Specific instructions are important: A cross-sectional study on device parameters and instruction types while walking with a robot in children and adolescents.

OBJECTIVE: To evaluate how gait kinematics and muscle activity during robot-assisted gait training are affected by different combinations of parameter settings and a number of instruction types, ranging from no instructions to goal-specific instructions. DESIGN: Robots for gait therapy provide a haptic guidance, but too much guidance can limit the active participation. Therapists can stimulate this active participation either with instructions or by adapting device parameters. How these two factors interact is still unknown. In the present study, we test the interaction of 3 different parameter settings and 4 instruction types in a cross-sectional study with 20 children and adolescents without impairment. Gait kinematics and surface electromyography were measured to evaluate the immediate effects. RESULTS: We found that only goal-specific instructions in combination with a low guidance led to a moderate but significant change in gait kinematics. The muscle activity was altered by all instructions, but the biggest effect was found for goal-specific instructions with a 2.5 times higher sEMG amplitude compared to no instruction. CONCLUSIONS: Goal-specific instructions are a key element of robot-assisted gait therapy interventions and device parameter adjustments may be used to modulate their effects. Therapists should pay close attention to how they instruct patients.

Accuracy of Sensor-Based Measurement of Clinically Relevant Motor Activities in Daily Life of Children With Mobility Impairments.

OBJECTIVE: This study aimed to determine the accuracy of 3 sensor configurations and corresponding algorithms deriving clinically relevant outcomes of everyday life motor activities in children undergoing rehabilitation. These outcomes were identified in 2 preceding studies assessing the needs of pediatric rehabilitation. The first algorithm estimates the duration of lying, sitting, and standing positions and the number of sit-to-stand transitions with data from a trunk and a thigh sensor. The second algorithm detects active and passive wheeling periods with data from a wrist and a wheelchair sensor. The third algorithm detects free and assisted walking periods and estimates the covered altitude change during stair climbing with data from a single ankle sensor and a sensor placed on walking aids. DESIGN: The participants performed a semi-structured activity circuit while wearing inertial sensors on both wrists, the sternum, and the thigh and shank of the less-affected side. The circuit included watching a movie, playing, cycling, drinking, and moving around between facilities. Video recordings, which 2 independent researchers labeled, served as reference criteria to determine the algorithms' performance. SETTING: In-patient rehabilitation center. PARTICIPANTS: Thirty-one children and adolescents with mobility impairments who were able to walk or use a manual wheelchair for household distances (N=31). INTERVENTIONS: Not applicable. MAIN OUTCOME MEASURE(S): The algorithms' activity classification accuracies. RESULTS: The activity classification accuracy was 97% for the posture detection algorithm, 96% for the wheeling detection algorithm, and 93% for the walking detection algorithm. CONCLUSION(S): The 3 sensor configurations and corresponding algorithms presented in this study revealed accurate measurements of everyday life motor activities in children with mobility impairments. To follow-up on this promising results, the sensor systems needs to be tested in long-term measurements outside the clinic before using the system to determine the children's motor performance in their habitual environment for clinical and scientific purposes.

1D-Convolutional Neural Networks can Quantify Therapy Content of Children and Adolescents Walking in a Robot-Assisted Gait Trainer.

Therapy content, consisting of device parameter settings and therapy instructions, is crucial for an effective robot-assisted gait therapy program. Settings and instructions depend on the therapy goals of the individual patient. While device parameters can be recorded by the robot, therapeutic instructions and associated patient responses are currently difficult to capture. This limits the transferability of successful therapeutic approaches between clinics. Here, we propose that 1D-convolutional neural networks can be used to relate patient behavior during individual steps to the instructions given as a surrogate for the patient's intent. Our model takes the surface electromyography patterns of two leg muscles as input and predicts the given instruction as output. We tested this approach with data from 20 healthy children walking in a robot-assisted gait trainer with 5 different instructions. Our model performs well, with a classification accuracy of almost 90%, when the instruction targets specific aspects of gait, such as step length. This shows that 1D-convolutional neural networks are a viable tool for quantifying therapy content. Thus, they could help compare therapy approaches and identify effective strategies.

