Andrea Parri

A light-weight active orthosis for hip movement assistance

In the last decades, wearable powered orthoses have been developed with the aim of augmenting or assisting motor activities. In particular, among many applications, wearable powered orthoses have been also introduced in the state of the art with the goal of providing lower-limb movement assistance in locomotion-related tasks (e.g.: walking, ascending/descending stairs) in scenarios of activities of daily living. In this paper we present a light-weight active orthosis endowed with two series elastic actuators for hip flexion-extension assistance. Along with the description of its mechatronic modules, we report the experimental characterization of the performance of the actuation and control system, as well as the usability test carried out with a healthy subject. Results showed a suitable dynamic behavior of the actuation unit: the closed-loop torque control bandwidth is about 15 Hz and the output impedance ranges from about 1 N m/rad to 35 N m/rad in the frequency spectrum between 0.2 and 3.2 Hz. Results from the tests with the healthy subject proved the overall system usability: the subject could walk with the device without being hindered and while he received a smooth assistive flexion-extension torque profile on both hip articulations. Development of a novel light-weight wearable powered bilateral pelvis orthosis.Design of a novel compact, light-weight series-elastic actuator (SEA).SEA closed-loop torque control bandwidth equal to 15 Hz.SEA output impedance ranges from 1 to 35 N m /rad in human gait frequency spectrum.The overall system usability was proved by tests with a healthy subject.

Walking Assistance Using Artificial Primitives: A Novel Bioinspired Framework Using Motor Primitives for Locomotion Assistance Through a Wearable Cooperative Exoskeleton

Bioinspiration in robotics deals with applying biological principles to the design of better performing devices. In this article, we propose a novel bioinspired framework using motor primitives for locomotion assistance through a wearable cooperative exoskeleton. In particular, the use of motor primitives for assisting different locomotion modes (i.e., ground-level walking at several cadences and ascending and descending stairs) is explored by means of two different strategies. In the first strategy, identified motor primitives are combined through weights to directly produce the desired assistive torque profiles. In the second strategy, identified motor primitives are combined to serve as neural stimulations to a virtual model of the musculoskeletal system, which, in turn, produces the desired assistive torque profiles.

An oscillator-based smooth real-time estimate of gait phase for wearable robotics

This paper presents a novel methodology for estimating the gait phase of human walking through a simple sensory apparatus. Three subsystems are combined: a primary phase estimator based on adaptive oscillators, a desired gait event detector and a phase error compensator. The estimated gait phase is expected to linearly increase from 0 to 2

Response time analysis for G-EDF and G-DM scheduling of sporadic DAG-tasks with arbitrary deadline

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A novel adaptive oscillators-based control for a powered multi-joint lower-limb orthosis

π rad in one stride and remain continuous also when transiting to the next stride. We designed two experimental scenarios to validate this gait phase estimator, namely treadmill walking at different speeds and free walking. In the case of treadmill walking, the maximum phase error at the desired gait events was found to be 0.155 rad, and the maximum phase difference between the end of the previous stride and beginning of the current stride was 0.020 rad. In the free walking trials, phase error at the desired gait event was never larger than 0.278 rad. Our algorithm outperformed against two other benchmarked methods. The good performance of our gait phase estimator could provide consistent and finely tuned assistance for an exoskeleton designed to augment the mobility of patients.

Experimental Validation of Motor Primitive-Based Control for Leg Exoskeletons during Continuous Multi-Locomotion Tasks

The response time analysis (RTA) is one of the fundamental tools used to guarantee the schedulability of sets of real-time tasks scheduled by Fixed Priorities. Also, several analysis methods inspired by RTA have been successfully developed to address more sophisticated execution platforms (distributed systems, multiprocessor) and application models (DAGs). The major issue with RTA is its time complexity, which is NP-hard. Such a complexity shows up when the task set has high utilization and RTA needs to check all jobs until the first idle instant. In this paper, we propose a continuous upper bound to the response time with quadratic time complexity in the number of tasks. Such an upper bound is demonstrated to be tighter than previously proposed ones with linear time complexity. In addition, with two tasks only, we prove that the proposed bound is the tightest continuous function upper bounding the exact response time of sets of tasks with full utilization. Whether or not this property holds with more than two tasks is still an open problem.

Gait Phase Estimation Based on Noncontact Capacitive Sensing and Adaptive Oscillators

New programming models have been proposed to exploit the parallelism of modern computing architectures. Also in the real-time domain more detailed task models are under evaluation to provide a tighter analysis of parallel application with precedence and timing constraints. This paper presents two schedulability tests based on Response Time Analysis for determining whether a set of sporadic DAG-tasks with arbitrary deadlines can be scheduled by G-EDF or G-DM on a platform consisting of m identical processor. The first test is a simple polynomial time test, while the second one is a pseudo-polynomial time test. Our tests exploit the combinatorial properties of the DAGs by considering the interference experienced by each vertex. We describe a set of simulations showing that our tests outperform the tests described in [7] in terms of schedulability ratio and running time. We also provide resource augmentation bounds for our polynomial time test when considering single-DAG systems.

Whole Body Awareness for Controlling a Robotic Transfemoral Prosthesis

This paper presents a realtime locomotion mode recognition method for an active pelvis orthosis. Five locomotion modes, including sitting, standing still, level-ground walking, ascending stairs, and descending stairs, are taken into consideration. The recognition is performed with locomotion information measured by the onboard hip angle sensors and the pressure insoles. These five modes are firstly divided into static modes and dynamic modes, and the two kinds are classified by monitoring the variation of the relative hip angles of the two legs within a pre-defined period. Static states are further classified into sitting and standing still based on the absolute hip angle. As for dynamic modes, a fuzzy-logic based method is proposed for the recognition. Two event-based locomotion features, including the hip joint angle at the first foot-strike and the center of foot pressure at the first foot-strike are used to calculate the membership of different modes based on the membership function, and the mode with the maximal membership is selected as the target mode. Experimental results with three subjects achieve an average recognition accuracy of 99.87% and average recognition delay of 18.12% of one gait cycle.