Simple statistical inference algorithms for task-dependent wellness assessment.

Stress is a key indicator of wellness in human beings and a prime contributor to performance degradation and errors during various human tasks. The overriding purpose of this paper is to propose two algorithms (probabilistic and non-probabilistic) that iteratively track stress states to compute a wellness index in terms of the stress levels. This paper adopts the physiological view-point that high stress is accompanied with large deviations in biometrics such as body temperature, heart rate, etc.