The FreeD module's lateral translation timing in the gait robot Lokomat: a manual adaptation is necessary.

BACKGROUND: Pelvic and trunk movements are often restricted in stationary robotic gait trainers. The optional FreeD module of the driven gait orthosis Lokomat offers a combined, guided lateral translation and transverse rotation of the pelvis and may therefore support weight shifting during walking. However, from clinical experience, it seems that the default setting of this timing does not correspond well with the timing of the physiological pelvic movement during the gait cycle. In the software, a manual adaptation of the lateral translation's timing with respect to the gait cycle is possible. The aim of this study was to investigate if such an offset is indeed present and if a manual adaptation by the therapist can improve the timing towards a more physiological pattern comparable to physiological overground walking. METHODS & RESULTS: Children and adolescents with neurologic gait disorders and a Gross Motor Function Classification System level I-IV completed two different walking conditions (FreeD Default and FreeD Time Offset) in the Lokomat. The medio-lateral center of mass positions were calculated from RGB-Depth video recordings with a marker-less motion capture algorithm. Data of 22 patients (mean age: 12 ± 3 years) were analyzed. Kinematic analyses showed that in the FreeD Default condition, the maximum lateral center of mass excursion occurred too early. In the FreeD Time Offset condition, the manual adaptation by the therapists led to a delay of the maximum center of mass displacement by 8.2% in the first phase of the gait cycle and by 4.9% in the second phase of the gait cycle compared to the FreeD Default condition. The maximum lateral center of mass excursion was closer to that during physiological overground walking in the FreeD Time Offset condition than in the FreeD Default condition. CONCLUSION: A manual adaptation of the timing of the FreeD module in the Lokomat shifts pelvis kinematics in a direction of physiological overground walking. We recommend therapists to use this FreeD Time Offset function to adjust the phase of weight shifting for each patient individually to optimize the kinematic walking pattern when a restorative therapy approach is adopted.

Within- and between-therapist agreement on personalized parameters for robot-assisted gait therapy: the challenge of adjusting robotic assistance.

BACKGROUND: Stationary robotic gait trainers usually allow for adjustment of training parameters, including gait speed, body weight support and robotic assistance, to personalize therapy. Consequently, therapists personalize parameter settings to pursue a relevant therapy goal for each patient. Previous work has shown that the choice of parameters influences the behavior of patients. At the same time, randomized clinical trials usually do not report the applied settings and do not consider them in the interpretation of their results. The choice of adequate parameter settings therefore remains one of the major challenges that therapists face in everyday clinical practice. For therapy to be most effective, personalization should ideally result in repeatable parameter settings for repeatable therapy situations, irrespective of the therapist who adjusts the parameters. This has not yet been investigated. Therefore, the aim of the present study was to investigate the agreement of parameter settings from session to session within a therapist and between two different therapists in children and adolescents undergoing robot-assisted gait training. METHODS AND RESULTS: Fourteen patients walked in the robotic gait trainer Lokomat on 2 days. Two therapists from a pool of 5 therapists independently personalized gait speed, bodyweight support and robotic assistance for a moderately and a vigorously intensive therapy task. There was a very high agreement within and between therapists for the parameters gait speed and bodyweight support, but a substantially lower agreement for robotic assistance. CONCLUSION: These findings imply that therapists perform consistently at setting parameters that have a very clear and visible clinical effect (e.g. walking speed and bodyweight support). However, they have more difficulties with robotic assistance, which has a more ambiguous effect because patients may respond differently to changes. Future work should therefore focus on better understanding patient reactions to changes in robotic assistance and especially on how instructions can be employed to steer these reactions. To improve the agreement, we propose that therapists link their choice of robotic assistance to the individual therapy goals of the patients and closely guide the patients during walking with instructions.

Health-enhancing physical activity interventions in non-ambulatory people with severe motor impairments - a scoping review.

