Towards a validated glossary of usability attributes for the evaluation of wearable robotic devices.

BACKGROUND: Despite technical advances in the field of wearable robotic devices (WRD), there is still limited user acceptance of these technologies. While usability often comes as a key factor influencing acceptance, there is a scattered landscape of definitions and scopes for the term. To advance usability evaluation, and to integrate usability features as design requirements during technology development, there is a need for benchmarks and shared terminology. These should be easily accessible and implementable by developers. METHODS: An initial set of usability attributes (UA) was extracted from a literature survey on usability evaluation in WRD. The initial set of attributes was enriched and locally validated with seven developers of WRD through an online survey and a focus group. The locally validated glossary was then externally validated through a globally distributed online survey. RESULTS: The result is the Robotics Usability Glossary (RUG), a comprehensive glossary of 41 UA validated by 70 WRD developers from 17 countries, ensuring its generalizability. 31 of the UA had high agreement scores among respondents and 27 were considered highly relevant in the field, but only 11 of them had been included as design criteria by the respondents. CONCLUSIONS: Multiple UA ought to be considered for a comprehensive usability assessment. Usability remains inadequately incorporated into device development, indicating a need for increased awareness and end-user perspective. The RUG can be readily accessed through an online platform, the Interactive Usability Toolbox (IUT), developed to provide context-specific outcome measures and usability evaluation methods. Overall, this effort is an important step towards improving and promoting usability evaluation practices within WRD. It has the potential to pave the way for establishing usability evaluation benchmarks that further endorse the acceptance of WRD.

First-in-human demonstration of floating EMG sensors and stimulators wirelessly powered and operated by volume conduction.

BACKGROUND: Recently we reported the design and evaluation of floating semi-implantable devices that receive power from and bidirectionally communicate with an external system using coupling by volume conduction. The approach, of which the semi-implantable devices are proof-of-concept prototypes, may overcome some limitations presented by existing neuroprostheses, especially those related to implant size and deployment, as the implants avoid bulky components and can be developed as threadlike devices. Here, it is reported the first-in-human acute demonstration of these devices for electromyography (EMG) sensing and electrical stimulation. METHODS: A proof-of-concept device, consisting of implantable thin-film electrodes and a nonimplantable miniature electronic circuit connected to them, was deployed in the upper or lower limb of six healthy participants. Two external electrodes were strapped around the limb and were connected to the external system which delivered high frequency current bursts. Within these bursts, 13 commands were modulated to communicate with the implant. RESULTS: Four devices were deployed in the biceps brachii and the gastrocnemius medialis muscles, and the external system was able to power and communicate with them. Limitations regarding insertion and communication speed are reported. Sensing and stimulation parameters were configured from the external system. In one participant, electrical stimulation and EMG acquisition assays were performed, demonstrating the feasibility of the approach to power and communicate with the floating device. CONCLUSIONS: This is the first-in-human demonstration of EMG sensors and electrical stimulators powered and operated by volume conduction. These proof-of-concept devices can be miniaturized using current microelectronic technologies, enabling fully implantable networked neuroprosthetics.

Predictors of fall risk in older adults using the G-STRIDE inertial sensor: an observational multicenter case-control study.

BACKGROUND: There are a lot of tools to use for fall assessment, but there is not yet one that predicts the risk of falls in the elderly. This study aims to evaluate the use of the G-STRIDE prototype in the analysis of fall risk, defining the cut-off points to predict the risk of falling and developing a predictive model that allows discriminating between subjects with and without fall risks and those at risk of future falls. METHODS: An observational, multicenter case-control study was conducted with older people coming from two different public hospitals and three different nursing homes. We gathered clinical variables ( Short Physical Performance Battery (SPPB), Standardized Frailty Criteria, Speed 4 m walk, Falls Efficacy Scale-International (FES-I), Time-Up Go Test, and Global Deterioration Scale (GDS)) and measured gait kinematics using an inertial measure unit (IMU). We performed a logistic regression model using a training set of observations (70% of the participants) to predict the probability of falls. RESULTS: A total of 163 participants were included, 86 people with gait and balance disorders or falls and 77 without falls; 67,8% were females, with a mean age of 82,63 ± 6,01 years. G-STRIDE made it possible to measure gait parameters under normal living conditions. There are 46 cut-off values of conventional clinical parameters and those estimated with the G-STRIDE solution. A logistic regression mixed model, with four conventional and 2 kinematic variables allows us to identify people at risk of falls showing good predictive value with AUC of 77,6% (sensitivity 0,773 y specificity 0,780). In addition, we could predict the fallers in the test group (30% observations not in the model) with similar performance to conventional methods. CONCLUSIONS: The G-STRIDE IMU device allows to predict the risk of falls using a mixed model with an accuracy of 0,776 with similar performance to conventional model. This approach allows better precision, low cost and less infrastructures for an early intervention and prevention of future falls.

