Thumbs-Up

Thumbs-Up explores a novel sensing method for detection of hand-to-mouth compulsive habits. Using electrical bio-impedance spectroscopy and inertial measurement units, a prototype system was implemented. The system can easily be worn around the arm and may perhaps be integrated into future wearable devices. It recognises occurrences of the habits in real-time, allowing monitoring and immediate interventions. These have so far been very limited, impeding behavioural studies and the development of therapeutic treatments. Throughout this paper the method’s feasibility is demonstrated and aspects of its performance are explored. We present an approach to process the bio-impedance signals and associate them with possible body postures. A positioning strategy optimises the device’s sensitivity and increases its efficacy. Machine learning algorithms are leveraged to infer the hand-to-mouth detection. We achieve 92% detection accuracy for recurrent usage and 90% accuracy for users that have not been previously encountered.