PURPOSE: Non-ambulatory people with severe motor impairments due to chronic neurological diagnoses are forced into a sedentary lifestyle. The purpose of this scoping review was to understand the type and amount of physical activity interventions performed in this population as well as their effect. METHODS: PubMed, Cochran and CINAHL Complete were systematically searched for articles describing physical activity interventions in people with a chronic, stable central nervous system lesion. The outcome measures needed to include physiological or psychological variables, measures of general health or quality of life. RESULTS: Of the initial 7554 articles, 34 were included after the title, abstract, and full-text screening. Only six studies were designed as randomized-controlled trials. Most interventions were supported by technologies, mainly functional electrical stimulation (cycling or rowing). The duration of the intervention ranged from four to 52 weeks. Endurance and strength training interventions (and a combination of both) were performed and over 70% of studies resulted in health improvements. CONCLUSIONS: Non-ambulatory people with severe motor impairments may benefit from physical activity interventions. However, the number of studies and their comparability is very limited. This indicates the need for future research with standard measures to develop evidence-based, specific recommendations for physical activity in this population.Key messagesPhysical activity interventions can have health benefits in non-ambulatory people with severe motor impairments.Even simple, low-tech interventions allow for health-enhancing training.

Clustering trunk movements of children and adolescents with neurological gait disorders undergoing robot-assisted gait therapy: the functional ability determines if actuated pelvis movements are clinically useful.

INTRODUCTION: Robot-assisted gait therapy is frequently used for gait therapy in children and adolescents but has been shown to limit the physiological excursions of the trunk and pelvis. Actuated pelvis movements might support more physiological trunk patterns during robot-assisted training. However, not every patient is expected to react identically to actuated pelvis movements. Therefore, the aim of the present study was to identify different trunk movement patterns with and without actuated pelvis movements and compare them based on their similarity to the physiological gait pattern. METHODS AND RESULTS: A clustering algorithm was used to separate pediatric patients into three groups based on different kinematic reactions of the trunk to walking with and without actuated pelvis movements. The three clusters included 9, 11 and 15 patients and showed weak to strong correlations with physiological treadmill gait. The groups also statistically differed in clinical assessment scores, which were consistent with the strength of the correlations. Patients with a higher gait capacity reacted with more physiological trunk movements to actuated pelvis movements. CONCLUSION: Actuated pelvis movements do not lead to physiological trunk movements in patients with a poor trunk control, while patients with better walking functions can show physiological trunk movements. Therapists should carefully consider for whom and why they decide to include actuated pelvis movements in their therapy plan.

Markerless motion tracking to quantify behavioral changes during robot-assisted gait training: A validation study.

Introduction: Measuring kinematic behavior during robot-assisted gait therapy requires either laborious set up of a marker-based motion capture system or relies on the internal sensors of devices that may not cover all relevant degrees of freedom. This presents a major barrier for the adoption of kinematic measurements in the normal clinical schedule. However, to advance the field of robot-assisted therapy many insights could be gained from evaluating patient behavior during regular therapies. Methods: For this reason, we recently developed and validated a method for extracting kinematics from recordings of a low-cost RGB-D sensor, which relies on a virtual 3D body model to estimate the patient's body shape and pose in each frame. The present study aimed to evaluate the robustness of the method to the presence of a lower limb exoskeleton. 10 healthy children without gait impairment walked on a treadmill with and without wearing the exoskeleton to evaluate the estimated body shape, and 8 custom stickers were placed on the body to evaluate the accuracy of estimated poses. Results & Conclusion: We found that the shape is generally robust to wearing the exoskeleton, and systematic pose tracking errors were around 5 mm. Therefore, the method can be a valuable measurement tool for the clinical evaluation, e.g., to measure compensatory movements of the trunk.

Acceptability of wearable inertial sensors, completeness of data, and day-to-day variability of everyday life motor activities in children and adolescents with neuromotor impairments.

