Response to perturbation during quiet standing resembles delayed state feedback optimized for performance and robustness

Torque modulation mechanism of the knee joint during balance recovery

Exploring the torque modulation mechanisms of human joints is critical for analyzing the human balance control system and developing natural human-machine interactions for balance support. However, the knee joint is often overlooked in biomechanical models because of its limited range of motion during balance recovery. This poses a challenge in establishing mathematical models for the knee joint's torque modulation mechanisms using computer simulations based on the inverted pendulum model. This study aims to provide a simplified linear feedback model inspired by sensorimotor transformation theory to reveal the torque modulation mechanism of the knee joint. The model was validated using data from experiments involving support-surface translation perturbations. The goodness-of-fit metrics of the model, including R2 values and root mean square errors (RMSE), demonstrated strong explanatory power (R2 ranged from 0.77 to 0.90) and low error (RMSE ranging from 0.035 to 0.072) across different perturbation magnitudes and directions. Through pooling samples across various perturbation conditions and conducting multiple fits, this model revealed that knee torque is modulated using a direction-specific strategy with adaptable feedback gains. These results suggest that the proposed simplified linear model can be used to develop assistive systems and retrieve insights on balance recovery mechanisms.

Time-delay estimation in biomechanical stability: a scoping review

Despite its high-level of robustness and versatility, the human sensorimotor control system regularly encounters and manages various noises, non-linearities, uncertainties, redundancies, and delays. These delays, which are critical to biomechanical stability, occur in various parts of the system and include sensory, signal transmission, CNS processing, as well as muscle activation delays. Despite the relevance of accurate estimation and prediction of the various time delays, the current literature reflects major discrepancy with regards to existing prediction and estimation methods. This scoping review was conducted with the aim of characterizing and categorizing various approaches for estimation of physiological time delays based on PRISMA guidelines. Five data bases (EMBASE, PubMed, Scopus, IEEE and Web of Science) were consulted between the years of 2000 and 2022, with a combination of four related categories of keywords. Scientific articles estimating at least one physiological time delay, experimentally or through simulations, were included. Eventually, 46 articles were identified and analyzed with 20 quantification and 16 qualification questions by two separate reviewers. Overall, the reviewed studies, experimental and analytical, employing both linear and non-linear models, reflected heterogeneity in the definition of time delay and demonstrated high variability in experimental protocols as well as the estimation of delay values. Most of the summarized articles were classified in the high-quality category, where multiple sound analytical approaches, including optimization, regression, Kalman filter and neural network in time domain or frequency domain were used. Importantly, more than 50% of the reviewed articles did not clearly define the nature of the estimated delays. This review presents and summarizes these issues and calls for a standardization of future scientific works for estimation of physiological time-delay.

Optimal controllers resembling postural sway during upright stance

The human postural control system can maintain our balance in an upright stance. A simplified control model that can mimic the mechanisms of this complex system and adapt to the changes due to aging and injuries is a significant problem that can be used in clinical applications. While the Intermittent Proportional Derivative (IPD) is commonly used as a postural sway model in the upright stance, it does not consider the predictability and adaptability behavior of the human postural control system and the physical limitations of the human musculoskeletal system. In this article, we studied the methods based on optimization algorithms that can mimic the performance of the postural sway controller in the upright stance. First, we compared three optimal methods (Model Predictive Control (MPC), COP-Based Controller (COP-BC) and Momentum-Based Controller (MBC)) in simulation by considering a feedback structure of the dynamic of the skeletal body as a double link inverted pendulum while taking into account sensory noise and neurological time delay. Second, we evaluated the validity of these methods by the postural sway data of ten subjects in quiet stance trials. The results revealed that the optimal methods could mimic the postural sway with higher accuracy and less energy consumption in the joints compared to the IPD method. Among optimal approaches, COP-BC and MPC show promising results to mimic the human postural sway. The choice of controller weights and parameters is a trade-off between the consumption of energy in the joints and the prediction accuracy. Therefore, the capability and (dis)advantage of each method reviewed in this article can navigate the usage of each controller in different applications of postural sway, from clinical assessments to robotic applications.

Exploring the effects of serial and parallel elasticity on a hopping robot

The interaction between the motor control and the morphological design of the human leg is critical for generating efficient and robust locomotion. In this paper, we focus on exploring the effects of the serial and parallel elasticity on hopping with a two-segmented robotic leg called electric-pneumatic actuation (EPA)-Hopper. EPA-Hopper uses a hybrid actuation system that combines electric motors and pneumatic artificial muscles (PAM). It provides direct access to adjust the physical compliance of the actuation system by tuning PAM pressures. We evaluate the role of the serial and parallel PAMs with different levels of compliance with respect to four criteria: efficiency, performance, stability, and robustness of hopping against perturbations. The results show that the serial PAM has a more pronounced impact than the parallel PAM on these criteria. Increasing the stiffness of the serial PAM decreases the leg stiffness of the unloading phase during hopping. The stiffer the leg, the more efficient and the less robust the movement. These findings can help us further understand the human hopping mechanism and support the design and control of legged robots and assistive devices.

Control of structural redundancy from the head to trunk in the human upright standing revealed using a data-driven approach

The human being dynamically and highly controls the head-trunk with redundant mechanical structures to maintain a stable upright standing position that is inherently unstable. The posture control strategies are also affected by the differences in the conditions of sensory inputs. However, it is unclear how the head-trunk segmental properties are altered to respond to situations that require appropriate changes in standing posture control strategies. We used a data-driven approach to conduct a multipoint measurement of head-trunk sway control in a quiet standing position with differences in the conditions of sensory inputs. Healthy young subjects with 22 accelerometers attached to their backs were evaluated for head-trunk vibration during quiet standing under two conditions: one with open eyes and one with closed eyes. The synchronization of the acceleration and the instantaneous phase was then calculated. The results showed that the synchronization of acceleration and instantaneous phase varied depending on the visual condition, and there were some continuous coherent patterns in each condition. Findings were that the structural redundancy of the head-trunk, which is multi-segmental and has a high mass ratio in the whole body, must be adjusted adaptively according to the conditions to stabilize upright standing in human-specific bipeds.

Virtual stick balancing: skill development in Newtonian and Aristotelian dynamics

Human reaction delay significantly limits manual control of unstable systems. It is more difficult to balance a short stick on a fingertip than a long one, because a shorter stick falls faster and therefore requires faster reactions. In this study, a virtual stick balancing environment was developed where the reaction delay can be artificially modulated and the law of motion can be changed between second-order (Newtonian) and first-order (Aristotelian) dynamics. Twenty-four subjects were separated into two groups and asked to perform virtual stick balancing programmed according to either Newtonian or Aristotelian dynamics. The shortest stick length (critical length, L_c) was determined for different added delays in six sessions of balancing trials performed on different days. The observed relation between L_c and the overall reaction delay τ reflected the feature of the underlying mathematical models: (i) for the Newtonian dynamics L_c is proportional to τ²; (ii) for the Aristotelian dynamics L_c is proportional to τ. Deviation of the measured L_c(τ) function from the theoretical one was larger for the Newtonian dynamics for all sessions, which suggests that, at least in virtually controlled tasks, it is more difficult to adopt second-order dynamics than first-order dynamics.