A Motor Learning Oriented, Compliant and Mobile Gait Orthosis

Abstract

People affected by Cerebral Palsy suffer from physical disabilities due to irreversible neural impairment since the very beginning of their life. Difficulties in motor control and coordination often relegate these patients to the use of a wheelchair and to the unavoidable upcoming of disuse syndromes. As pointed out in recent literature Damiano [7] physical exercise, especially in young ages, can have a deep impact on the patient health and quality of life. For training purposes is very important to keep an upright position, although in some severe cases this is not trivial. Many commercial mobile orthoses are designed to facilitate the standing, but not all the patients are able to deploy them. ARGO, the Active Reciprocated Gait Orthosis we developed, is a device that overcomes some of the limitations of these devices. It is an active device that is realized starting from a commercial reciprocated Gait Orthosis applying sensors and actuators to it. With ARGO we aim to develop a device for helping limbs in a non-coercive way accordingly to user’s intention. In this way patients can drive the orthosis by themselves, deploying augmented biofeedback over movements. In fact Cerebral Palsy patients usually have weak biofeedback mechanisms and consequently are hardly inclined to learn movements. To achieve this behavior ARGO deploys a torque planning algorithm and a force control system. Data collected from a single case of study shows benefits of the orthosis. We will show that our test patient reaches complete autonomous walking after few hour of training with prototype.

Robust Force Control of Series Elastic Actuators

“…In this work, we focus on stability and performance at the force control level, regardless of the specific assistive algorithm. Assuring the stability and well-defined performance of a "human in the loop system" is very challenging, because human modeling introduces many uncertainties, as already observed in the literature [8] and in our previous experience (In particular, in [9], one can observe the different force control responses when the orthosis is worn by the real patient instead of a manikin) [9,10]. Uncertainties can be addressed using classical robust control, which ensures the stability and desired performance within a well-defined uncertainty set, which is supposed to include the real system.…”

Human-adaptive control of series elastic actuators

“…In the control application, the worst case is when c, or equivalently r, is high, showing high sensitivity to the human joint model. This can be seen in (6) where r multiplies human forces/tuques. Unfortunately, this is often the case of SEAs where geared motors are usually adopted.…”

“…The first controller that we propose is based on the compensation of certain dynamics aiming to make the τ/τ h relation behaving like a second-order system. We consider an arranged version of system (6),…”

“…Several control algorithms have been proposed following this "assist as needed" approach, e.g. "path control," "virtual model control," "clime," gravity compensation, 6,13 or impedance control. 25 This class of algorithms is built upon a force/torque controller that is supposed to be ideally fast.…”

Investigation on Inter-Limb Coordination and Motion Stability, Intensity and Complexity of Trunk and Limbs during Hands-Knees Crawling in Human Adults

“…Normal crawling is often regarded as a sign of the normal development of infants and young children [ 1 ]. Crawling can be divided into hand-knee type, hand-foot type, scooting type, creeping type, and mixed type, etc.…”