Decoding Muscle Movement: Analyzing Neuromuscular Signals With EMG
EMG signals visualized on a PC using the Spike Recorder application which can turn a PC into a high-tech data recording and analysis tool.Copyright Ashwin Mohan
In this second activity, students dive deeper into the neuromuscular system by exploring how the body recruits and activates muscles in response to various gestures. They begin by examining the neuromuscular junction and diagramming the neuronal circuitry pathway involved in muscle activation. Using electromyography (EMG), students learn how to measure subtle muscle responses triggered by wrist and finger movements. They collect and analyze EMG data with the help of surface electrodes and computer software, focusing on recording and processing signals from both large and small muscle groups at different speeds. By practicing data acquisition, filtering, and signal analysis, students apply the scientific method and engineering design process to understand how neurons interact with muscles. As they work in teams to compare signal parameters such as amplitude and frequency, they gain valuable insights into muscle recruitment and learn to distinguish between different types of gestures based on their EMG data. This activity reinforces students' understanding of neuromuscular function while enhancing their skills in data collection and analysis.
EMG technology draws on multiple engineering disciplines. Biomedical engineers develop and refine EMG sensors and signal processing methods. Electrical engineers design circuits and systems to acquire, filter, and interpret muscle signals. Mechanical engineers study muscle biomechanics to guide sensor placement and understand force dynamics. Computer engineers create software and algorithms—often using machine learning—for data analysis and gesture recognition. Neuroengineers, a branch of biomedical engineering, focus on neuron-muscle interactions to optimize EMG for medical, prosthetic, and rehab applications. Together, these disciplines drive EMG innovation across healthcare, robotics, and human-computer interaction.
After this activity, students should be able to:
- Describe muscle physiology and neuron/muscle communication using electromyograms (EMG), specifically explain EMG signal property changes between large and fine muscle.
- Acquire and analyze biological data to make valid and reliable scientific observations.
- Discuss, hypothesize, and suggest other experiments based on learning from these EMG studies (e.g., carpal tunnel syndrome, Parkinson’s to robotic/neuroprosthetic applications).