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UnitGrades 10 - 12

Neural Engineering in Action: Exploring Muscle Movement Through Data and Design

A photo showing students working in a group recording and observing EMG data on their computer in class.Students try to explore muscle movements to see if their actions reflect in the software application.

The first activity introduces foundational neuroscience concepts, including neurons, synapses, and the pathways connecting neurons to muscles. Students use a micro:bit to interact with a simulated “beating heart” and observe how the rate of wrist or finger movements affects the animation. They are also encouraged to create their own animations. An optional extension introduces students to basic electromyography (EMG) recording. By the end of this activity, students will have gained introductory experience with neurobiology and microcontroller-based data collection.

In the second activity, students bridge neuroscience and engineering by designing an experimental protocol to collect EMG signals during a variety of hand movements—similar to those used in robotics and neuroprosthetics. Using surface electrodes and a dedicated microcontroller, they collect and visualize EMG signals, comparing coarse and fine motor movements. Through this process, students are introduced to both the engineering design process and the scientific method as they collect and analyze data to investigate how neural signals control muscle activity.

The third activity focuses on data transformation and organization. Students convert previously collected EMG recordings (in .wav format) into .csv files using Python libraries in Google Colab. They learn how to sample and clean the data for efficient visualization and analysis, building a collaborative dataset for class use.

In the final activity, students apply their data science skills to visualize EMG data using the graphics.py Python library. Working collaboratively, they analyze trends in neural activation and muscle movement, draw conclusions, and communicate their findings in a written report using a structured template.

This unit provides a rich, hands-on experience that highlights real-world applications of engineering in neuroscience—from brain-machine interfaces to prosthetics. It empowers students to explore how the brain and muscles work together and how engineers use data, coding, and design to model and support human movement.

Neuroengineers and biomedical engineers are at the forefront of adapting and reverse-engineering natural processes in the human body to better understand and address physiological challenges. As technologies such as artificial intelligence become more deeply embedded in healthcare, their work is increasingly essential to advancing medical diagnostics, treatments, and assistive devices.

Neuroengineers focus specifically on the nervous system—designing brain-computer interfaces, developing neuroprosthetics that restore lost movement, and creating systems for deep brain stimulation to treat neurological disorders. Their work bridges neuroscience and engineering, helping to decode how neural signals control muscles and movement.

Biomedical engineers design medical technologies that replicate or enhance the body’s natural functions. This includes creating artificial limbs with sensors that mimic muscle activity, as well as developing tools such as pacemakers, hearing aids, imaging systems, and surgical robotics. A strong understanding of the muscular and nervous systems is critical to designing solutions that respond effectively to the body’s complex signals.

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