Noninvasive spinal stimulation improves walking in chronic stroke survivors: a proof-of-concept case series.

BACKGROUND: After stroke, restoring safe, independent, and efficient walking is a top rehabilitation priority. However, in nearly 70% of stroke survivors asymmetrical walking patterns and reduced walking speed persist. This case series study aims to investigate the effectiveness of transcutaneous spinal cord stimulation (tSCS) in enhancing walking ability of persons with chronic stroke. METHODS: Eight participants with hemiparesis after a single, chronic stroke were enrolled. Each participant was assigned to either the Stim group (N = 4, gait training + tSCS) or Control group (N = 4, gait training alone). Each participant in the Stim group was matched to a participant in the Control group based on age, time since stroke, and self-selected gait speed. For the Stim group, tSCS was delivered during gait training via electrodes placed on the skin between the spinous processes of C5-C6, T11-T12, and L1-L2. Both groups received 24 sessions of gait training over 8 weeks with a physical therapist providing verbal cueing for improved gait symmetry. Gait speed (measured from 10 m walk test), endurance (measured from 6 min walk test), spatiotemporal gait symmetries (step length and swing time), as well as the neurophysiological outcomes (muscle synergy, resting motor thresholds via spinal motor evoked responses) were collected without tSCS at baseline, completion, and 3 month follow-up. RESULTS: All four Stim participants sustained spatiotemporal symmetry improvements at the 3 month follow-up (step length: 17.7%, swing time: 10.1%) compared to the Control group (step length: 1.1%, swing time 3.6%). Additionally, 3 of 4 Stim participants showed increased number of muscle synergies and/or lowered resting motor thresholds compared to the Control group. CONCLUSIONS: This study provides promising preliminary evidence that using tSCS as a therapeutic catalyst to gait training may increase the efficacy of gait rehabilitation in individuals with chronic stroke. Trial registration NCT03714282 (clinicaltrials.gov), registration date: 2018-10-18.

Modular hip exoskeleton improves walking function and reduces sedentary time in community-dwelling older adults.

BACKGROUND: Despite the benefits of physical activity for healthy physical and cognitive aging, 35% of adults over the age of 75 in the United States are inactive. Robotic exoskeleton-based exercise studies have shown benefits in improving walking function, but most are conducted in clinical settings with a neurologically impaired population. Emerging technology is starting to enable easy-to-use, lightweight, wearable robots, but their impact in the otherwise healthy older adult population remains mostly unknown. For the first time, this study investigates the feasibility and efficacy of using a lightweight, modular hip exoskeleton for in-community gait training in the older adult population to improve walking function. METHODS: Twelve adults over the age of 65 were enrolled in a gait training intervention involving twelve 30-min sessions using the Gait Enhancing and Motivating System for Hip in their own senior living community. RESULTS: Performance-based outcome measures suggest clinically significant improvements in balance, gait speed, and endurance following the exoskeleton training, and the device was safe and well tolerated. Gait speed below 1.0 m/s is an indicator of fall risk, and two out of the four participants below this threshold increased their self-selected gait speed over 1.0 m/s after intervention. Time spent in sedentary behavior also decreased significantly. CONCLUSIONS: This intervention resulted in greater improvements in speed and endurance than traditional exercise programs, in significantly less time. Together, our results demonstrated that exoskeleton-based gait training is an effective intervention and novel approach to encouraging older adults to exercise and reduce sedentary time, while improving walking function. Future work will focus on whether the device can be used independently long-term by older adults as an everyday exercise and community-use personal mobility device. Trial registration This study was retrospectively registered with ClinicalTrials.gov (ID: NCT05197127).

Video-Based Pose Estimation for Gait Analysis in Stroke Survivors during Clinical Assessments: A Proof-of-Concept Study.