Monitoring the patients' motor activities in a real-world setting would provide essential information on their functioning in daily life. In this study, we used wearable inertial sensors to monitor motor activities of children and adolescents with congenital and acquired brain injuries. We derived a set of clinically meaningful performance measures and addressed the following research questions: Is the target population willing to wear the sensors in their habitual environment? Which factors lead to missing data, and can we avoid them? How many measurement days are needed to obtain reliable estimates of the children's and adolescents' motor performance? The study participants wore our sensor system for seven consecutive days during waking hours. First, we derived the daily hand use of all participants, the duration of different body positions and the wheeling activity of individuals using a manual wheelchair, and walking-related measures in individuals being able to walk. Then, we analyzed the reasons for missing data and determined the reliability of the performance measures mentioned above. The large majority (41 of 43 participants) was willing to wear the sensor system for a week. However, forgetting to reattach the sensors after charging them overnight and taking them off during bathing and swimming was the main contributor to missing data. Consequently, improved battery life and waterproofness of the sensor technology are essential requirements for measurements in daily life. Besides, 5 of 11 performance measures showed significant differences between weekdays and weekend days. The reliability, measured with the intraclass correlation coefficient, ranged between 0.82 and 0.98. Seven measurement days were enough to obtain significantly higher reliability scores than the desired level of 0.8 for all but two performance measures. In children and adolescents with neuromotor impairments, we recommend monitoring everyday life motor activities on seven consecutive days. The target population accepted this measurement protocol, it covers school days and weekend days, and the number of measurement days is sufficient to obtain reliable estimates of motor performance.

Accuracy and comparison of sensor-based gait speed estimations under standardized and daily life conditions in children undergoing rehabilitation.

BACKGROUND: Gait speed is a widely used outcome measure to assess the walking abilities of children undergoing rehabilitation. It is routinely determined during a walking test under standardized conditions, but it remains unclear whether these outcomes reflect the children's performance in daily life. An ankle-worn inertial sensor provides a usable opportunity to measure gait speed in the children's habitual environment. However, sensor-based gait speed estimations need to be accurate to allow for comparison of the children's gait speed between a test situation and daily life. Hence, the first aim of this study was to determine the measurement error of a novel algorithm that estimates gait speed based on data of a single ankle-worn inertial sensor in children undergoing rehabilitation. The second aim of this study was to compare the children's gait speed between standardized and daily life conditions. METHODS: Twenty-four children with walking impairments completed four walking tests at different speeds (standardized condition) and were monitored for one hour during leisure or school time (daily life condition). We determined accuracy by comparing sensor-based gait speed estimations with a reference method in both conditions. Eventually, we compared individual gait speeds between the two conditions. RESULTS: The measurement error was 0.01 ± 0.07 m/s under the standardized and 0.04 ± 0.06 m/s under the daily life condition. Besides, the majority of children did not use the same speed during the test situation as in daily life. CONCLUSION: This study demonstrates an accurate method to measure children's gait speed during standardized walking tests and in the children's habitual environment after rehabilitation. It only requires a single ankle sensor, which potentially increases wearing time and data quality of measurements in daily life. We recommend placing the sensor on the less affected side, unless the child wears one orthosis. In this latter case, the sensor should be placed on the side with the orthosis. Moreover, this study showed that most children did not use the same speed in the two conditions, which encourages the use of wearable inertial sensors to assess the children's walking performance in their habitual environment following rehabilitation.

Sensor-based outcomes to monitor everyday life motor activities of children and adolescents with neuromotor impairments: A survey with health professionals.

In combination with appropriate data processing algorithms, wearable inertial sensors enable the measurement of motor activities in children's and adolescents' habitual environments after rehabilitation. However, existing algorithms were predominantly designed for adult patients, and their outcomes might not be relevant for a pediatric population. In this study, we identified the needs of pediatric rehabilitation to create the basis for developing new algorithms that derive clinically relevant outcomes for children and adolescents with neuromotor impairments. We conducted an international survey with health professionals of pediatric neurorehabilitation centers, provided them a list of 34 outcome measures currently used in the literature, and asked them to rate the clinical relevance of these measures for a pediatric population. The survey was completed by 62 therapists, 16 doctors, and 9 nurses of 16 different pediatric neurorehabilitation centers from Switzerland, Germany, and Austria. They had an average work experience of 13 ± 10 years. The most relevant outcome measures were the duration of lying, sitting, and standing positions; the amount of active self-propulsion during wheeling periods; the hand use laterality; and the duration, distance, and speed of walking periods. The health profession, work experience, and workplace had a minimal impact on the priorities of health professionals. Eventually, we complemented the survey findings with the family priorities of a previous study to provide developers with the clinically most relevant outcomes to monitor everyday life motor activities of children and adolescents with neuromotor impairments.

