Automated guidance from physiological sensing to reduce thermal-work strain levels on a novel task

This experiment demonstrated that automated pace guidance generated from real-time physiological monitoring allowed less stressful completion of a timed (60 minute limit) 5 mile treadmill exercise. An optimal pacing policy was estimated from a Markov decision process that balanced the goals of the movement task and the thermal-work strain safety constraints. The machine guided pace was based on current physiological strain index (PSI), the time, and the distance already completed. Fourteen healthy and fit young subjects participated in the study (9 men, 5 women). Each participated in an unguided exercise session followed by a guided one. In the unguided session, they were instructed to complete 5 miles in 60 minutes and to try to finish at the lowest body temperature possible; in the guided sessions, participants were instructed to match machine-provided pacing guidance provided every 2 minutes. Continuous real-time measures of heart rate and core body temperature were obtained from a wearable Hidalgo EquivitalTM EQ-02 and the MiniMitter Jonah thermometer pill. Of the fourteen subjects, 13 completed the 5 miles in one hour for the unguided session; at least three different self-pacing strategies were observed, with an alternating speed proving to be most effective. In the guided sessions, 6 subjects were stopped by the machine guidance for exceeding the algorithms PSI “safety” limit. Eight subjects were guided to complete the task with significantly lower PSIs. The results indicate that machine guided advice shows promise for preventing hyperthermia and improving outcomes for performers of an unfamiliar task.