  This paper presents our findings from a multi-year effort to detect motion
events early using inertial sensors in real-world settings. We believe early
event detection is the next step in advancing motion tracking, and can enable
just-in-time interventions, particularly for mHealth applications. Our system
targets strength training workouts in the fitness domain, where users perform
well-defined movements for each exercise, while wearing an inertial sensor. We
collect data for 20 exercises across 12 users over 26 months. We propose an
algorithm to detect repetitions before they end, to allow a user to visualize
movement derived metrics in real-time. We further develop a gamified approach
to display this information to the user and encourage them to perform
consistent movements. Participants in a feasibility study find the gamified
feedback useful in improving their form. Our system can detect repetition
events as early as 500 ms before it ends, which is 2x faster and more accurate
than state-of-the-art trackers. We believe our approach will open exciting
avenues for tracking, detection, and gamification for fitness frameworks.
