Gait-Symmetry-Based Human-in-the-Loop Optimization for Unilateral Transtibial Amputees With Robotic Prostheses

Abstract

Gait asymmetry due to the loss of unilateral limb increases the risk of injury or progressive joint degeneration. The development of wearable robotic devices paves a way to improve gait symmetry of unilateral amputees. Moreover, the state-of-the-art studies on human-in-the-loop optimization strategies through decreasing the metabolic cost as the optimization task, have met several challenges, e.g. too long period of optimization and the optimization feasibility for unilateral amputees who have the deficit of gait symmetry. Here, in this paper, we proposed gait-symmetry-based human-in-the-loop optimization method to decrease the risk of injury or progressive joint degeneration for unilateral transtibial amputees. The experimental results (N = 3 unilateral transtibial subjects) demonstrate that only average 9.0±4.1min of convergence was taken. Compared to gait symmetry while wearing prosthetics, after optimization, the gait symmetry indicator value of the subjects wearing the robotic prostheses was improved by 21.0% and meanwhile the net metabolic energy consumption value was reduced by 9.2%. Also, this paper explores the rationality of gait indicators and what kind of gait indicators are the optimization target. These results suggest that gait-symmetry-based human-in-the-loop strategy could pave a practical way to improve gait symmetry by accompanying the reduction of metabolic cost, and thus to decrease the risk of joint injury for the unilateral amputees. KeywordsHuman-in-the-loop, gait symmetry, metabolic cost, unilateral transtibial amputees, robotic prostheses metabolic cost rate. Moreover, few studies of human-inthe-loop focused on the unilateral amputees, who had the consequences of gait symmetry.Biological studies show that due to the loss of lower limb, the amputees exhibited the gait asymmetry in kinetics and kinematics, compared to the able-bodied Sanderson and Martin (1997). For the unilateral amputees, this kind of gait asymmetry influences the maximum torque and torque steadiness significantly in the intact leg in some extents Simoneau-Buessinger et al. (2019). The reason for gait asymmetry maybe mainly resulted from strength asymmetry Lloyd et al. (2010), during walking. Strength asymmetry in unilateral transtibial amputees has a moderate relationship in an increased risk of developing osteoarthritis Lloyd et al. (2010). For the transtibial amputees, the walking speed also influenced gait symmetry Nolan et al. (2003). During jumping landing, peak force asymmetry and moment asymmetry may potentially be easy to result in injury or progressive joint degeneration for transtibial amputees and improving gait symmetry in jumping is

Improving Walking Energy Efficiency in Transtibial Amputees Through the Integration of a Low-Power Actuator in an ESAR Foot

“…Energy release was set between 45% and 55% of the gait cycle. An alternative approach to the manual tuning of assistive parameters is to use Human-In-the-Loop Optimization (HILO) algorithms, which demonstrated significant advantages in the automatic tuning of multiple parameters in fully-powered prostheses [44]. However, the specific nature of the WRL TTP prosthesis (with only one parameter to tune via software) makes this approach unnecessarily complex.…”

Robotic Leg Prosthesis: A Survey From Dynamic Model to Adaptive Control for Gait Coordination

“…According to (14), we provide advances on how to achieve stochastic coordination using adaptive control methods. We also consider two categories depending on the controller levels: adaptation to stochastically uneven terrains (high-level) and constrained adaptation to random uncertainty (low-level), as shown in TABLE IV.…”

“…It mainly benefits from the collaborative behaviors of locomotion systems observed in the real world [12] [13]. Therefore, gait coordination (GC) awareness of prosthesis-human systems (PHSs) has attracted much attention from the dynamics field over the past decades [14]. To enhance GC performance, recent advancements in robotic leg prostheses primarily focus on two aspects: dynamic models [15] and adaptive control methods [16][17] [18].…”