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Background: The company Ethnocare has developed the Overlay, a new pneumatic solution for managing volumetric variations (VVs) of the residual limb (RL) in transtibial amputees (TTAs), which improves socket fitting. However, the impact of the Overlay during functional tasks and on the comfort and pain felt in the RL is unknown. Methods: 8 TTAs participated in two evaluations, separated by two weeks. We measured compensatory strategies (CS) using spatio-temporal parameters and three-dimensional lower limb kinematics and kinetics during gait and sit-to-stand (STS) tasks. During each visit, the participant carried out our protocol while wearing the Overlay and prosthetic folds (PFs), the most common solution to VV. Between each task, comfort and pain felt were assessed using visual analog scales. Results: While walking, the cadence with the Overlay was 105 steps/min, while it was 101 steps/min with PFs (p = 0.021). During 35% and 55% of the STS cycle, less hip flexion was observed while wearing the Overlay compared to PFs (p = 0.004). We found asymmetry coefficients of 13.9% with the Overlay and 17% with PFs during the STS (p = 0.016) task. Pain (p = 0.031), comfort (p = 0.017), and satisfaction (p = 0.041) were better with the Overlay during the second visit. Conclusion: The Overlay's impact is similar to PFs' but provides less pain and better comfort. [ABSTRACT FROM AUTHOR]

Altered tibiofemoral contact forces represent a risk factor for osteoarthritis onset and progression, making optimization of the knee force distribution a target of treatment strategies. Musculoskeletal model-based simulations are a state-of-the-art method to estimate joint contact forces, but they typically require laboratory-based input and skilled operators. To overcome these limitations, ambulatory methods, relying on inertial measurement units, have been proposed to estimated ground reaction forces and, consequently, knee contact forces out-of-the-lab. This study proposes the use of a full inertial-capture-based musculoskeletal modelling workflow with an underlying probabilistic principal component analysis model trained on 1787 gait cycles in patients with knee osteoarthritis. As validation, five patients with knee osteoarthritis were instrumented with 17 inertial measurement units and 76 opto-reflective markers. Participants performed multiple overground walking trials while motion and inertial capture methods were synchronously recorded. Moderate to strong correlations were found for the inertial capture-based knee contact forces compared to motion capture with root mean square error between 0.15 and 0.40 of body weight. The results show that our workflow can inform and potentially assist clinical practitioners to monitor knee joint loading in physical therapy sessions and eventually assess long-term therapeutic effects in a clinical context. [ABSTRACT FROM AUTHOR]

Segmenting the gait cycle into multiple phases using gait event detection (GED) is a well-researched subject with many accurate algorithms. However, the algorithms that are able to perform accurate and robust GED for real-life environments and physical diseases tend to be too complex for their implementation on simple hardware systems limited in computing power and memory, such as those used in wearable devices. This study focuses on a numerical implementation of a reservoir computing (RC) algorithm called the echo state network (ESN) that is based on simple computational steps that are easy to implement on portable hardware systems for real-time detection. RC is a neural network method that is widely used for signal processing applications and uses a fast-training method based on a ridge regression adapted to the large quantity and variety of IMU data needed to use RC in various real-life environment GED. In this study, an ESN was used to perform offline GED with gait data from IMU and ground force sensors retrieved from three databases for a total of 28 healthy adults and 15 walking conditions. Our main finding is that despite its low complexity, ESN is robust for GED, with performance comparable to other state-of-the-art algorithms. Our results show the ESN is robust enough to obtain good detection results in all conditions if the algorithm is trained with variable data that match those conditions. The distribution of the mean absolute errors (MAE) between the detection times from the ESN and the force sensors were between 40 and 120 ms for 6 defined gait events (95th percentile). We compared our ESN with four different state-of-the-art algorithms from the literature. The ESN obtained a MAE not more than 10 ms above three other reference algorithms for normal walking indoor and outdoor conditions and yielded the 2nd lowest MAE and the 2nd highest true positive rate and specificity when applied to outdoor walking and running conditions. Our work opens the door to using the ESN as a GED for applications in wearable sensors for long-term patient monitoring. [ABSTRACT FROM AUTHOR]

For individuals with altered sensory cues, vibrotactile feedback improves their balance control. However, should vibrotactile feedback be provided every time balance control is compromised, or only one-third of the time their balance is compromised? We hypothesized that vibrotactile feedback would improve balance control more when provided every time their balance is compromised. Healthy young adults were randomly assigned to two groups: group 33% feedback (6 males and 6 females) and group 100% feedback (6 males and 6 females). Vibrotactile feedbacks related to the body's sway angle amplitude and direction were provided, while participants stood upright on a foam surface with their eyes closed. Then, we assessed if balance control improvement lasted when the vibrotactile feedback was removed (i.e., post-vibration condition). Finally, we verified whether or not vibrotactile feedback unrelated to the body's sway angle and direction (sham condition) altered balance control. The results revealed no significant group difference in balance control improvement during vibrotactile feedback. Immediately following vibrotactile feedback, both groups reduced their balance control commands; body sway velocity and the ground reaction forces variability decreased. For both groups, unrelated vibrotactile feedback worsened balance control. These results confirmed that participants processed and implemented vibrotactile feedback to control their body sways. Less vibrotactile feedback was effective in improving balance control. [ABSTRACT FROM AUTHOR]

Gait parameters are altered and asymmetrical in individuals with transtibial amputation. The purpose of this study was to evaluate and compare the effect of four different prosthetic feet on lower-limb biomechanics during gait. A 34-year-old man with transtibial amputation performed four gait analysis sessions with four foot-ankle prostheses (Variflex, Meridium, Echelon, and Kinterra). Kinematic and kinetic parameters and gait symmetry were analyzed in different prosthetic conditions. The type of prosthesis had little effect on the participant's spatiotemporal parameters. Throughout the stance phase, increased hip angle, reduced knee flexion and ankle dorsiflexion were observed in the amputated leg. For kinetic parameters, reduced propulsive force (SI = 0.42-0.65), reduced knee extension moment (mainly during Echelon and Kinterra conditions, SI = 0.17 and 0.32, respectively), and increased knee abduction moment (mainly during the Variflex and Meridium, SI = 5.74 and 8.93, respectively) were measured in the amputated leg. Lower support moments were observed in the amputated leg as compared to the unaffected leg, regardless of the type of prosthesis (SI = 0.61-0.80). The prostheses tested induced different lower-limb mechanical adaptations. In order to achieve the clinical goal of better gait symmetry between lower limbs, an objective gait analysis could help clinicians to prescribe prosthetic feet based on quantitative measurement indicators to optimize gait rehabilitation.