Review of electromyography onset detection methods for real-time control of robotic exoskeletons.

BACKGROUND: Electromyography (EMG) is a classical technique used to record electrical activity associated with muscle contraction and is widely applied in Biomechanics, Biomedical Engineering, Neuroscience and Rehabilitation Robotics. Determining muscle activation onset timing, which can be used to infer movement intention and trigger prostheses and robotic exoskeletons, is still a big challenge. The main goal of this paper was to perform a review of the state-of-the-art of EMG onset detection methods. Moreover, we compared the performance of the most commonly used methods on experimental EMG data. METHODS: A total of 156 papers published until March 2022 were included in the review. The papers were analyzed in terms of application domain, pre-processing method and EMG onset detection method. The three most commonly used methods [Single (ST), Double (DT) and Adaptive Threshold (AT)] were applied offline on experimental intramuscular and surface EMG signals obtained during contractions of ankle and knee joint muscles. RESULTS: Threshold-based methods are still the most commonly used to detect EMG onset. Compared to ST and AT, DT required more processing time and, therefore, increased onset timing detection, when applied on experimental data. The accuracy of these three methods was high (maximum error detection rate of 7.3%), demonstrating their ability to automatically detect the onset of muscle activity. Recently, other studies have tested different methods (especially Machine Learning based) to determine muscle activation onset offline, reporting promising results. CONCLUSIONS: This study organized and classified the existing EMG onset detection methods to create consensus towards a possible standardized method for EMG onset detection, which would also allow more reproducibility across studies. The three most commonly used methods (ST, DT and AT) proved to be accurate, while ST and AT were faster in terms of EMG onset detection time, especially when applied on intramuscular EMG data. These are important features towards movement intention identification, especially in real-time applications. Machine Learning methods have received increased attention as an alternative to detect muscle activation onset. However, although several methods have shown their capability offline, more research is required to address their full potential towards real-time applications, namely to infer movement intention.

Exoskeleton-based training improves walking independence in incomplete spinal cord injury patients: results from a randomized controlled trial.

BACKGROUND: In recent years, ambulatory lower limb exoskeletons are being gradually introduced into the clinical practice to complement walking rehabilitation programs. However, the clinical evidence of the outcomes attained with these devices is still limited and nonconclusive. Furthermore, the user-to-robot adaptation mechanisms responsible for functional improvement are still not adequately unveiled. This study aimed to (1) assess the safety and feasibility of using the HANK exoskeleton for walking rehabilitation, and (2) investigate the effects on walking function after a training program with it. METHODS: A randomized controlled trial was conducted including a cohort of 23 patients with less than 1 year since injury, neurological level of injury (C2-L4) and severity (American Spinal Cord Injury Association Impairment Scale [AIS] C or D). The intervention was comprised of 15 one-hour gait training sessions with lower limb exoskeleton HANK. Safety was assessed through monitoring of adverse events, and pain and fatigue through a Visual Analogue Scale. LEMS, WISCI-II, and SCIM-III scales were assessed, along with the 10MWT, 6MWT, and the TUG walking tests (see text for acronyms). RESULTS: No major adverse events were reported. Participants in the intervention group (IG) reported 1.8 cm (SD 1.0) for pain and 3.8 (SD 1.7) for fatigue using the VAS. Statistically significant differences were observed for the WISCI-II for both the "group" factor (F = 16.75, p < 0.001) and "group-time" interactions (F = 8.87; p < 0.01). A post-hoc analysis revealed a statistically significant increase of 3.54 points (SD 2.65, p < 0.0001) after intervention for the IG but not in the CG (0.7 points, SD 1.49, p = 0.285). No statistical differences were observed between groups for the remaining variables. CONCLUSIONS: The use of HANK exoskeleton in clinical settings is safe and well-tolerated by the patients. Patients receiving treatment with the exoskeleton improved their walking independence as measured by the WISCI-II after the treatment.

