Loose Clothing Enhances Human Motion Prediction

Researchers in a Nature Communications paper report that sensor-embedded loose-fitting clothing can recognize and predict human motion more accurately than rigidly attached sensors in laboratory experiments. Across mechanical, robotic, and human reaching tasks (22 participants), fabric-mounted sensors increased recognition accuracy by up to 40% and reduced required past-history by about 80%, though results derive mainly from controlled settings.