Robot-assisted gait training: more randomized controlled trials are needed! Or maybe not?

I was encouraged by the recent article by Kuo et al. entitled "Prediction of robotic neurorehabilitation functional ambulatory outcome in patients with neurological disorders" to write an opinion piece on the possible further development of stationary robot-assisted gait training research. Randomized clinical trials investigating stationary gait robots have not shown the superiority of these devices over comparable interventions regarding clinical effectiveness, and there are clinical practice guidelines that even recommend against their use. Nevertheless, these devices are still widely used, and our field needs to find ways to apply these devices more effectively. The authors of the article mentioned above feed different machine learning algorithms with patients' data from the beginning of a robot-assisted gait training intervention using the robot Lokomat. The output of these algorithms allows predictions of the clinical outcome (i.e., functional ambulation categories) while the patients are still participating in the intervention. Such an analysis based on the collection of the device's data could optimize the application of these devices. The article provides an example of how our field of research could make progress as we advance, and in this opinion piece, I would like to present my view on the prioritization of upcoming research on robot-assisted gait training. Furthermore, I briefly speculate on some drawbacks of randomized clinical trials in the field of robot-assisted gait training and how the quality and thus the effectiveness of robot-assisted gait training could potentially be improved based on the collection and analysis of clinical training data, a better patient selection and by giving greater weight to the motivational aspects for the participants.

Settings matter: a scoping review on parameters in robot-assisted gait therapy identifies the importance of reporting standards.

BACKGROUND: Lokomat therapy for gait rehabilitation has become increasingly popular. Most evidence suggests that Lokomat therapy is equally effective as but not superior to standard therapy approaches. One reason might be that the Lokomat parameters to personalize therapy, such as gait speed, body weight support and Guidance Force, are not optimally used. However, there is little evidence available about the influence of Lokomat parameters on the effectiveness of the therapy. Nevertheless, an appropriate reporting of the applied therapy parameters is key to the successful clinical transfer of study results. The aim of this scoping review was therefore to evaluate how the currently available clinical studies report Lokomat parameter settings and map the current literature on Lokomat therapy parameters. METHODS AND RESULTS: A systematic literature search was performed in three databases: Pubmed, Scopus and Embase. All primary research articles performing therapy with the Lokomat in neurologic populations in English or German were included. The quality of reporting of all clinical studies was assessed with a framework developed for this particular purpose. We identified 208 studies investigating Lokomat therapy in patients with neurologic diseases. The reporting quality was generally poor. Less than a third of the studies indicate which parameter settings have been applied. The usability of the reporting for a clinical transfer of promising results is therefore limited. CONCLUSION: Although the currently available evidence on Lokomat parameters suggests that therapy parameters might have an influence on the effectiveness, there is currently not enough evidence available to provide detailed recommendations. Nevertheless, clinicians should pay close attention to the reported therapy parameters when translating research findings to their own clinical practice. To this end, we propose that the quality of reporting should be improved and we provide a reporting framework for authors as a quality control before submitting a Lokomat-related article.

Concurrent Validity of Different Sensor-Based Measures: Activity Counts Do Not Reflect Functional Hand Use in Children and Adolescents With Upper Limb Impairments.

OBJECTIVE: To investigate the concurrent validity of 4 different outcome measures to determine daily functional hand use with wrist-worn inertial sensors in children with upper limb impairments. We hypothesized that the commonly used activity counts are biased by walking and wheeling activities, while measures that exclude arm movements during these periods with activity detection algorithms or by limiting the analysis to a range of functional forearm elevation would lead to more valid estimates of daily hand use. DESIGN: Concurrent validity study with video-based observations of functional hand use serving as the criterion measure. SETTING: The participants were videotaped while performing an activity circuit at the rehabilitation center and wearing inertial sensors. PARTICIPANTS: A convenience sample of 30 school-aged children and adolescents with upper limb impairments. INTERVENTIONS: Not applicable. MAIN OUTCOME MEASURES: Spearman rank correlation coefficients ρ between the criterion measure and 4 sensor-based measures: activity counts, combining activity counts with activity detection algorithms (arm activity counts), limiting activity counts to a functional range of forearm elevation (functional activity counts), and a threshold-based approach limited to the same range of forearm elevation (gross arm movements). RESULTS: Activity counts (ρ=0.43) and gross arm movements (ρ=0.57) did not reveal valid estimates of daily hand use. In contrast, arm and functional activity counts correlated significantly stronger with the criterion measure and revealed valid correlation coefficients of 0.78 and 0.71, respectively. CONCLUSIONS: Activity counts should not be used to measure daily hand use because they are biased by walking and wheeling activities. Arm and functional activity counts provide better and valid alternatives. The selection of these 2 approaches depends on the availability and accuracy of activity detection algorithms and on the users' willingness to wear additional sensors in daily life.