A qualitative study to elicit user requirements for lower limb wearable exoskeletons for gait rehabilitation in spinal cord injury.

OBJECTIVE: We aim to determine a comprehensive set of requirements, perceptions, and expectations that people with spinal cord injury (SCI) and the clinicians in charge of their rehabilitation have regarding the use of wearable robots (WR) for gait rehabilitation. BACKGROUND: There are concerns due to the limited user acceptance of WR for gait rehabilitation. Developers need to emphasize understanding the needs and constraints of all stakeholders involved, including the real-life dynamics of rehabilitation centers. METHODS: 15 people with SCI, 9 without experience with WR and 6 with experience with these technologies, and 10 clinicians from 3 rehabilitation centers in Spain were interviewed. A directed content analysis approach was used. RESULTS: 78 codes grouped into 9 categories (physical results, usability, psychology-related codes, technical characteristics, activities, acquisition issues, context of use, development of the technologies and clinical rehabilitation context) were expressed by at least 20% of the users interviewed, of whom 16 were not found in the literature. The agreement percentage between each group and subgroup included in the study, calculated as the number of codes that more than 20% of both groups expressed, divided over the total amount of codes any of those two groups agreed on (≥ 20%), showed limited agreement between patients and clinicians (50.00%) and between both types of patients (55.77%). The limited accessibility and availability of lower limb exoskeletons for gait rehabilitation arose in most of the interviews. CONCLUSIONS: The limited agreement percentage between patients and clinicians indicates that including both types of users in the design process of these technologies is important, given that their requirements are complementary. Engaging users with prior technology experience is recommended, as they often exhibit strong internal consensus and articulate well-defined requirements. This study adds up the knowledge available in the literature and the new codes found in our data, which enlighten important aspects that ought to be addressed in the field to develop technologies that respond to users' needs, are usable and feasible to implement in their intended contexts. APPLICATION: The set of criteria summarized in our study will be useful to guide the design, development, and evaluation of WR for gait rehabilitation to meet user's needs and allow them to be implemented in their intended context of use.

Benchmarking the Effects on Human-Exoskeleton Interaction of Trajectory, Admittance and EMG-Triggered Exoskeleton Movement Control.

Nowadays, robotic technology for gait training is becoming a common tool in rehabilitation hospitals. However, its effectiveness is still controversial. Traditional control strategies do not adequately integrate human intention and interaction and little is known regarding the impact of exoskeleton control strategies on muscle coordination, physical effort, and user acceptance. In this article, we benchmarked three types of exoskeleton control strategies in a sample of seven healthy volunteers: trajectory assistance (TC), compliant assistance (AC), and compliant assistance with EMG-Onset stepping control (OC), which allows the user to decide when to take a step during the walking cycle. This exploratory study was conducted within the EUROBENCH project facility. Experimental procedures and data analysis were conducted following EUROBENCH's protocols. Specifically, exoskeleton kinematics, muscle activation, heart and breathing rates, skin conductance, as well as user-perceived effort were analyzed. Our results show that the OC controller showed robust performance in detecting stepping intention even using a corrupt EMG acquisition channel. The AC and OC controllers resulted in similar kinematic alterations compared to the TC controller. Muscle synergies remained similar to the synergies found in the literature, although some changes in muscle contribution were found, as well as an overall increase in agonist-antagonist co-contraction. The OC condition led to the decreased mean duration of activation of synergies. These differences were not reflected in the overall physiological impact of walking or subjective perception. We conclude that, although the AC and OC walking conditions allowed the users to modulate their walking pattern, the application of these two controllers did not translate into significant changes in the overall physiological cost of walking nor the perceived experience of use. Nonetheless, results suggest that both AC and OC controllers are potentially interesting approaches that can be explored as gait rehabilitation tools. Furthermore, the INTENTION project is, to our knowledge, the first study to benchmark the effects on human-exoskeleton interaction of three different exoskeleton controllers, including a new EMG-based controller designed by us and never tested in previous studies, which has made it possible to provide valuable third-party feedback on the use of the EUROBENCH facility and testbed, enriching the apprenticeship of the project consortium and contributing to the scientific community.

