  Personalized Active Learner (PAL) is a wearable system for real-time,
personalized, and context-aware health and cognition support. PAL's system
consists of a wearable device, mobile app, cloud database, data visualization
web app, and machine learning server. PAL's wearable device uses multi-modal
sensors (camera, microphone, heart-rate) with on-device machine learning and
open-ear audio output to provide real-time and context-aware cognitive,
behavioral and psychological interventions. PAL also allows users to track the
long-term correlations between their activities and physiological states to
make well-informed lifestyle decisions. In this paper, we present and
open-source PAL's system so that people can use it for health and cognition
support applications. We also open-source three fully-developed example
applications using PAL for face-based memory augmentation, contextual language
learning, and heart-rate-based psychological support. PAL's flexible, modular
and extensible platform combines trends in data-driven medicine, mobile
psychology, and cognitive enhancement to support data-driven and empowering
health and cognition applications.