Systematic review on the application of wearable inertial sensors to quantify everyday life motor activity in people with mobility impairments.

BACKGROUND: Recent advances in wearable sensor technologies enable objective and long-term monitoring of motor activities in a patient's habitual environment. People with mobility impairments require appropriate data processing algorithms that deal with their altered movement patterns and determine clinically meaningful outcome measures. Over the years, a large variety of algorithms have been published and this review provides an overview of their outcome measures, the concepts of the algorithms, the type and placement of required sensors as well as the investigated patient populations and measurement properties. METHODS: A systematic search was conducted in MEDLINE, EMBASE, and SCOPUS in October 2019. The search strategy was designed to identify studies that (1) involved people with mobility impairments, (2) used wearable inertial sensors, (3) provided a description of the underlying algorithm, and (4) quantified an aspect of everyday life motor activity. The two review authors independently screened the search hits for eligibility and conducted the data extraction for the narrative review. RESULTS: Ninety-five studies were included in this review. They covered a large variety of outcome measures and algorithms which can be grouped into four categories: (1) maintaining and changing a body position, (2) walking and moving, (3) moving around using a wheelchair, and (4) activities that involve the upper extremity. The validity or reproducibility of these outcomes measures was investigated in fourteen different patient populations. Most of the studies evaluated the algorithm's accuracy to detect certain activities in unlabeled raw data. The type and placement of required sensor technologies depends on the activity and outcome measure and are thoroughly described in this review. The usability of the applied sensor setups was rarely reported. CONCLUSION: This systematic review provides a comprehensive overview of applications of wearable inertial sensors to quantify everyday life motor activity in people with mobility impairments. It summarizes the state-of-the-art, it provides quick access to the relevant literature, and it enables the identification of gaps for the evaluation of existing and the development of new algorithms.

ICF mobility and self-care goals of children in inpatient rehabilitation.

AIM: To develop a detailed priority list of family-centred rehabilitation goals on the activity level within the International Classification of Functioning, Disability and Health (ICF) chapters d4 'Mobility' and d5 'Self-care' in a paediatric population with a broad range of health conditions. METHOD: Twenty-two months after implementing a systematic, family-centred, goal-setting process, the rehabilitation goals of 212 inpatients were retrospectively allocated to the most detailed level of ICF categories by two independent researchers. The overall frequencies of these goals were calculated and stratified by health condition, functional independence, and age. RESULTS: Ninety-three females and 119 males were included in the study (mean age 10y 9mo, SD 4y 5mo, range 2y 1mo-21y 5mo). The five most frequent rehabilitation goals were ICF codes d4500 'Walking short distances' (11%), d4200 'Transferring oneself while sitting' (9%), d5400 'Putting on clothes' (7%), d451 'Going up and down stairs' (6%), and d4153 'Maintaining a sitting position' (5%). These top goals varied in the subgroups with regard to the underlying health condition, functional independence, and age. INTERPRETATION: The findings of this study are not generalizable due to the large heterogeneity in priorities. However, they can be used to incorporate families' needs into future research designs and the development of new technologies. WHAT THIS PAPER ADDS: Walking short distances is the most frequent mobility/self-care goal of paediatric rehabilitation. The top goals depend on health condition, functional independence, and age. Priorities vary considerably between children undergoing rehabilitation. Rehabilitation goals need to be assessed individually for each child.