Effect of posture and body weight loading on spinal posterior root reflex responses.

The posterior root muscle response (PRM) is a monosynaptic reflex that is evoked by single pulse transcutaneous spinal cord stimulation (tSCS). The main aim of this work was to analyse how body weight loading influences PRM reflex threshold measured from several lower limb muscles in healthy participants. PRM reflex responses were evoked with 1-ms rectangular monophasic pulses applied at an interval of 6 s via a self-adhesive electrode (9 × 5 cm) at the T11-T12 vertebral level. Surface electromyographic activity of lower limb muscles was recorded during four different conditions, one in decubitus supine (DS) and the other three involving standing at 100%, 50%, and 0% body weight loading (BW). PRM threshold intensity, peak-to-peak amplitude, and latency for each muscle were analysed in different conditions study. PRM reflex threshold increased with body weight unloading compared with DS, and the largest change was observed between DS and 0% BW for the proximal muscles and between DS and 50% BW for distal muscles. Peak-to-peak amplitude analysis showed only a significant mean decrease of 34.6% (SD 10.4, p = 0.028) in TA and 53.6% (SD 15.1, p = 0.019) in GM muscles between DS and 50% BW. No significant differences were observed for PRM latency. This study has shown that sensorimotor networks can be activated with tSCS in various conditions of body weight unloading. Higher stimulus intensities are necessary to evoke reflex response during standing at 50% body weight loading. These results have practical implications for gait rehabilitation training programmes that include body weight support.

Transcranial direct current stimulation combined with robotic therapy for upper and lower limb function after stroke: a systematic review and meta-analysis of randomized control trials.

BACKGROUND: Transcranial direct current stimulation (tDCS) is a non-invasive brain stimulation method able to modulate neuronal activity after stroke. The aim of this systematic review was to determine if tDCS combined with robotic therapy (RT) improves limb function after stroke when compared to RT alone. METHODS: A search for randomized controlled trials (RCTs) published prior to July 15, 2021 was performed. The main outcome was function assessed with the Fugl-Meyer motor assessment for upper extremities (FM/ue) and 10-m walking test (10MWT) for the lower limbs. As secondary outcomes, strength was assessed with the Motricity Index (MI) or Medical Research Council scale (MRC), spasticity with the modified Ashworth scale (MAS), functional independence with the Barthel Index (BI), and kinematic parameters. RESULTS: Ten studies were included for analysis (n = 368 enrolled participants). The results showed a non-significant effect for tDCS combined with RT to improve upper limb function [standardized mean difference (SMD) = - 0.12; 95% confidence interval (CI): - 0.35-0.11)]. However, a positive effect of the combined therapy was observed in the lower limb function (SMD = 0.48; 95% CI: - 0.15-1.12). Significant results favouring tDCS combined with RT were not found in strength (SMD = - 0.15; 95% CI: - 0.4-0.1), spasticity [mean difference (MD) = - 0.15; 95% CI: - 0.8-0.5)], functional independence (MD = 2.5; 95% CI: - 1.9-6.9) or velocity of movement (SMD = 0.06; 95% CI: - 0.3-0.5) with a "moderate" or "low" recommendation level according to the GRADE guidelines. CONCLUSIONS: Current findings suggest that tDCS combined with RT does not improve upper limb function, strength, spasticity, functional independence or velocity of movement after stroke. However, tDCS may enhance the effects of RT alone for lower limb function. tDCS parameters and the stage or type of stroke injury could be crucial factors that determine the effectiveness of this therapy.

