Wearable-Machine Interface Architectures for Mental Stress

The human body responds to neurocognitive stress in multiple ways through its autonomic nervous system. Changes in skin conductance measurements indicate sudomotor nerve activity, and can be used to infer the underlying autonomic nervous system stimulation. We model skin conductance measurements using a state-space model with sparse impulsive events as inputs. Next, we recover the timing and amplitudes of this spiking neural activity using a generalized cross-validation based sparse recovery approach. Finally, we relate stress to the probability that a neural spike occurs in a skin conductance signal to continuously track a subject’s stress level. Results demonstrate a promising approach for tracking stress through wearable devices.