Recent advancements in deep learning have produced significant progress in markerless human pose estimation, making it possible to estimate human kinematics from single camera videos without the need for reflective markers and specialized labs equipped with motion capture systems. Such algorithms have the potential to enable the quantification of clinical metrics from videos recorded with a handheld camera. Here we used DeepLabCut, an open-source framework for markerless pose estimation, to fine-tune a deep network to track 5 body keypoints (hip, knee, ankle, heel, and toe) in 82 below-waist videos of 8 patients with stroke performing overground walking during clinical assessments. We trained the pose estimation model by labeling the keypoints in 2 frames per video and then trained a convolutional neural network to estimate 5 clinically relevant gait parameters (cadence, double support time, swing time, stance time, and walking speed) from the trajectory of these keypoints. These results were then compared to those obtained from a clinical system for gait analysis (GAITRite®, CIR Systems). Absolute accuracy (mean error) and precision (standard deviation of error) for swing, stance, and double support time were within 0.04 ± 0.11 s; Pearson's correlation with the reference system was moderate for swing times (r = 0.4-0.66), but stronger for stance and double support time (r = 0.93-0.95). Cadence mean error was -0.25 steps/min ± 3.9 steps/min (r = 0.97), while walking speed mean error was -0.02 ± 0.11 m/s (r = 0.92). These preliminary results suggest that single camera videos and pose estimation models based on deep networks could be used to quantify clinically relevant gait metrics in individuals poststroke, even while using assistive devices in uncontrolled environments. Such development opens the door to applications for gait analysis both inside and outside of clinical settings, without the need of sophisticated equipment.

A Novel Technique to Reject Artifact Components for Surface EMG Signals Recorded During Walking With Transcutaneous Spinal Cord Stimulation: A Pilot Study.

Transcutaneous spinal cord electrical stimulation (tSCS) is an emerging technology that targets to restore functionally integrated neuromuscular control of gait. The purpose of this study was to demonstrate a novel filtering method, Artifact Component Specific Rejection (ACSR), for removing artifacts induced by tSCS from surface electromyogram (sEMG) data for investigation of muscle response during walking when applying spinal stimulation. Both simulated and real tSCS contaminated sEMG data from six stroke survivors were processed using ACSR and notch filtering, respectively. The performance of the filters was evaluated with data collected in various conditions (e.g., simulated artifacts contaminating sEMG in multiple degrees, various tSCS intensities in five lower-limb muscles of six participants). In the simulation test, after applying the ACSR filter, the contaminated-signal was well matched with the original signal, showing a high correlation (r = 0.959) and low amplitude difference (normalized root means square error = 0.266) between them. In the real tSCS contaminated data, the ACSR filter showed superior performance on reducing the artifacts (96% decrease) over the notch filter (25% decrease). These results indicate that ACSR filtering is capable of eliminating artifacts from sEMG collected during tSCS application, improving the precision of quantitative analysis of muscle activity.

Characterization of Motor-Evoked Responses Obtained with Transcutaneous Electrical Spinal Stimulation from the Lower-Limb Muscles after Stroke.

An increasing number of studies suggests that a novel neuromodulation technique targeting the spinal circuitry enhances gait rehabilitation, but research on its application to stroke survivors is limited. Therefore, we investigated the characteristics of spinal motor-evoked responses (sMERs) from lower-limb muscles obtained by transcutaneous spinal cord stimulation (tSCS) after stroke compared to age-matched and younger controls without stroke. Thirty participants (ten stroke survivors, ten age-matched controls, and ten younger controls) completed the study. By using tSCS applied between the L1 and L2 vertebral levels, we compared sMER characteristics (resting motor threshold (RMT), slope of the recruitment curve, and latency) of the tibialis anterior (TA) and medial gastrocnemius (MG) muscles among groups. A single pulse of stimulation was delivered in 5 mA increments, increasing from 5 mA to 250 mA or until the subjects reached their maximum tolerance. The stroke group had an increased RMT (27-51%) compared to both age-matched (TA: p = 0.032; MG: p = 0.005) and younger controls (TA: p < 0.001; MG: p<0.001). For the TA muscle, the paretic side demonstrated a 13% increased latency compared to the non-paretic side in the stroke group (p = 0.010). Age-matched controls also exhibited an increased RMT compared to younger controls (TA: p = 0.002; MG: p = 0.007), suggesting that altered sMER characteristics present in stroke survivors may result from both stroke and normal aging. This observation may provide implications for altered spinal motor output after stroke and demonstrates the feasibility of using sMER characteristics as an assessment after stroke.

Age-Related Differences in Head Impact during Experimentally Induced Sideways Falls.

