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Abstract Background & purpose Afferent input from the sole affects postural stability. Cutaneous reflexes from the foot are important to posture and gait. Lower-limb afferents alone provide enough information to maintain upright stance and are critical in perceiving postural sway. Altered feedback from propreoceptive receptors alters gait and patterns of muscle activation. The position and posture of the foot and ankle may also play an important role in proprioceptive input.Therefore, the current research aims to compare static balance and ankle and knee proprioception in people with and without flexible flatfeet. Methodology 91 female students between the ages of 18 and 25 voluntarily participated in this study, of which 24 were in the flexible flatfoot group and 67 were in the regular foot group after evaluating the longitudinal arch of the foot. The position sense of ankle and knee joints were measured using the active reconstruction test of the ankle and knee angle; Static balance was measured using the Sharpened Romberg test. Data were non-normally distributed. Accordingly, non-parametric tests were applied. The Kruskal-Wallis test was applied to compare differences between groups in variables. Result Kruskal-Wallis test showed a significant difference between two groups of flat feet and normal feet in the variables of static balance and position sense of ankle plantarflexion, ankle dorsiflexion, and knee flexion (p ≤ 0.05). A significant correlation was found between static balance and sense of ankle and knee position in the group with normal feet. The analysis of the regression line also showed that ankle and knee position sense could predict the static balance score in the regular foot group (ankle dorsiflexion position sense 17% (R2 = 0.17), ankle plantarflexion position sense 17% (R2 = 0.17) and knee flexion position sense 46% (R2 = 0.46) explain of changes in static balance). Discussion & conclusion Flexible flatfoot soles can cause loss of balance and sense of joint position; therefore, according to this preliminary study, clinicians must be aware and should take into account this possible deficit in the management of these patients.

The purpose of this study was to evaluate the use of compressible soft robotic sensors (C-SRS) in determining plantar pressure to infer vertical and shear forces in wearable technology: A ground reaction pressure sock (GRPS). To assess pressure relationships between C-SRS, pressure cells on a BodiTrakTM Vector Plate, and KistlerTM Force Plates, thirteen volunteers performed three repetitions of three different movements: squats, shifting center-of-pressure right to left foot, and shifting toes to heels with C-SRS in both anterior−posterior (A/P) and medial−lateral (M/L) sensor orientations. Pearson correlation coefficient of C-SRS to BodiTrakTM Vector Plate resulted in an average R-value greater than 0.70 in 618/780 (79%) of sensor to cell comparisons. An average R-value greater than 0.90 was seen in C-SRS comparison to KistlerTM Force Plates during shifting right to left. An autoregressive integrated moving average (ARIMA) was conducted to identify and estimate future C-SRS data. No significant differences were seen in sensor orientation. Sensors in the A/P orientation reported a mean R2 value of 0.952 and 0.945 in the M/L sensor orientation, reducing the effectiveness to infer shear forces. Given the high R values, the use of C-SRSs to infer normal pressures appears to make the development of the GRPS feasible.

The linearity of soft robotic sensors (SRS) was recently validated for movement angle assessment using a rigid body structure that accurately depicted critical movements of the foot−ankle complex. The purpose of this study was to continue the validation of SRS for joint angle movement capture on 10 participants (five male and five female) performing ankle movements in a non-weight bearing, high-seated, sitting position. The four basic ankle movements—plantar flexion (PF), dorsiflexion (DF), inversion (INV), and eversion (EVR)—were assessed individually in order to select good placement and orientation configurations (POCs) for four SRS positioned to capture each movement type. PF, INV, and EVR each had three POCs identified based on bony landmarks of the foot and ankle while the DF location was only tested for one POC. Each participant wore a specialized compression sock where the SRS could be consistently tested from all POCs for each participant. The movement data collected from each sensor was then compared against 3D motion capture data. R-squared and root-mean-squared error averages were used to assess relative and absolute measures of fit to motion capture output. Participant robustness, opposing movements, and gender were also used to identify good SRS POC placement for foot−ankle movement capture.