Adaptive multichannel FES neuroprosthesis with learning control and automatic gait assessment.

BACKGROUND: FES (Functional Electrical Stimulation) neuroprostheses have long been a permanent feature in the rehabilitation and gait support of people who had a stroke or have a Spinal Cord Injury (SCI). Over time the well-known foot switch triggered drop foot neuroprosthesis, was extended to a multichannel full-leg support neuroprosthesis enabling improved support and rehabilitation. However, these neuroprostheses had to be manually tuned and could not adapt to the persons' individual needs. In recent research, a learning controller was added to the drop foot neuroprosthesis, so that the full stimulation pattern during the swing phase could be adapted by measuring the joint angles of previous steps. METHODS: The aim of this research is to begin developing a learning full-leg supporting neuroprosthesis, which controls the antagonistic muscle pairs for knee flexion and extension, as well as for ankle joint dorsi- and plantarflexion during all gait phases. A method was established that allows a continuous assessment of knee and foot joint angles with every step. This method can warp the physiological joint angles of healthy subjects to match the individual pathological gait of the subject and thus allows a direct comparison of the two. A new kind of Iterative Learning Controller (ILC) is proposed which works independent of the step duration of the individual and uses physiological joint angle reference bands. RESULTS: In a first test with four people with an incomplete SCI, the results showed that the proposed neuroprosthesis was able to generate individually fitted stimulation patterns for three of the participants. The other participant was more severely affected and had to be excluded due to the resulting false triggering of the gait phase detection. For two of the three remaining participants, a slight improvement in the average foot angles could be observed, for one participant slight improvements in the averaged knee angles. These improvements where in the range of 4circat the times of peak dorsiflexion, peak plantarflexion, or peak knee flexion. CONCLUSIONS: Direct adaptation to the current gait of the participants could be achieved with the proposed method. The preliminary first test with people with a SCI showed that the neuroprosthesis can generate individual stimulation patterns. The sensitivity to the knee angle reset, timing problems in participants with significant gait fluctuations, and the automatic ILC gain tuning are remaining issues that need be addressed. Subsequently, future studies should compare the improved, long-term rehabilitation effects of the here presented neuroprosthesis, with conventional multichannel FES neuroprostheses.

Assessing the Involvement of Users During Development of Lower Limb Wearable Robotic Exoskeletons: A Survey Study.

OBJECTIVE: To explore user-centered design methods currently implemented during development of lower limb wearable robots and how they are utilized during different stages of product development. BACKGROUND: Currently, there appears to be a lack of standardized frameworks for evaluation methods and design requirements to implement effective user-centered design for safe and effective clinical or ergonomic system application. METHOD: Responses from a total of 191 experts working in the field of lower limb exoskeletons were analyzed in this exploratory survey. Descriptive statistics were used to present responses and measures of frequency, and chi-square tests were used to contrast the answers of respondents who identified as clinicians versus engineers. RESULTS: A vast majority of respondents involve users in their development, in particular at the initial and iterative stages, although some differences were found between disciplines. A variety of methods and metrics are used to capture feedback from users and test devices, and although valuable, some methods used may not be based on validated measures. Guidelines regarding tests on safety of exoskeletons also lack standardization. CONCLUSION: There seems to be a consensus among experts regarding the importance of a user-centered approach in exoskeleton development; however, standardized frameworks with regard to appropriate testing methods and design approaches are lacking. Such frameworks should consider an interdisciplinary focus on the needs and safety of the intended user during each iteration of the process. APPLICATION: This exploratory study provides an overview of current practice among engineers and clinicians regarding the user-centered design of exoskeletons. Limitations and recommendations for future directions are identified.

A Systematic Methodology to Analyze the Impact of Hand-Rim Wheelchair Propulsion on the Upper Limb.