PURPOSE: To examine head impact incidence and head acceleration during experimentally induced falls as a function of age. METHODS: 15 young adults (21.2±2.7) and 10 older adults (61.9±4.3 years) underwent 6 experimentally induced sideways falls. Participants fell sideways onto a 20cm crash pad. The number of head impacts was tabulated from video recordings and head acceleration was calculated from motion capture data. A total of 147 falls were analyzed. RESULTS: The young group underwent 88 falls, in which 11.4% resulted in head impact. The older group underwent 59 falls, in which 34.5% resulted in head impact. A proportion analysis revealed older adults had a significantly greater proportion of head impacts than young adults (X 2(1) = 11.445, p = 0.001). A two-way ANOVA only revealed a main effect of head impact on acceleration (F(1,142) = 54.342, p<0.001). CONCLUSION: The older adults experienced a greater proportion of head impacts during sideways falls. Head impact resulted in greater head acceleration compared to no head impact. Collectively, this data highlights the possibility that age-related neuromuscular changes to head control may result in elevated risk of fall-related TBIs. Future research examining mechanisms underlying increases in fall-related head impact is warranted.

Preliminary investigation of teaching older adults the tuck-and-roll strategy: Can older adults learn to fall with reduced impact severity.

Falls are common and potentially disastrous for older adults. A novel approach that could augment current fall prevention procedures is to teach older adults movement strategies to reduce the risk of injury. The purpose of the study was to determine whether older adults can learn a movement strategy ("tuck-and-roll") that reduces fall impact severity. Learning was quantified with short-term acquisition, bilateral transfer and 1-week-retention. 14 healthy older individuals participated (63.9 ±â€¯5.6 years) in the investigation. Participants were randomly assigned into either training group (n = 7) or active control group (n = 7). All participants performed standardized sideway falls at baseline, immediately post intervention and 1-week-retention tests. During the falling assessments, kinetic and kinematic impact severity parameters were measured. The results for short-term learning revealed that the training group showed greater reduction in hip impact force (33% reduction) than the control group (16% reduction). Furthermore, there was partial bilateral transfer effect and 1-week retention observed in the training group. The observations provide preliminary evidence that teaching tuck-and-roll strategy to older adults has potential effect. The observations provide preliminary evidence that older adults might reduce impact severity utilizing tuck-and-roll strategy during unpredictably-timed sideway falls.

Validating Virtual Time to Contact With Home Based Technology in Young and Older Adults.

Virtual time to contact (VTC) is a measure of postural stability that estimates the virtual time it would take to reach an individual's stability boundary. This study aimed to validate VTC as measured by a depth sensor, and to determine if VTC from the depth sensor distinguishes between older adult fallers and non-fallers compared to a force platform. VTC was assessed in 10 young and 20 older adults by having participants lean in a circular direction followed by five balance tests: eyes open, dual task, eyes open foam, eyes closed, and eyes closed foam. Spearman's correlations and Bland-Altman plots were conducted to determine validity, and Receiver Operating Curves were constructed to discriminate between fallers and non-fallers. Significant correlations were found in the dual task (p = 0.03), eyes open foam (p < 0.01), and eyes closed foam conditions (p = 0.05). The depth sensor discriminated between fallers and non-fallers in the eyes open (p = 0.02), dual task (p = 0.03), and eyes open foam conditions (p = 0.04). VTC was in agreement between the two devices, and VTC derived from a depth sensor and may be used to discriminate between older adult fallers and non-fallers during challenging balance conditions.

Assessment of Postural Sway in Individuals with Multiple Sclerosis Using a Novel Wearable Inertial Sensor.

Balance impairment is common in individuals with multiple sclerosis (MS). However, objective assessment of balance usually requires clinical expertise and/or the use of expensive and obtrusive measuring equipment. These barriers to the objective assessment of balance may be overcome with the development of a lightweight inertial sensor system. In this study, we examined the concurrent validity of a novel wireless, skin-mounted inertial sensor system (BioStamp®, MC10 Inc.) to measure postural sway in individuals with MS by comparing measurement agreement between this novel sensor and gold standard measurement tools (force plate and externally validated inertial sensor). A total of 39 individuals with MS and 15 healthy controls participated in the study. Participants with MS were divided into groups based on the amount of impairment (MSMild: EDSS 2-4, n = 19; MSSevere: EDSS ≥6, n = 20). The balance assessment consisted of two 30-s quiet standing trials in each of three conditions: eyes open/firm surface, eyes closed/firm surface, and eyes open/foam surface. For each trial, postural sway was recorded with a force plate (Bertec) and simultaneously using two accelerometers (BioStamp and Xsens) mounted on the participant's posterior trunk at L5. Sway metrics (sway area, sway path length, root mean square amplitude, mean velocity, JERK, and total power) were derived to compare the measurement agreement among the measurement devices. Excellent agreement (intraclass correlation coefficients >0.9) between sway metrics derived from the BioStamp and the MTx sensors were observed across all conditions and groups. Good to excellent correlations (r >0.7) between devices were observed in all sway metrics and conditions. Additionally, the acceleration sway metrics were nearly as effective as the force plate sway metrics in differentiating individuals with poor balance from healthy controls. Overall, the BioStamp sensor is a valid and objective measurement tool for postural sway assessment. This novel, lightweight and portable sensor may offer unique advantages in tracking patient's postural performance.

