Lab Affiliation(s):
Biomimetic Robotics Lab
Advisor:
Prof Sangbae Kim
Areas of Expertise:
  • Robotics
  • Sensors
  • Machine Learning
Expected date of graduation:
May 1, 2017

Meng Yee (Michael) Chuah

  • PhD

Department: 

  • Mechanical Engineering

Lab Affiliation(s): 

Biomimetic Robotics Lab

Advisor: 

Prof Sangbae Kim

Top 3 Areas of Expertise: 

Robotics
Sensors
Machine Learning

Expected date of graduation: 

May 1, 2017

CV: 

Thesis Title: 

Design Principles for Multi-Axis Force Detecting and Slip Predicting Sensors for Use in Robotic Applications

Thesis Abstract: 

We are developing the next generation of lightweight, low-cost, multi-axis force sensors that can be fully integrated into smart shoes, prosthetic devices, and robotic exoskeletons to provide the real-time ground reaction force data that would enable new capabilities in various fields such as healthcare, sports analytics, virtual reality, and robotics.

Our approach maps the sampled stress distribution inside a polymeric footpad to forces in three axes using machine learning techniques. This approach is to resolve the limitations of conventional force sensors where strains are measured using heavy, high stiffness metal flexures, which are subject to heavy noises and damages vibrations and shocks.  Instead of measuring the forces through the load paths, we sample the stresses within a compliant footpad using an array of piezoresistive sensors completely embedded in a protective polyurethane rubber layer. We then use a combination of linear and nonlinear regression to deduce the normal and shear forces that led to this stress distribution [2]. This approach allows the force sensing shoes without increasing the weight of the shoes or changing the properties of the original shoes.

These multi-axis force sensors can then be used to create force sensing smart shoes can be as comfortable as regular shoes, as the main material used to make these force sensors are elastomers with similar stiffness to the ethylene-vinyl acetate (EVA) foam used in manufacturing most footwear. These force sensing smart shoes can be used to help:

  • Elderly to detect neurologic gait abnormalities, and facilitate earlier treatment for dementia, etc. Research has shown that there are clear differences between the gait of normal people and people suffering from neurological disorders [3].
  • Disabled people for fall prevention and mitigation, when moving about with prosthetics or exoskeletons
  • Athletes to collect data during trainings to better optimize their workouts.
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