Bipedal Model and Hybrid Zero Dynamics of Human Walking with Foot Slip

Foot slip is one of the major causes of falls in human locomotion. Analytical bipedal models provide an insight into the complex slip dynamics and reactive control strategies for slip-induced fall prevention. Most of the existing bipedal dynamics models are built on no foot slip assumption and cannot be used directly for such analysis. We relax the no-slip assumption and present a new bipedal model to capture and predict human walking locomotion under slip. We first validate the proposed slip walking dynamic model by tuning and optimizing the model parameters to match the experimental results. The results demonstrate that the model successfully predicts both the human walking and recovery gaits with slip. Then, we extend the hybrid zero dynamics (HZD) model and properties to capture human walking with slip. We present the closed-form of the HZD for human walking and discuss the transition between the non-slip and slip states through slip recovery control design. The analysis and design are illustrated through human walking experiments. The models and analysis can be further used to design and control wearable robotic assistive devices to prevent slip-and-fall

Toward Intelligent Biped-Humanoids Gaits Generation

In this chapter we will highlight our experimental studies on natural human walking analysis and introduce a biologically inspired design for simple bipedal locomotion system of humanoid robots. Inspiration comes directly from human walking analysis and human muscles mechanism and control. A hybrid algorithm for walking gaits generation is then proposed as an innovative alternative to classically used kinematics and dynamic equations solving, the gaits include knee, ankle and hip trajectories. The proposed algorithm is an intelligent evolutionary based on particle swarm optimization paradigm. This proposal can be used for small size humanoid robots, with a knee an ankle and a hip and at least six Degrees of Freedom (DOF).Comment: 15 page

Uner Tan Syndrome: History, Clinical Evaluations, Genetics, and the\ud Dynamics of Human Quadrupedalism

Abstract: This review includes for the first time a dynamical systems analysis of human quadrupedalism in Uner Tan syndrome, which is characterized by habitual quadrupedalism, impaired intelligence, and rudimentary speech. The first family was discovered in a small village near Iskenderun, and families were later found in Adana and two other small villages near Gaziantep and Canakkale. In all the affected individuals dynamic balance was impaired during upright walking,and they habitually preferred walking on all four extremities. MRI scans showed inferior cerebellovermian hypoplasia with slightly simplified cerebral gyri in three of the families, but appeared normal in the fourth. PET scans showed a decreased glucose metabolic activity in the cerebellum, vermis and, to a lesser extent the cerebral cortex, except for one patient,\ud whose MRI scan also appeared to be normal. All four families had consanguineous marriages in their pedigrees,\ud suggesting autosomal recessive transmission. The syndrome was genetically heterogeneous. Since the initial discoveries\ud more cases have been found, and these exhibit facultative quadrupedal locomotion, and in one case, late childhood onset. It has been suggested that the human quadrupedalism may, at least, be a phenotypic example of reverse evolution. From the viewpoint of dynamic systems theory, it was concluded there may not be a single factor that predetermines human quadrupedalism in Uner Tan syndrome, but that it may involve self-organization, brain plasticity, and rewiring, from the many decentralized and local interactions among neuronal, genetic, and environmental subsystems

Analysis of Dynamic Parameters of Observation Towers in Latvia

The purpose of this research is to experimentally identify the performance of most of the light-weight observation towers open for public in Latvia. It analyzes the structure of towers, technical condition, dynamic parameters and dynamic response to human movement along the tower height. During the experiment there were measured and recorded the vibration accelerations of 18 observation towers’ upper platform. Further dynamic parameters were extracted using the spectral analysis. There was performed the sensitivity analysis to establish parameters that most influences the dynamic response amplitudes due to human movement. All experimentally obtained fundamental frequencies of the inspected towers are in the typical range of human walking frequencies. It is found that the main parameter that denotes the response level (acceleration amplitude) of the tower due to human movement is a tower self-weight

Effectively Quantifying the Performance of Lower-Limb Exoskeletons Over a Range of Walking Conditions