A machine learning approach for gait speed estimation using skin-mounted wearable sensors: From healthy controls to individuals with multiple sclerosis.

Gait speed is a powerful clinical marker for mobility impairment in patients suffering from neurological disorders. However, assessment of gait speed in coordination with delivery of comprehensive care is usually constrained to clinical environments and is often limited due to mounting demands on the availability of trained clinical staff. These limitations in assessment design could give rise to poor ecological validity and limited ability to tailor interventions to individual patients. Recent advances in wearable sensor technologies have fostered the development of new methods for monitoring parameters that characterize mobility impairment, such as gait speed, outside the clinic, and therefore address many of the limitations associated with clinical assessments. However, these methods are often validated using normal gait patterns; and extending their utility to subjects with gait impairments continues to be a challenge. In this paper, we present a machine learning method for estimating gait speed using a configurable array of skin-mounted, conformal accelerometers. We establish the accuracy of this technique on treadmill walking data from subjects with normal gait patterns and subjects with multiple sclerosis-induced gait impairments. For subjects with normal gait, the best performing model systematically overestimates speed by only 0.01 m/s, detects changes in speed to within less than 1%, and achieves a root-mean-square-error of 0.12 m/s. Extending these models trained on normal gait to subjects with gait impairments yields only minor changes in model performance. For example, for subjects with gait impairments, the best performing model systematically overestimates speed by 0.01 m/s, quantifies changes in speed to within 1%, and achieves a root-mean-square-error of 0.14 m/s. Additional analyses demonstrate that there is no correlation between gait speed estimation error and impairment severity, and that the estimated speeds maintain the clinical significance of ground truth speed in this population. These results support the use of wearable accelerometer arrays for estimating walking speed in normal subjects and their extension to MS patient cohorts with gait impairment.

Monitoring gait in multiple sclerosis with novel wearable motion sensors.

BACKGROUND: Mobility impairment is common in people with multiple sclerosis (PwMS) and there is a need to assess mobility in remote settings. Here, we apply a novel wireless, skin-mounted, and conformal inertial sensor (BioStampRC, MC10 Inc.) to examine gait characteristics of PwMS under controlled conditions. We determine the accuracy and precision of BioStampRC in measuring gait kinematics by comparing to contemporary research-grade measurement devices. METHODS: A total of 45 PwMS, who presented with diverse walking impairment (Mild MS = 15, Moderate MS = 15, Severe MS = 15), and 15 healthy control subjects participated in the study. Participants completed a series of clinical walking tests. During the tests participants were instrumented with BioStampRC and MTx (Xsens, Inc.) sensors on their shanks, as well as an activity monitor GT3X (Actigraph, Inc.) on their non-dominant hip. Shank angular velocity was simultaneously measured with the inertial sensors. Step number and temporal gait parameters were calculated from the data recorded by each sensor. Visual inspection and the MTx served as the reference standards for computing the step number and temporal parameters, respectively. Accuracy (error) and precision (variance of error) was assessed based on absolute and relative metrics. Temporal parameters were compared across groups using ANOVA. RESULTS: Mean accuracy±precision for the BioStampRC was 2±2 steps error for step number, 6±9ms error for stride time and 6±7ms error for step time (0.6-2.6% relative error). Swing time had the least accuracy±precision (25±19ms error, 5±4% relative error) among the parameters. GT3X had the least accuracy±precision (8±14% relative error) in step number estimate among the devices. Both MTx and BioStampRC detected significantly distinct gait characteristics between PwMS with different disability levels (p<0.01). CONCLUSION: BioStampRC sensors accurately and precisely measure gait parameters in PwMS across diverse walking impairment levels and detected differences in gait characteristics by disability level in PwMS. This technology has the potential to provide granular monitoring of gait both inside and outside the clinic.

