Three custom TENG sensors integrated into eyeglasses capture arterial pulse, jaw kinematics, and facial activity at 4.1 µW total front-end power, achieving 93.8% activity accuracy and 1.82 BPM heart rate error in a 20-participant study.
Title resolution pending
2 Pith papers cite this work, alongside 2 external citations. Polarity classification is still indexing.
2
Pith papers citing it
2
external citations · external index
years
2026 2representative citing papers
LLMs can infer individual domain knowledge from Slack logs with best MAE of 21.13% using Gemini 2.5 Flash, though performance varies by model and shows weak dependence on message volume.
citing papers explorer
-
GlassTENG: Self-Powered Triboelectric Nanogenerator based Sensing of Pulse, Jaw, and Upper Facial Activity from Everyday Glasses
Three custom TENG sensors integrated into eyeglasses capture arterial pulse, jaw kinematics, and facial activity at 4.1 µW total front-end power, achieving 93.8% activity accuracy and 1.82 BPM heart rate error in a 20-participant study.
-
Can AI Guess What You Know? Performance Comparison of Large Language Models for Human Domain Knowledge Estimation From Communication Logs
LLMs can infer individual domain knowledge from Slack logs with best MAE of 21.13% using Gemini 2.5 Flash, though performance varies by model and shows weak dependence on message volume.