Manual wheelchair propulsion results in physical demand of the upper limb extremities that, because of its repetitive nature, can lead to chronic pathologies on spinal cord injury patients. The aim of this study was to design and test a methodology to compare kinematic and kinetic variables of the upper limb joints when propelling different wheelchairs. Moreover, this methodology was used to analyze the differences that may exist between paraplegic and tetraplegic patients when propelling two different wheelchairs. Five adults with paraplegia and five adults with tetraplegia performed several propulsion tests. Participants propelled two different wheelchairs for three minutes at 0.833 m/s (3 km/h) with one minute break between the tests. Kinematic and kinetic variables of the upper limb as well as variables with respect to the propulsion style were recorded. Important differences in the kinetic and kinematic variables of the joints of the upper limb were found when comparing paraplegic and tetraplegic patients. Nevertheless, this difference depends on the wheelchair used. As expected, in all tests, the shoulder shows to be the most impacted joint.

Volition-adaptive control for gait training using wearable exoskeleton: preliminary tests with incomplete spinal cord injury individuals.

BACKGROUND: Gait training for individuals with neurological disorders is challenging in providing the suitable assistance and more adaptive behaviour towards user needs. The user specific adaptation can be defined based on the user interaction with the orthosis and by monitoring the user intentions. In this paper, an adaptive control model, commanded by the user intention, is evaluated using a lower limb exoskeleton with incomplete spinal cord injury individuals (SCI). METHODS: A user intention based adaptive control model has been developed and evaluated with 4 incomplete SCI individuals across 3 sessions of training per individual. The adaptive control model modifies the joint impedance properties of the exoskeleton as a function of the human-orthosis interaction torques and the joint trajectory evolution along the gait sequence, in real time. The volitional input of the user is identified by monitoring the neural signals, pertaining to the user's motor activity. These volitional inputs are used as a trigger to initiate the gait movement, allowing the user to control the initialization of the exoskeleton movement, independently. A Finite-state machine based control model is used in this set-up which helps in combining the volitional orders with the gait adaptation. RESULTS: The exoskeleton demonstrated an adaptive assistance depending on the patients' performance without guiding them to follow an imposed trajectory. The exoskeleton initiated the trajectory based on the user intention command received from the brain machine interface, demonstrating it as a reliable trigger. The exoskeleton maintained the equilibrium by providing suitable assistance throughout the experiments. A progressive change in the maximum flexion of the knee joint was observed at the end of each session which shows improvement in the patient performance. Results of the adaptive impedance were evaluated by comparing with the application of a constant impedance value. Participants reported that the movement of the exoskeleton was flexible and the walking patterns were similar to their own distinct patterns. CONCLUSIONS: This study demonstrates that user specific adaptive control can be applied on a wearable robot based on the human-orthosis interaction torques and modifying the joints' impedance properties. The patients perceived no external or impulsive force and felt comfortable with the assistance provided by the exoskeleton. The main goal of such a user dependent control is to assist the patients' needs and adapt to their characteristics, thus maximizing their engagement in the therapy and avoiding slacking. In addition, the initiation directly controlled by the brain allows synchronizing the user's intention with the afferent stimulus provided by the movement of the exoskeleton, which maximizes the potentiality of the system in neuro-rehabilitative therapies.

Advances in selective activation of muscles for non-invasive motor neuroprostheses.

Non-invasive neuroprosthetic (NP) technologies for movement compensation and rehabilitation remain with challenges for their clinical application. Two of those major challenges are selective activation of muscles and fatigue management. This review discusses how electrode arrays improve the efficiency and selectivity of functional electrical stimulation (FES) applied via transcutaneous electrodes. In this paper we review the principles and achievements during the last decade on techniques for artificial motor unit recruitment to improve the selective activation of muscles. We review the key factors affecting the outcome of muscle force production via multi-pad transcutaneous electrical stimulation and discuss how stimulation parameters can be set to optimize external activation of body segments. A detailed review of existing electrode array systems proposed by different research teams is also provided. Furthermore, a review of the targeted applications of existing electrode arrays for control of upper and lower limb NPs is provided. Eventually, last section demonstrates the potential of electrode arrays to overcome the major challenges of NPs for compensation and rehabilitation of patient-specific impairments.