Unplanned gait termination in individuals with multiple sclerosis.

Despite the pervasive nature of gait impairment in multiple sclerosis (MS), there is limited information concerning the control of gait termination in individuals with MS. The purpose of this investigation was to examine unplanned gait termination with and without cognitive distractors in individuals with MS compared to healthy controls. Thirty-one individuals with MS and 14 healthy controls completed a series of unplanned gait termination tasks over a pressure sensitive walkway under distracting and non-distracting conditions. Individuals with MS were further broken down into groups based on assistive device use: (no assistive device (MSnoAD) n=18; and assistive device (MSAD) n=13). Individuals with MS who walked with an assistive device (MSAD: 67.8±15.1cm/s) walked slower than individuals without an assistive device (MSnoAD: 110.4±32.3cm/s, p<0.01) and controls (120.0±30.0cm/s; p<0.01). There was a significant reduction in velocity in the cognitively distracting condition (93.4±32.1cm/s) compared to the normal condition [108.8±36.2cm/s; F(1,43)=3.4, p=0.04]. All participants took longer to stop during the distracting condition (1.7±0.6s) than the non-distracting condition (1.4±0.4s; U=673.0 p<0.01). After controlling for gait velocity, post-hoc analysis revealed the MSAD group took significantly longer to stop compared to the control group (p=0.05). Further research investigating the control of unplanned gait termination in MS is warranted.

Safe Landing Strategies During a Fall: Systematic Review and Meta-Analysis.

OBJECTIVES: To systematically synthesize information on safe landing strategies for a fall, and quantitatively examine the effects of the strategies to reduce the risk of injury from a fall. DATA SOURCES: PubMed, Web of Science, Cumulative Index to Nursing and Allied Health Literature, and Cochrane Library. STUDY SELECTION: Databases were searched using the combinations of keywords of "falls," "strategy," "impact," and "load." Randomized controlled trials, cohort studies, pre-post studies, and cross-sectional studies were included. DATA EXTRACTION: Fall strategies were extracted and categorized by falling direction. Measurements of impact loads that reflect the risk of injuries were extracted (eg, impact velocity, impact force, fall duration, impact angle). Hedges' g was used as effect size to quantify the effect of a protective landing strategy to reduce the impact load. DATA SYNTHESIS: A total of 7 landing strategies (squatting, elbow flexion, forward rotation, martial arts rolling, martial arts slapping, relaxed muscle, stepping) in 13 studies were examined. In general, all strategies, except for the martial arts slapping technique, significantly reduced impact load (g values=.73-2.70). Squatting was an efficient strategy to reduce impact in backward falling (g=1.77), while elbow flexion with outstretched arms was effective in forward falling (g=.82). Also, in sideways falling strategies, martial arts rolling (g=2.70) and forward rotation (g=.82) were the most efficient strategies to reduce impact load. CONCLUSIONS: The results showed that landing strategies have a significant effect on reducing impact load during a fall and might be effective to reduce the impact load of falling. The current study also highlighted limitations of the previous studies that focused on a young population and self-initiated falls. Further investigation with elderly individuals and unexpected falls is necessary to verify the effectiveness and suitability of the strategies for at-risk populations in real-life falls.

Shoulder pain and time dependent structure in wheelchair propulsion variability.

Manual wheelchair propulsion places considerable repetitive mechanical strain on the upper limbs leading to shoulder injury and pain. While recent research indicates that the amount of variability in wheelchair propulsion and shoulder pain may be related. There has been minimal inquiry into the fluctuation over time (i.e. time-dependent structure) in wheelchair propulsion variability. Consequently the purpose of this investigation was to examine if the time-dependent structure in the wheelchair propulsion parameters are related to shoulder pain. 27 experienced wheelchair users manually propelled their own wheelchair fitted with a SMARTWheel on a roller at 1.1m/s for 3min. Time-dependent structure of cycle-to-cycle fluctuations in contact angle and inter push time interval was quantified using sample entropy (SampEn) and compared between the groups with/without shoulder pain using non-parametric statistics. Overall findings were, (1) variability observed in contact angle fluctuations during manual wheelchair propulsion is structured (Z=3.15;p<0.05), (2) individuals with shoulder pain exhibited higher SampEn magnitude for contact angle during wheelchair propulsion than those without pain (χ(2)(1)=6.12;p<0.05); and (3) SampEn of contact angle correlated significantly with self-reported shoulder pain (rs (WUSPI) =0.41;rs (VAS)=0.56;p<0.05). It was concluded that the time-dependent structure in wheelchair propulsion may provide novel information for tracking and monitoring shoulder pain.