Pediatric Rehabilitation Therapies Differ in Intensity: A Pilot Study to Highlight the Implications for Dose-Response Relationships.

OBJECTIVE: When investigating dose-response relationships in rehabilitation studies, dose is often equated with duration of therapy. However, according to the American College of Sports Medicine, dose consists of the factors frequency, intensity, time, and type. Thereby, especially quantification of intensity needs improvement to have a more precise estimate of the dose. Thus, the aim was to investigate the intensity during mobility-focused, real-life pediatric rehabilitation therapies. DESIGN: Eleven participants (5 girls, 12.5 ± 2.1 yrs old) with neurological disorders and independent mobility wore accelerometers at wrists and ankles and a portable heart rate monitor during several of the following therapies: sports therapy, mobility-focused physiotherapy, medical training therapy, and robot-assisted gait training. Intensity of physical activity was quantified by activity counts (measured via accelerometers) and heart rate. RESULTS: Therapy duration did not correlate with intensity. At the same time, we found significant differences between intensities of different therapies. CONCLUSION: Different therapies elicit different levels of intensity in children with neuromotor disorders. Heart rate and activity counts are suited to estimate the intensity of a therapy and provide complementary information. We recommend against using the duration of a therapy as a proxy for the dose to make statements about dose-response relationships. TO CLAIM CME CREDITS: Complete the self-assessment activity and evaluation online at http://www.physiatry.org/JournalCME CME OBJECTIVES: Upon completion of this article, the reader should be able to: (1) Appraise the importance of measuring the intensity of various types of inpatient rehabilitation therapy for determining the dose; (2) Describe the differences in intensities between different training forms and name factors that influence this intensity; and (3) Discuss the influence of the functional level of a patient on his/her potential to engage in physically intensive therapy sessions. LEVEL: Advanced. ACCREDITATION: The Association of Academic Physiatrists is accredited by the Accreditation Council for Continuing Medical Education to provide continuing medical education for physicians.The Association of Academic Physiatrists designates this journal-based CME activity for a maximum of 1.0 AMA PRA Category 1 Credit(s)™. Physicians should only claim credit commensurate with the extent of their participation in the activity.

Correction to: The FreeD module for the Lokomat facilitates a physiological movement pattern in healthy people - a proof of concept study.

The original article [1] contains an error whereby the legends of Figs. 3 and 4 are erroneously swapped. As such, the correct configuration of these legends can be seen in the same figures below instead.

The FreeD module for the Lokomat facilitates a physiological movement pattern in healthy people - a proof of concept study.

BACKGROUND: A contralateral pelvic drop, a transverse rotation and a lateral translation of the pelvis are essential features of normal human gait. These motions are often restricted in robot-assisted gait devices. The optional FreeD module of the driven gait orthosis Lokomat (Hocoma AG, Switzerland) incorporates guided lateral translation and transverse rotation of the pelvis. It consequently should support weight shifting during walking. This study aimed to investigate the influence of the FreeD module on trunk kinematics and hip and trunk muscle activity. METHODS: Thirty- one healthy adults participated. A video analysis of their trunk movements was performed to investigate the lateral chest and pelvis displacement within the Lokomat (with and without FreeD), and this was compared to treadmill walking. Furthermore, surface electromyography (sEMG) signals from eight muscles were collected during walking in the Lokomat (with and without FreeD), on the treadmill, and overground. To compare the similarity of the sEMG patterns, Spearman's correlation analyses were applied. RESULTS: Walking with FreeD elicited a significantly higher lateral pelvis displacement and a lower lateral chest displacement (relative to the pelvis) compared to walking with a fixated pelvis. No significant differences in the sEMG patterns were found for the Lokomat conditions (with and without FreeD) when comparing it to treadmill or overground walking. CONCLUSIONS: The differences in pelvis displacement act as a proof of concept of the FreeD module. The reduction of relative lateral chest movement corresponds to a decrease in compensatory trunk movements and has its origin in allowing weight shifting through the FreeD module. Both Lokomat conditions showed very similar muscle activity patterns of the trunk and hip compared to overground and treadmill walking. This indicates that the Lokomat allows a physiological muscle activity of the trunk and hip during gait.