to better choose the appropriate training for individuals with SCI.

Performance Evaluation of Lower Limb Exoskeletons: A Systematic Review

Benchmarks have long been used to verify and compare the readiness level of different technologies in many application domains. In the field of wearable robots, the lack of a recognized benchmarking methodology is one important impediment that may hamper the efficient translation of research prototypes into actual products. At the same time, an exponentially growing number of research studies are addressing the problem of quantifying the performance of robotic exoskeletons, resulting in a rich and highly heterogeneous picture of methods, variables and protocols. This review aims to organize this information, and identify the most promising performance indicators that can be converted into practical benchmarks. We focus our analysis on lower limb functions, including a wide spectrum of motor skills and performance indicators. We found that, in general, the evaluation of lower limb exoskeletons is still largely focused on straight walking, with poor coverage of most of the basic motor skills that make up the activities of daily life. Our analysis also reveals a clear bias towards generic kinematics and kinetic indicators, in spite of the metrics of human-robot interaction. Based on these results, we identify and discuss a number of promising research directions that may help the community to attain a comprehensive benchmarking methodology for robot-assisted locomotion more efficiently.

A Brief Review on the Sensor Measurement Solutions for the Ten-Meter Walk Test

The wide-spread use of wearables and the adoption of the Internet of Things (IoT) paradigm provide an opportunity to use mobile-device sensors for medical applications. Sensors available in the commonly used devices may inspire innovative solutions for physiotherapy striving for accurate and early identification of various pathologies. An essential and reliable performance measure is the ten-meter walk test, which is employed to determine functional mobility, gait, and vestibular function. Sensor-based approaches can identify the various test phases and their segmented duration, among other parameters. The measurement parameter primarily used is related to the tests’ duration, and after identifying patterns, a variety of physical treatments can be recommended. This paper reviews multiple studies focusing on automated measurements of the ten-meter walk test with different sensors. Most of the analyzed studies measure similar parameters as traditional methods, such as velocity, duration, and other involuntary and dangerous patients’ movements after stroke. That provides an opportunity to measure different parameters that can be later fed into machine learning models for analyzing more complex patterns.

Wearable rehabilitation exoskeletons of the lower limb: analysis of versatility and adaptability

PURPOSE

To analyse the versatility and adaptability of commercially available exoskeletons for mobility assistance and their adaptation to diverse pathologies through a review of clinical trials in robotic lower limb training.

DATA SOURCES

A computer-aided search in bibliographic databases (PubMed and Web of Science) of clinical trials published up to September 2020 was done.

METHODS

To be selected for detailed review, clinical trials had to meet the following criteria: (1) a protocol was designed and approved, (2) participants were people with pathologies, and (3) the trials were not a single case study. Clinical trial data were collected, extracted, and analysed, considering: objectives, trial participants, number of sessions, pathologies involved, and conclusions.

RESULTS

The search resulted in 312 potentially relevant studies of seven commercial exoskeletons, of which 135 passed the preliminary screening; and 69 studies were finally selected. Of the 69 clinical trials included in the review about 50% involved Spinal Cord Injury participants, while roughly 25% focussed on stroke and two trials corresponded to patients with both disorders. The rest were composed of neurological diseases and trauma disorders.

CONCLUSIONS

The use of a single wearable robot for different medical conditions in various diseases is a challenge. Based on this comparative, the properties of the exoskeletons that improve the working ability with different pathologies and patient conditions have been evaluated. Suggestions were made for developing a new lower-limb exoskeleton based on various modules with a distributed control system to improve versatility in wearable technology for different gait pattern progression.Implications for rehabilitationWearable robotic exoskeletons for gait assistance have been analysed from the perspective of adaptation to different diseases.This paper emphasizes the importance of personalized therapies and adaptive assistive technology.Suggestions were made for a new modular exoskeleton capable of addressing the issue of low versatility characterizing currently wearable assistive technology.

Computer Vision to Automatically Assess Infant Neuromotor Risk

An infant's risk of developing neuromotor impairment is primarily assessed through visual examination by specialized clinicians. Therefore, many infants at risk for impairment go undetected, particularly in under-resourced environments. There is thus a need to develop automated, clinical assessments based on quantitative measures from widely-available sources, such as videos recorded on a mobile device. Here, we automatically extract body poses and movement kinematics from the videos of at-risk infants (N = 19). For each infant, we calculate how much they deviate from a group of healthy infants (N = 85 online videos) using a Naïve Gaussian Bayesian Surprise metric. After pre-registering our Bayesian Surprise calculations, we find that infants who are at high risk for impairments deviate considerably from the healthy group. Our simple method, provided as an open-source toolkit, thus shows promise as the basis for an automated and low-cost assessment of risk based on video recordings.

Computer Vision to Automatically Assess Infant Neuromotor Risk

An infant's risk of developing neuromotor impairment is primarily assessed through visual examination by specialized clinicians. Therefore, many infants at risk for impairment go undetected, particularly in under-resourced environments. There is thus a need to develop automated, clinical assessments based on quantitative measures from widely-available sources, such as videos recorded on a mobile device. Here, we automatically extract body poses and movement kinematics from the videos of at-risk infants (N = 19). For each infant, we calculate how much they deviate from a group of healthy infants (N = 85 online videos) using a Naïve Gaussian Bayesian Surprise metric. After pre-registering our Bayesian Surprise calculations, we find that infants who are at high risk for impairments deviate considerably from the healthy group. Our simple method, provided as an open-source toolkit, thus shows promise as the basis for an automated and low-cost assessment of risk based on video recordings.