Functional electrical stimulation (FES) walking interventions have demonstrated improvements to gait parameters; however, studies were often confined to stimulation of one or two muscle groups. Increased options such as number of muscle groups targeted, timing of stimulation delivery, and level of stimulation are needed to address subject-specific gait deviations. We aimed to demonstrate the feasibility of using a FES system with increased stimulation options during walking in children with cerebral palsy (CP). Three physical therapists designed individualized stimulation programs for six children with CP to target participant-specific gait deviations. Stimulation settings (pulse duration and current) were tuned to each participant. Participants donned our custom FES system that utilized gait phase detection to control stimulation to lower extremity muscle groups and walked on a treadmill at a self-selected speed. Motion capture data were collected during walking with and without the individualized stimulation program. Eight gait metrics and associated timing were compared between walking conditions. The prescribed participant-specific stimulation programs induced significant change towards typical gait in at least one metric for each participant with one iteration of FES-walking. FES systems with increased stimulation options have the potential to allow the physical therapist to better target the individual’s gait deviations than a one size fits all device.

Recumbent stationary cycling is a potential exercise modality for individuals with cerebral palsy (CP) that lack the postural control needed for upright exercises. Functional electrical stimulation (FES) of lower extremity muscles can help such individuals reach the cycling intensities that are required for aerobic benefits. The aim of this study was to examine the effect of cycling with and without FES assistance to that of a no-intervention control group on the cardiorespiratory fitness of children with CP. Thirty-nine participants were randomized to a FES group that underwent an 8-week FES-assisted cycling program, the volitional group (VOL), who cycled without FES, or a no-intervention control group (CON) (15 FES, 11 VOL, 13 CON). Cadence, peak VO₂, and net rise in heart rate were assessed at baseline, end of training, and washout (8-weeks after cessation of training). Latent growth curve modeling was used for analysis. The FES group showed significantly higher cycling cadences than the VOL and CON groups at POST and WO. There were no differences in improvements in the peak VO₂ and peak net HR between groups. FES-assisted cycling may help children with CP attain higher cycling cadences and to retain these gains after training cessation. Higher training intensities may be necessary to obtain improvements in peak VO₂ and heart rate.

Aims: Clinical evaluation of balance has relied on forceplate systems as the gold standard for postural sway measures. Recently, systems based on wireless inertial sensors have been explored, mostly in the adult population, as an alternative given their practicality and lower cost. Our goal was to validate body-worn sensors against forceplate balance measures in typically developing children during tests of quiet stance. Methods: 18 participants (8 males) 7 to 17 years old performed a quiet stance test standing on a forceplate while wearing 3 inertial sensors. Three 30-second trials were performed under 4 conditions: firm surface with eyes open and closed, and foam surface with eyes open and closed. Sway area, path length, and sway velocity were calculated. Results: We found 20 significant and 8 non-significant correlations. Variables found to be significant were represented across all conditions, except for the foam eyes closed condition. Conclusions: These results support the validity of wearable sensors in measuring postural sway in children. Inertial sensors may represent a viable alternative to the gold standard forceplate to test static balance in children.

This is the first study to objectively measure gait, balance, and upper limb coordination in a group of patients with NPC1 and compare the results to age and gender matched controls. This is also the first study to report effect sizes in these measures. Spatiotemporal gait analysis, static and dynamic posturography, and upper limb reaching motion analysis were performed. The findings showed that the NPC1 subjects had statistically significant deficits on 12 out of the 16 parameters investigated compared to controls, and large effect sizes for all but 1 parameter. When ranking the variables in terms of the effect sizes, the top 5 included at least 1 parameter from each of the 3 motor domains investigated. These results can provide insight to clinical researchers on the selection of outcome measures for longitudinal and interventional studies.

Gait analysis has applications in medical diagnosis, biometrics, and development of therapeutic rehabilitation interventions (such as orthotics, prosthetics, and exoskeletons). While offering accurate measurements, gait laboratories are expensive, not scalable, and not easily accessible. In a pandemic-afflicted world, where telemedicine is crucial, there is need for subject-driven data remote collection. This study proposed a remote and purely subject-driven procedure for reproducible and scalable collection of real-life gait data. To evaluate the feasibility of our proposed procedure, the spatiotemporal parameters of gait were compared across two real-life terrains using a smartphone application on a focus population of healthy middle-aged individuals. Previous research validated smartphone motion sensors as accurate instruments for gait analysis, but required highly supervised, controlled environments on smaller sample sizes, thereby limiting application in real-life gait analysis. To this end, a custom-designed mobile application was developed to record lower extremity angular velocities on 69 healthy middle-aged adults; factoring in a subject-driven data submission error rate (DSER) of 17.4%, there were 57 usable data sets for analysis. Comparisons of spatiotemporal gait parameters across primary outcome measures on grass versus asphalt revealed significant measurable increases in gait duration (stride time), valley depth (max swing phase), and peak-to-valley (max stance phase to max swing phase). These results demonstrated the feasibility of using smartphones for a remote and fully subject-driven gait data collection. Additionally, our data analysis showed that even in short trials, a physical environmental load has a substantial and measurable effect on the gait of the understudied middle-aged population.