Mirror, Mirror On the Wall, Am I Healthy After All: Device Connectivity
Fairy tales and science fiction stories often pave the way to real world technology. Magic mirrors have been used in Snow White and Harry Potter’s world. Now you can get one, too – manufactured by a Hong Kong company James Law Cybertecture International.
What other health metrics could be performed by the mirror during your regular morning hygiene routine? If a camera can measure minute changes in the color of your face to determine your heart rate, it could also measure your facial expressions and emotions or perform observational analysis – the first of four methods of diagnosis performed by traditional Chinese medicine.
Prototypes for computerized facial diagnostic systems already have been developed. One recent study, for example, (Li et al 2012) analyzes lips. The software segments lips from the rest of the face and extracts color, texture and shape features. Special supervised learning algorithms are then able to classify lips as deep-red, purple, red or pale and make inferences related to energy levels and circulation.
Health management applications will not be limited to smartphones or smart homes. All objects in our lives will gradually become “smarter.” Mobile phones can already manage vacuum cleaners and thermostats. Refrigerators can tweet, check Google calendars, download recipes, play tunes and alert us about food spoilage. Mirrors can monitor our weight and exercise.
Poh MZ, McDuff DJ, & Picard RW (2010). Non-contact, automated cardiac pulse measurements using video imaging and blind source separation. Optics express, 18 (10), 10762-74 PMID: 20588929
Li F, Zhao C, Xia Z, Wang Y, Zhou X, & Li GZ (2012). Computer-assisted lip diagnosis on traditional Chinese medicine using multi-class support vector machines. BMC complementary and alternative medicine, 12 (1) PMID: 22898352
Littlewort, G., Whitehill, J., Wu, T., Fasel, I.R., Frank, M., Movellan, J.R., Bartlett, M.S. (2011) The Computer Expression Recognition Toolbox (CERT). Proceedings of the 9th IEEE Conference on Automatic Face and Gesture Recognition.