Characterization of kinetic and kinematic parameters for wearable robotics

The design process of a wearable robotic device for human assistance requires the characterization of both kinetic and kinematic parameters (KKP) of the human joints. The first step in this process is to extract the KKP from different gait analyses studies. This work is based on the human lower limb considering the following activities of daily living (ADL): walking over ground, stairs ascending/descending, ramp ascending/descending and chair standing up. The usage of different gait analyses in the characterization process, causes the data to have great variations from one study to another. Therefore, the data is graphically represented using Matlab® and Excel® to facilitate its assessment. Finally, the characterization of the KKP performed was proved to be useful in assessing the data reliability by directly comparing all the studies between each other; providing guidelines for the selection of actuator capacities depending on the end application; and highlighting optimization opportunities such as the implementation of agonist-antagonist actuators for particular human joints

Predicting the motions and forces of wearable robotic systems using optimal control

Wearable robotic systems are being developed to prevent injury to the low back. Designing a wearable robotic system is challenging because it is difficult to predict how the exoskeleton will affect the movement of the wearer. To aid the design of exoskeletons, we formulate and numerically solve an optimal control problem (OCP) to predict the movements and forces of a person as they lift a 15 kg box from the ground both without (human-only OCP) and with (with-exo OCP) the aid of an exoskeleton. We model the human body as a sagittal-plane multibody system that is actuated by agonist and antagonist pairs of muscle torque generators (MTGs) at each joint. Using the literature as a guide, we have derived a set of MTGs that capture the active torque–angle, passive torque–angle, and torque–velocity characteristics of the flexor and extensor groups surrounding the hip, knee, ankle, lumbar spine, shoulder, elbow, and wrist. Uniquely, these MTGs are continuous to the second derivative and so are compatible with gradient-based optimization. The exoskeleton is modeled as a rigid-body mechanism that is actuated by a motor at the hip and the lumbar spine and is coupled to the wearer through kinematic constraints. We evaluate our results by comparing our predictions with experimental recordings of a human subject. Our results indicate that the predicted peak lumbar-flexion angles and extension torques of the human-only OCP are within the range reported in the literature. The results of the with-exo OCP indicate that the exoskeleton motors should provide relatively little support during the descent to the box but apply a substantial amount of support during the ascent phase. The support provided by the lumbar motor is similar in shape to the net moment generated at the L5/S1 joint by the body; however, the support of the hip motor is more complex because it is coupled to the passive forces that are being generated by the hip extensors of the human subject. The simulations developed in this study are specific to lifting motion and a lower back exoskeleton. However, the framework is applicable for simulating a large range of robotic-assisted human motions

User Intent Detection and Control of a Soft Poly-Limb

abstract: This work presents the integration of user intent detection and control in the development of the fluid-driven, wearable, and continuum, Soft Poly-Limb (SPL). The SPL utilizes the numerous traits of soft robotics to enable a novel approach to provide safe and compliant mobile manipulation assistance to healthy and impaired users. This wearable system equips the user with an additional limb made of soft materials that can be controlled to produce complex three-dimensional motion in space, like its biological counterparts with hydrostatic muscles. Similar to the elephant trunk, the SPL is able to manipulate objects using various end effectors, such as suction adhesion or a soft grasper, and can also wrap its entire length around objects for manipulation. User control of the limb is demonstrated using multiple user intent detection modalities. Further, the performance of the SPL studied by testing its capability to interact safely and closely around a user through a spatial mobility test. Finally, the limb’s ability to assist the user is explored through multitasking scenarios and pick and place tests with varying mounting locations of the arm around the user’s body. The results of these assessments demonstrate the SPL’s ability to safely interact with the user while exhibiting promising performance in assisting the user with a wide variety of tasks, in both work and general living scenarios.Dissertation/ThesisMasters Thesis Biomedical Engineering 201

On the Efficacy of Isolating Shoulder and Elbow Movements with a Soft, Portable, and Wearable Robotic Device

Treatment intensity has a profound effect on motor recovery following neurological injury. The use of robotics has potential to automate these labor-intensive therapy procedures that are typically performed by physical therapists. Further, the use of wearable robotics offers an aspect of portability that may allow for rehabilitation outside the clinic. The authors have developed a soft, portable, lightweight upper extremity wearable robotic device to provide motor rehabilitation of patients with affected upper limbs due to traumatic brain injury (TBI). A key feature of the device demonstrated in this paper is the isolation of shoulder and elbow movements necessary for effective rehabilitation interventions. Herein is presented a feasibility study with one subject and demonstration of the device's ability to provide safe, comfortable, and controlled upper extremity movements. Moreover, it is shown that by decoupling shoulder and elbow motions, desired isolated joint actuation can be achieved

JNER at 15 years: analysis of the state of neuroengineering and rehabilitation.

On JNER's 15th anniversary, this editorial analyzes the state of the field of neuroengineering and rehabilitation. I first discuss some ways that the nature of neurorehabilitation research has evolved in the past 15 years based on my perspective as editor-in-chief of JNER and a researcher in the field. I highlight increasing reliance on advanced technologies, improved rigor and openness of research, and three, related, new paradigms - wearable devices, the Cybathlon competition, and human augmentation studies - indicators that neurorehabilitation is squarely in the age of wearability. Then, I briefly speculate on how the field might make progress going forward, highlighting the need for new models of training and learning driven by big data, better personalization and targeting, and an increase in the quantity and quality of usability and uptake studies to improve translation