Multimodal Sensing Prototype, 2025
Team 2 person Collaboration
Format Wearable Sensing Prototype
Tools Arduino,GSR/EMG,Python,TensorFlow
Year 2025
OVERVIEW
The Body Knows explores whether physiological signals can reveal differences between spontaneous and deliberately controlled behaviour. I developed a multimodal wearable sensing prototype using GSR and EMG sensors to capture skin conductance, large-muscle activity and subtle forearm muscle responses. These signals were compared to identify patterns of natural fluctuation and deliberate control within a forensic assessment context. The system combines Arduino-based sensing, real-time serial data capture, signal processing, and exploratory machine learning using Python and TensorFlow.
CONCEPT & SYSTEM
Can multimodal physiological signals reveal inconsistencies between spontaneous and intentionally controlled responses?
The project explores whether changes in skin conductance and muscle activity can help distinguish natural physiological responses from deliberately controlled behaviour, with the aim of identifying differences between genuine psychiatric symptoms and simulated behaviour in forensic assessment.
PROTOTYPE & DATA
Tracks skin conductance and autonomic arousal through the fingers.
Upper-arm EMG
Measures large-muscle contraction and involuntary tension.
Measures large-muscle contraction and involuntary tension.
Forearm EMG
Captures subtle hand and forearm muscle activity for fine-response analysis.
01 Sensor Testing
Hardware integration, Arduino and sensor testing
02 Raw Data Capture
Real-time GSR and EMG signals via serial communication
03 Machine Learning
Feature extraction and exploratory classification with Python
and TensorFlow
ANALYSIS & REFLECTION
The Body Knows brings wearable sensing, physiological data and machine learning into one experimental system, exploring how bodily responses can become another layer of information alongside observable behaviour.