Project Description

Our overall goal is to improve the quality of life of older adults with smart soft robots and imaging systems that will immunize them against falls. The two thrusts of the project are: i) smart soft robotic carpet that changes topography and safely applies controlled perturbations to humans, ii) fast and robust computer models for control and design of the soft robots.

Falls are the leading cause of fatal and non-fatal injuries in older adults resulting in a loss of independence and financial burden (predicted to exceed $54 billion by 2020 by the National Safety Council). Exposure to gait perturbations in a controlled environment (i.e. while preventing an actual fall) reduces falls because the central nervous system learns the appropriate corrective action. Current methods for such training apply only one type of perturbation in the anterior-posterior direction, while real-world perturbations occur in all directions. We will harness the unique advantages of soft robotic systems to train the gait of individuals under a wide range of perturbations. Advantages of using soft robots in this space are: i) they are lightweight and portable, enabling use even in rural areas, ii) they are highly configurable, and iii) they are safe for human interaction.

Start Date

June 2020

Postdoc Qualifications 

Must have a PhD in one of the following or related fields: biomedical engineering, mechanical engineering, electrical engineering, or industrial engineering. Must be interested in research in the field of soft robots and modeling. Must demonstrate excellent communication skills, in the form of published papers and conference presentations. Prior experience with soft robots is desirable.

Co-advisors 

Mohit Verma
msverma@purdue.edu
Assistant Professor, Nanotechnology Preeminent team
Birck Nanotechnology Center
Department of Agricultural and Biological Engineering
Weldon School of Biomedical Engineering
www.vermalab.com

Adrian Buganza-Tepole
abuganza@purdue.edu 
Assistant Professor
School of Mechanical Engineering
https://engineering.purdue.edu/buganzalab/people

References 

Rietdyk, S. & Rhea, C. K. Control of adaptive locomotion: effect of visual obstruction and visual cues in the environment. Exp. Brain Res. 169, 272–278 (2006).

Verma, M. S., Ainla, A., Yang, D., Harburg, D. & Whitesides, G. M. A Soft Tube-Climbing Robot. Soft Robot. 5, (2017).

Ainla, A., Verma, M. S., Yang, D. & Whitesides, G. M. Soft, Rotating Pneumatic Actuator. Soft Robot. 4, 297–304 (2017).

Yang, D. et al. Buckling pneumatic linear actuators inspired by muscle. Adv. Mater. Technol. 1, (2016).

Lee, T., Turin, S. Y., Gosain, A. K., Bilionis, I. & Buganza Tepole, A. Propagation of material behavior uncertainty in a nonlinear finite element model of reconstructive surgery. Biomech. Model. Mechanobiol. 17, 1857–1873 (2018).