Advanced Training Programme in Biological Sciences


Image of a student conducting neurobioengineering research

Monday 27 – Friday 31 July 2020


In this course you will learn about tools and techniques that support research at the systems level and its application to design and development of prosthetics and assistive tools like exoskeletons. As an example, you will use hands-on development of a single-joint mechanical arm driven by muscle EMG/s. To evaluate the best way to make the arm reproduce the natural activity of the elbow, you will apply different data processing and coding tools.

Practical content

  • Breadboard assembly and testing (oscilloscopes).
  • Basics of electrical and electronics (Ohms law, impedance, etc).
  • Simple signal modulation (filters, amplifiers and transformations).
  • Simple 'arduino duo' coding tutorials (online resources, made available prior to arrival).
  • EMG recordings from 2 muscles.
  • EMG recording, making sense of these recordings in time and frequency domains.
  • Statistical methods for analysing the data collected.
  • Segmenting and classifying samples into different clusters.
  • Design and operate a single joint robotic arm using your own EMGs.
  • Design a 2 joint robotic arm.
  • Design a threshold finding script and classification tool for up to 4 EMG channels (AD, PD, BB, LT - Upper arm).
  • Use classifier and threshold function to map the inputs of the EMG channels to the 2 joint robotic arm.

Learning outcomes

On completing this course you should:

  • Understand basic physiology and concepts on muscle activity and its control.
  • Know how to obtain meaningful muscle response or signal and make sense of it, use these signals to drive the motors (arm), thus needs to be linked to your future experimental planning.
  • Be able to design effective experiments for recording the EMGs from more than one muscle in non-clinical environments and use it to drive a single- and double-jointed model arms.
  • Be competent in the generation of codes for analysing the EMGs in both time and frequency domains.
  • Be able to design and execute experiments to evaluate the relative influence of the time and frequency components of EMG for control of the model arms.
  • Be able to design and execute experiments to produce movement of the model arm that is the closest replication of the real activity.

Course structure

You will work in small teams to conduct your own experiments and collect data, under the guidance of a team of experienced teachers. At the end of the course, we will bring together to compare notes and evaluate the designed arm/s. There is no formal assessment and not limits imposed on what you can make if it is a working model.

Who would benefit from this week?

  • Graduates from scientific disciplines outside the molecular/cellular biosciences looking to develop competencies in these areas.
  • Recent graduates preparing to undertake Masters-level training with a significant research component.
  • Recent graduates with limited practical biosciences experience wishing to increase their competitiveness for research degree (PhD) programmes.
  • Undergraduate students approaching their final year of study, in particular those preparing for research projects.

Fees and funding

Programme fee: £750 per week payable to the University of Leeds prior to the course starting.  This fee includes tuition costs, consumables for the practical sessions and lunch during the teaching day. It does not include costs for accommodation or any living expenses.

If you’re unsure about the application process, contact or +44 (0) 113 343 3021.

How to apply

Applications for 2020 are now open!

All applications for the Advanced Training Programmes must be made online. The application deadline for the Advanced Training Programmes is 4pm on May 6 2020.

We recommend that you apply as soon as possible as enrolment is limited and allocated on a first-come first-served basis. Applying early also means you are more likely to secure a place on your first choice of course as popular subjects are likely to fill up quickly.

Submit your application.

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