Bodyinformed

Bodyinformed is a design and analysis concept describing systems that use information derived from the human body's signals to inform decisions, interfaces, or adaptive behavior. It emphasizes that bodily states—not just user input or explicit commands—can guide how information is presented or how tasks are supported.

The idea draws on embodied cognition, affective computing, and biosignal research. In practice, bodyinformed design may combine physiological data (such as heart rate and heart rate variability, skin conductance, and respiration), movement data (posture, gait, pose), and gaze or other sensor outputs to estimate conditions like fatigue, stress, arousal, or attention.

Applications include adaptive user interfaces, health and wellness devices, ergonomic advisories, education tools, and gaming, where system behavior adjusts to the user’s current bodily state to improve usability, safety, or learning outcomes.

Methods involve data collection from wearables, cameras, EMG, EEG, or other sensors; data fusion and interpretation through machine learning; privacy and consent frameworks; and user testing to ensure alignment with user intent and comfort.

Criticism and challenges include concerns about privacy and data ownership, potential biases, accuracy of inferences from physiological signals, interpretability, and the risk of overreliance on bodily data for decisions that require contextual understanding. The term remains not yet standardized and is used variably across disciplines.

See also: embodied cognition; affective computing; biosignals; human-centered AI.