Exoskeletons and other wearable robotic devices have a wide range of potential applications, including assisting patients with walking pathologies, acting as tools for rehabilitation, and enhancing the capabilities of healthy humans. However, applying these devices effectively in a real-world setting can be challenging, as the optimal design features and control commands for an exoskeleton are highly dependent on the current user, task and environment. Consequently, robust metrics and methods for quantifying exoskeleton performance are required. This work presents an analysis of walking data collected for healthy subjects walking with an active pelvis exoskeleton over three assistance scenarios and five walking contexts. Spatial and temporal, kinematic, kinetic and other novel dynamic gait metrics were compared to identify which metrics exhibit desirable invariance properties, and so are good candidates for use as a stability metric over varying walking conditions. Additionally, using a model-based approach, the average metabolic power consumption was calculated for a subset of muscles crossing the hip, knee and ankle joints, and used to analyse how the energy-reducing properties of an exoskeleton are affected by changes in walking context. The results demonstrated that medio-lateral centre of pressure displacement and medio-lateral margin of stability exhibit strong invariance to changes in walking conditions. This suggests that these dynamic gait metrics are optimised in human gait and are potentially suitable metrics for optimising in an exoskeleton control paradigm. The effectiveness of the exoskeleton at reducing human energy expenditure was observed to increase when walking on an incline, where muscles aiding in hip flexion were assisted, but decrease when walking at a slow speed. These results underline the need for adaptive control algorithms for exoskeletons if they are to be used in varied environments

Influence of the controller design on the accuracy of a forward dynamic simulation of human gait

The analysis of a captured motion can be addressed by means of forward or inverse dynamics approaches. For this purpose, a 12 segment 2D model with 14 degrees of freedom is developed and both methods are implemented using multibody dynamics techniques. The inverse dynamic analysis uses the experimentally captured motion to calculate the joint torques produced by the musculoskeletal system during the movement. This information is then used as input data for a forward dynamic analysis without any control design. This approach is able to reach the desired pattern within half cycle. In order to achieve the simulation of the complete gait cycle two different control strategies are implemented to stabilize all degrees of freedom: a proportional derivative (PD) control and a computed torque control (CTC). The selection of the control parameters is presented in this work: a kinematic perturbation is used for tuning PD gains, and pole placement techniques are used in order to determine the CTC parameters. A performance evaluation of the two controllers is done in order to quantify the accuracy of the simulated motion and the control torques needed when using one or the other control approach to track a known human walking pattern.Postprint (author's final draft

Automatic learning of 3D pose variability in walking performances for gait analysis

This paper proposes an action specific model which automatically learns the variability of 3D human postures observed in a set of training sequences. First, a Dynamic Programing synchronization algorithm is presented in order to establish a mapping between postures from different walking cycles, so the whole training set can be synchronized to a common time pattern. Then, the model is trained using the public CMU motion capture dataset for the walking action, and a mean walking performance is automatically learnt. Additionally statistics about the observed variability of the postures and motion direction are also computed at each time step. As a result, in this work we have extended a similar action model successfully used for tracking, by providing facilities for gait analysis and gait recognition applications.Peer ReviewedPreprin

Static and dynamic accuracy of an innovative miniaturized wearable platform for short range distance measurements for human movement applications

Magneto-inertial measurement units (MIMU) are a suitable solution to assess human motor performance both indoors and outdoors. However, relevant quantities such as step width and base of support, which play an important role in gait stability, cannot be directly measured using MIMU alone. To overcome this limitation, we developed a wearable platform specifically designed for human movement analysis applications, which integrates a MIMU and an Infrared Time-of-Flight proximity sensor (IR-ToF), allowing for the estimate of inter-object distance. We proposed a thorough testing protocol for evaluating the IR-ToF sensor performances under experimental conditions resembling those encountered during gait. In particular, we tested the sensor performance for different (i) target colors; (ii) sensor-target distances (up to 200 mm) and (iii) sensor-target angles of incidence (AoI) (up to 60°). Both static and dynamic conditions were analyzed. A pendulum, simulating the oscillation of a human leg, was used to generate highly repeatable oscillations with a maximum angular velocity of 6 rad/s. Results showed that the IR-ToF proximity sensor was not sensitive to variations of both distance and target color (except for black). Conversely, a relationship between error magnitude and AoI values was found. For AoI equal to 0°, the IR-ToF sensor performed equally well both in static and dynamic acquisitions with a distance mean absolute error <1.5 mm. Errors increased up to 3.6 mm (static) and 11.9 mm (dynamic) for AoI equal to ±30°, and up to 7.8 mm (static) and 25.6 mm (dynamic) for AoI equal to ±60°. In addition, the wearable platform was used during a preliminary experiment for the estimation of the inter-foot distance on a single healthy subject while walking. In conclusion, the combination of magneto-inertial unit and IR-ToF technology represents a valuable alternative solution in terms of accuracy, sampling frequency, dimension and power consumption, compared to existing technologies