Gait variability in people with neurological disorders: A systematic review and meta-analysis.

There has been growing evidence showing gait variability provides unique information about gait characteristics in neurological disorders. This study systemically reviewed and quantitatively synthesized (via meta-analysis) existing evidence on gait variability in various neurological diseases, including Alzheimer's disease (AD), amyotrophic lateral sclerosis (ALS), cerebellar ataxia (CA), Huntington's disease (HD), multiple sclerosis (MS), and Parkinson's disease (PD). Keyword search were conducted in PubMed, Web of science, Cumulative Index to Nursing and Allied Health Literature, and Cochrane Library. Meta-analysis was performed to estimate the pooled effect size for gait variability for each neurological group. Meta-regression was performed to compare gait variability across multiple groups with neurological diseases. Gait variability of 777 patients with AD, ALS, CA, HD, MS, or PD participating in 25 studies was included in meta-analysis. All pathological groups had increased amount of gait variability and loss of fractal structure of gait dynamics compared to healthy controls, and gait variability differentiated distinctive neurological conditions. The HD groups had the highest alterations in gait variability among all pathological groups, whereas the PD, AD and MS groups had the lowest. Interventions that aim to improve gait function in patients with neurological disorders should consider the heterogeneous relationship between gait variability and neurological conditions.

Variability in Wheelchair Propulsion: A New Window into an Old Problem.

Manual wheelchair users are at great risk for the development of upper extremity injury and pain. Any loss of upper limb function due to pain adversely impacts the independence and mobility of manual wheelchair users. There is growing theoretical and empirical evidence that fluctuations in movement (i.e., motor variability) are related to musculoskeletal pain. This perspectives paper discusses a local review on several investigations examining the association between variability in wheelchair propulsion and shoulder pain in manual wheelchair users. The experimental data reviewed highlights that the variability of wheelchair propulsion is impacted by shoulder pain in manual wheelchair users. We maintain that inclusion of these metrics in future research on wheelchair propulsion and upper limb pain may yield novel data. Several promising avenues for future research based on this collective work are discussed.

Preliminary investigation of gait initiation and falls in multiple sclerosis.

OBJECTIVE: To examine the relationship between gait initiation, fall history, and physiological fall risk in individuals with multiple sclerosis (MS) during both cognitive distracting and nondistracting conditions. DESIGN: Single time point cross-sectional analysis. SETTING: University research laboratory. PARTICIPANTS: Ambulatory individuals (N=20) with MS ranging in age from 28 to 76 years. INTERVENTION: Not applicable. MAIN OUTCOME MEASURES: Gait initiation time was quantified as the time to toe-off of the first step after an auditory cue. Gait initiation was performed with and without a concurrent cognitive challenge of reciting alternating letters of the alphabet. Additionally, participants underwent a test of fall risk using the Physiological Profile Assessment (PPA) and provided a self-report of the number of falls in the previous 3 months. RESULTS: Gait initiation times ranged from .67 to 1.12 seconds during the single-task condition and .73 to 1.84 seconds during the cognitive challenge condition. PPA scores ranged from -.80 to 3.87. Participants reported a median of 0.0 falls (interquartile range, 0.0-2.75) in the previous 3 months. There was a significant correlation between PPA score and gait initiation times only in the cognitive distraction condition (ρ=.50). There was also a correlation between cognitive distraction gait initiation times and fall history (ρ=.60). CONCLUSIONS: The observations provide preliminary evidence that gait initiation during cognitive challenge may represent a target for fall prevention strategies in MS.

Fall risk and incidence reduction in high risk individuals with multiple sclerosis: a pilot randomized control trial.

