Wearable Robotics
Wearable Robotics (IBIO 3172 – IMEC 3528) is a joint elective course from the Biomedical and Mechanical Engineering departments at Universidad de los Andes. It covers the analysis, modeling, simulation and design of wearable robotic systems oriented to human–machine interaction: exoskeletons, prosthetics, orthoses and motor-assistance devices.
The course builds a common theoretical foundation in biomechanics, human movement, ergonomics and the fundamentals of assistive systems. From there, each student carries out applied work following their profile of interest, either in modeling or in design, while keeping a unified conceptual framework. Wearable robotics is also one of the lab's research lines: projects such as the elbow exoskeleton stem from this interaction between biomechanics and actuation.
Learning objectives
By the end of the course, students will be able to:
- Analyze human movement from a quantitative biomechanical perspective.
- Model or design a wearable robotic system coupled to the human body.
- Integrate ergonomics, safety and functional performance criteria.
- Simulate or implement control strategies for motor assistance.
- Make design decisions based on biomechanical data.
Course content
Module 1 — Biomechanics and human movement
Introduction to wearable robotics and its applications, the human–robot system, kinematics of human movement (levers), biomechanical sensors and gait biomechanics.
Anatomical reference planes for human movement analysis.
The study of gait relies on locomotion datasets and motion capture to identify its phases and associated functional movements.
Phases of the human gait cycle.
Module 2 — Musculoskeletal modeling
Basic data handling in Python, signal interpretation and musculoskeletal modeling with tools such as OpenSim, OpenCap and MyoSuite, including Hill's musculotendon model and the dynamics of human movement.
Hill model: contractile element in series with elastic elements.
Module 3 — Actuation and control
Actuators for wearable systems, servo control applied to motor assistance and impedance control, with hands-on activities combining Arduino and MuJoCo simulation.
Closed control loop for motor assistance.
Module 4 — Device design
Orthoses and exoskeletons, body integration, ergonomics and human–device coupling, signal-driven design, assistance strategies, and human–robot safety with force limits and clinical and ethical considerations.
Hip Exo. Main components and lab setup
Final project
During the final weeks, students develop a profile-based applied project (simulation or design) with technical mentoring, intermediate deliverables and a final demonstration.
Methodology
- Lectures with prior reading of each topic.
- Workshops every 2-3 weeks: one on biomechanics and one on actuation, each graded in two parts.
- Semester-long project with initial, intermediate and final deliverables plus a final defense.
Software
- Python (NumPy, SciPy, Matplotlib, Pandas) — processing of data and biomechanical signals
- MyoSuite, MuJoCo, OpenCap/OpenSim — musculoskeletal and actuation simulation
- Arduino — servo control implementation
- Autodesk Inventor — CAD and wearable device design
References
- Perry, J. Gait Analysis: Normal and Pathological Function. SLACK, 1992.
- Nordin, M., Frankel, V. H. Basic Biomechanics of the Musculoskeletal System. 3rd Ed., McGraw Hill.
- Hall, S. Basic Biomechanics. 7th Ed., McGraw Hill.
- Hughes, A., Drury, W. Electric Motors and Drives: Fundamentals, Types and Applications. Elsevier, 2013.
- Smith, S. W. The Scientist and Engineer's Guide to Digital Signal Processing, 1997.
- Hibbeler, R. C. Mechanical Engineering: Dynamics. 12th Ed., Prentice Hall.
- Norton, R. Design of Machinery. McGraw Hill, 2005.