Hybrid FES-robot cooperative control of ambulatory gait rehabilitation exoskeleton.

Robotic and functional electrical stimulation (FES) approaches are used for rehabilitation of walking impairment of spinal cord injured individuals. Although devices are commercially available, there are still issues that remain to be solved. Control of hybrid exoskeletons aims at blending robotic exoskeletons and electrical stimulation to overcome the drawbacks of each approach while preserving their advantages. Hybrid actuation and control have a considerable potential for walking rehabilitation but there is a need of novel control strategies of hybrid systems that adequately manage the balance between FES and robotic controllers. Combination of FES and robotic control is a challenging issue, due to the non-linear behavior of muscle under stimulation and the lack of developments in the field of hybrid control. In this article, a cooperative control strategy of a hybrid exoskeleton is presented. This strategy is designed to overcome the main disadvantages of muscular stimulation: electromechanical delay and change in muscle performance over time, and to balance muscular and robotic actuation during walking.Experimental results in healthy subjects show the ability of the hybrid FES-robot cooperative control to balance power contribution between exoskeleton and muscle stimulation. The robotic exoskeleton decreases assistance while adequate knee kinematics are guaranteed. A new technique to monitor muscle performance is employed, which allows to estimate muscle fatigue and implement muscle fatigue management strategies. Kinesis is therefore the first ambulatory hybrid exoskeleton that can effectively balance robotic and FES actuation during walking. This represents a new opportunity to implement new rehabilitation interventions to induce locomotor activity in patients with paraplegia.Acronym list: 10 mWT: ten meters walking test; 6 MWT: six minutes walking test; FSM: finite-state machine; t-FSM: time-domain FSM; c-FSM: cycle-domain FSM; FES: functional electrical stimulation; HKAFO: hip-knee-ankle-foot orthosis; ILC: iterative error-based learning control; MFE: muscle fatigue estimator; NILC: Normalized stimulation output from ILC controller; PID: Proportional-Integral-derivative Control; PW: Stimulation pulse width; QUEST: Quebec User Evaluation of Satisfaction with assistive Technology; SCI: Spinal cord injury; TTI: torque-time integral; VAS: Visual Analog Scale.

Construct Validity of the Gait Deviation Index for People With Incomplete Spinal Cord Injury (GDI-SCI).

BACKGROUND: The Gait Deviation Index for Spinal Cord Injury (SCI-GDI) was recently proposed as a dimensionless multivariate kinematic measure based on 21 gait features derived from 3-dimensional kinematic data which quantifies gait impairment of adult population with incomplete spinal cord injury (iSCI) relative to the normative gait of a healthy group. Nevertheless, no validity studies of the SCI-GDI have been published to date. OBJECTIVE: To assess the construct validity of the SCI-GDI in adult population following iSCI. Methods. SCI-GDI data were obtained from a sample of 50 healthy volunteers and 35 adults with iSCI. iSCI group was also assessed with the following measures: 10-Meter Walk Test (10MWT) at both self-selected (SS) and maximum speeds, Timed Up and Go Test (TUGT), SS and maximum levels of the Walking Index for Spinal Cord Injury (WISCI) II, mobility items of the Spinal Cord Independence Measure III (SCIM IIIIOMob), Lower Extremity Motor Score (LEMS), and Modified Ashworth Scale (MAS). Spearman's correlation coefficient was used to investigate the relationship with the SCI-GDI. RESULTS: SCI-GDI shows strong correlation with the 10MWT (r ≥ -.716) and good correlation with LEMS (r = .638), TUGT (r = -.582), SS WISCI II levels (r = .521), and SCIM IIIIOMob (r = .501). No significant correlations were found with maximum WISCI II levels and MAS (P > .006). CONCLUSIONS: Construct validity of the SCI-GDI was demonstrated with the 10MWT, TUGT, LEMS, SCIM IIIIOMob, and SS WISCI II levels for independently walking adults with iSCI. Future work will include assessing the psychometric characteristics with a more heterogeneous sample, also considering the pediatric population.