OBJECTIVE: To determine the feasibility of three fall prevention programs delivered over 12 weeks among individuals with multiple sclerosis: (A) a home-based exercise program targeting physiological risk factors; (B) an educational program targeting behavioral risk factors; and (C) a combined exercise-and-education program targeting both factors. DESIGN: Randomized controlled trial. SETTING: Home-based training with assessments at research laboratory. PARTICIPANTS: A total of 103 individuals inquired about the investigation. After screening, 37 individuals with multiple sclerosis who had fallen in the last year and ranged in age from 45-75 years volunteered for the investigation. A total of 34 participants completed postassessment following the 12-week intervention. INTERVENTION: Participants were randomly assigned into one of four conditions: (1) wait-list control (n = 9); (2) home-based exercise (n = 11); (3) education (n = 9); or (4) a combined exercise and education (n = 8) group. MEASURES: Before and after the 12-week interventions, participants underwent a fall risk assessment as determined by the physiological profile assessment and provided information on their fall prevention behaviors as indexed by the Falls Prevention Strategy Survey. Participants completed falls diaries during the three-months postintervention. RESULTS: A total of 34 participants completed postintervention testing. Procedures and processes were found to be feasible. Overall, fall risk scores were lower in the exercise groups (1.15 SD 1.31) compared with the non-exercise groups (2.04 SD 1.04) following the intervention (p < 0.01). There was no group difference in fall prevention behaviors (p > 0.05). CONCLUSIONS: Further examination of home-based exercise/education programs for reducing falls in individuals with multiple sclerosis is warranted. A total of 108 participants would be needed in a larger randomized controlled trial.ClinicalTrials.org #NCT01956227.

Stride-Time Variability and Fall Risk in Persons with Multiple Sclerosis.

Gait variability is associated with falls in clinical populations. However, gait variability's link to falls in persons with Multiple Sclerosis (PwMS) is not well established. This investigation examined the relationship between stride-time variability, fall risk, and physiological fall risk factors in PwMS. 17 PwMS (62.8 ± 7.4 years) and 17 age-matched controls (62.8 ± 5.9 years) performed the 6-minute walk test. Stride-time was assessed with accelerometers attached to the participants' shanks. Stride-time variability was measured by interstride coefficient of variation (CV) of stride-time. The participant's fall risk was measured by the short form physiological profile assessment (PPA). A Spearman correlation analysis was used to determine the relationship between variables. Increased fall risk was strongly associated with increased stride-time CV in both PwMS (ρ = 0.71, p < 0.01) and the controls (ρ = 0.67, p < 0.01). Fall risk was not correlated with average stride-time (p > 0.05). In PwMS, stride-time CV was related to postural sway (ρ = 0.74, p < 0.01) while in the control group, it was related to proprioception (ρ = 0.61, p < 0.01) and postural sway (ρ = 0.78, p < 0.01). Current observations suggest that gait variability is maybe more sensitive marker of fall risk than average gait parameters in PwMS. It was also noted that postural sway may be potentially targeted to modify gait variability in PwMS.

Shoulder pain and cycle to cycle kinematic spatial variability during recovery phase in manual wheelchair users: a pilot investigation.

UNLABELLED: Wheelchair propulsion plays a significant role in the development of shoulder pain in manual wheelchair users (MWU). However wheelchair propulsion metrics related to shoulder pain are not clearly understood. This investigation examined intra-individual kinematic spatial variability during semi-circular wheelchair propulsion as a function of shoulder pain in MWU. Data from 10 experienced adult MWU with spinal cord injury (5 with shoulder pain; 5 without shoulder pain) were analyzed in this study. Participants propelled their own wheelchairs on a dynamometer at 3 distinct speeds (self-selected, 0.7 m/s, 1.1 m/s) for 3 minutes at each speed. Motion capture data of the upper limbs were recorded. Intra-individual kinematic spatial variability of the steady state wrist motion during the recovery phase was determined using principal component analysis (PCA). The kinematic spatial variability was calculated at every 10% intervals (i.e at 11 interval points, from 0% to 100%) along the wrist recovery path. RESULTS: Overall, spatial variability was found to be highest at the start and end of the recovery phase and lowest during the middle of the recovery path. Individuals with shoulder pain displayed significantly higher kinematic spatial variability than individuals without shoulder pain at the start (at 10% interval) of the recovery phase (p<.004). CONCLUSIONS: Analysis of intra-individual kinematic spatial variability during the recovery phase of manual wheelchair propulsion distinguished between those with and without shoulder pain. Variability analysis of wheelchair propulsion may offer a new approach to monitor the development and rehabilitation of shoulder pain.