A database with frailty, functional and inertial gait metrics for the research of fall causes in older adults.

The GSTRIDE database contains information of the health status assessment of 163 elderly adults. We provide socio-demographic data, functional and frailty variables, and the outcomes from tests commonly performed for the evaluation of elder people. The database contains gait parameters estimated from the measurements of an Inertial Measurement Unit (IMU) placed on the foot of volunteers. These parameters include the total walking distance, the number of strides and multiple spatio-temporal gait parameters, such as stride length, stride time, speed, foot angles and clearance, among others. The main processed database is stored, apart from MS Excel, in CSV format to ensure their usability. The database is complemented with the raw IMU recordings in TXT format, in order to let researchers test other algorithms of gait analysis. We include the Python programming codes as a base to reproduce or modify them. The database stores data to study the frailty-related parameters that distinguish faller and non-faller populations, and analyze the gait-related parameters in the frail subjects, which are essential topics for the elderly.

Powering Electronic Implants by High Frequency Volume Conduction: In Human Validation.

OBJECTIVE: Wireless power transfer (WPT) is used as an alternative to batteries to accomplish miniaturization in electronic medical implants. However, established WPT methods require bulky parts within the implant or cumbersome external systems, hindering minimally invasive deployments and the development of networks of implants. As an alternative, we propose a WPT approach based on volume conduction of high frequency (HF) current bursts. These currents are applied through external electrodes and are collected by the implants through two electrodes at their opposite ends. This approach avoids bulky components, enabling the development of flexible threadlike implants. METHODS: We study in humans if HF (6.78 MHz) current bursts complying with safety standards and applied through two textile electrodes strapped around a limb can provide substantial powers from pairs of implanted electrodes. RESULTS: Time averaged electric powers obtained from needle electrodes (diameter = 0.4 mm, length = 3 mm, separation = 30 mm) inserted into arms and lower legs of five healthy participants were 5.9 ± 0.7 mW and 2.4 ± 0.3 mW respectively. We also characterize the coupling between the external system and the implants using personalized two-port impedance models generated from medical images. CONCLUSIONS: The results demonstrate that innocuous and imperceptible HF current bursts that flow through the tissues by volume conduction can be used to wirelessly power threadlike implants. SIGNIFICANCE: This is the first time that WPT based on volume conduction is demonstrated in humans. This method overcomes the limitations of existing WPT methods in terms of minimal invasiveness and usability.

Assessing falls in the elderly population using G-STRIDE foot-mounted inertial sensor.

Falls are one of the main concerns in the elderly population due to their high prevalence and associated consequences. Guidelines for the management of the elder with falls are comprised of multidimensional assessments, especially gait and balance. Daily clinical practice needs for timely, effortless, and precise tools to assess gait. This work presents the clinical validation of the G-STRIDE system, a 6-axis inertial measurement unit (IMU) with onboard processing algorithms, that allows the calculation of walking-related metrics correlated with clinical markers of fall risk. A cross-sectional case-control study was conducted with 163 participants (falls and non-falls groups). All volunteers were assessed with clinical scales and conducted a 15-min walking test at a self-selected pace while wearing the G-STRIDE. G-STRIDE is a low-cost solution to facilitate the transfer to society and clinical evaluations. It is open hardware and flexible and, thus, has the advantage of providing runtime data processing. Walking descriptors were derived from the device, and a correlation analysis was conducted between walking and clinical variables. G-STRIDE allowed measuring walking parameters in non-restricted walking conditions (e.g. hallway). Walking parameters statistically discriminate between falls and non-falls groups. We found good/excellent estimation accuracy (ICC = 0.885; [Formula: see text]) for walking speed, showing good/excellent correlation between gait speed and several clinical variables. G-STRIDE can calculate walking-related metrics that allow for discrimination between falls and non-falls groups, which correlates with clinical indicators of fall risk. A preliminary fall-risk assessment based on the walking parameters was found to improve the Timed Up and Go test in the identification of fallers.