Prediction of mortality based on facial characteristics

Recent studies have shown that characteristics of the face contain a wealth of information about health, age and chronic clinical conditions. Such studies involve objective measurement of facial features correlated with historical health information. But some individuals also claim to be adept at g...

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Bibliographic Details
Main Authors: Arnaud Delorme, Alan Pierce, Leena Michel, Dean Radin
Format: Article
Language:English
Published: Frontiers Media S.A. 2016-05-01
Series:Frontiers in Human Neuroscience
Subjects:
EEG
Online Access:http://journal.frontiersin.org/Journal/10.3389/fnhum.2016.00173/full
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spelling doaj-b0d4040530b448cfafcdd567f19fbb652020-11-25T03:03:16ZengFrontiers Media S.A.Frontiers in Human Neuroscience1662-51612016-05-011010.3389/fnhum.2016.00173180186Prediction of mortality based on facial characteristicsArnaud Delorme0Arnaud Delorme1Alan Pierce2Leena Michel3Dean Radin4University of California San DiegoInstitute of Noetic SciencesInstitute of Noetic SciencesInstitute of Noetic SciencesInstitute of Noetic SciencesRecent studies have shown that characteristics of the face contain a wealth of information about health, age and chronic clinical conditions. Such studies involve objective measurement of facial features correlated with historical health information. But some individuals also claim to be adept at gauging mortality based on a glance at a person’s photograph. To test this claim, we invited 12 such individuals to see if they could determine if a person was alive or dead based solely on a brief examination of facial photographs. All photos used in the experiment were transformed into a uniform gray scale and then counterbalanced across eight categories: gender, age, gaze direction, glasses, head position, smile, hair color, and image resolution. Participants examined 404 photographs displayed on a computer monitor, one photo at a time, each shown for a maximum of 8 seconds. Half of the individuals in the photos were deceased, and half were alive at the time the experiment was conducted. Participants were asked to press a button if they thought the person in a photo was living or deceased. Overall mean accuracy on this task was 53.8%, where 50% was expected by chance (p < 0.004, two-tail). Statistically significant accuracy was independently obtained in 5 of the 12 participants. We also collected 32-channel electrophysiological recordings and observed a robust difference between images of deceased individuals correctly vs. incorrectly classified in the early event related potential at 100 ms post-stimulus onset. Our results support claims of individuals who report that some as-yet unknown features of the face predict mortality. The results are also compatible with claims about clairvoyance and warrants further investigation.http://journal.frontiersin.org/Journal/10.3389/fnhum.2016.00173/fullFaceIntuitionMortalityEEGreading
collection DOAJ
language English
format Article
sources DOAJ
author Arnaud Delorme
Arnaud Delorme
Alan Pierce
Leena Michel
Dean Radin
spellingShingle Arnaud Delorme
Arnaud Delorme
Alan Pierce
Leena Michel
Dean Radin
Prediction of mortality based on facial characteristics
Frontiers in Human Neuroscience
Face
Intuition
Mortality
EEG
reading
author_facet Arnaud Delorme
Arnaud Delorme
Alan Pierce
Leena Michel
Dean Radin
author_sort Arnaud Delorme
title Prediction of mortality based on facial characteristics
title_short Prediction of mortality based on facial characteristics
title_full Prediction of mortality based on facial characteristics
title_fullStr Prediction of mortality based on facial characteristics
title_full_unstemmed Prediction of mortality based on facial characteristics
title_sort prediction of mortality based on facial characteristics
publisher Frontiers Media S.A.
series Frontiers in Human Neuroscience
issn 1662-5161
publishDate 2016-05-01
description Recent studies have shown that characteristics of the face contain a wealth of information about health, age and chronic clinical conditions. Such studies involve objective measurement of facial features correlated with historical health information. But some individuals also claim to be adept at gauging mortality based on a glance at a person’s photograph. To test this claim, we invited 12 such individuals to see if they could determine if a person was alive or dead based solely on a brief examination of facial photographs. All photos used in the experiment were transformed into a uniform gray scale and then counterbalanced across eight categories: gender, age, gaze direction, glasses, head position, smile, hair color, and image resolution. Participants examined 404 photographs displayed on a computer monitor, one photo at a time, each shown for a maximum of 8 seconds. Half of the individuals in the photos were deceased, and half were alive at the time the experiment was conducted. Participants were asked to press a button if they thought the person in a photo was living or deceased. Overall mean accuracy on this task was 53.8%, where 50% was expected by chance (p < 0.004, two-tail). Statistically significant accuracy was independently obtained in 5 of the 12 participants. We also collected 32-channel electrophysiological recordings and observed a robust difference between images of deceased individuals correctly vs. incorrectly classified in the early event related potential at 100 ms post-stimulus onset. Our results support claims of individuals who report that some as-yet unknown features of the face predict mortality. The results are also compatible with claims about clairvoyance and warrants further investigation.
topic Face
Intuition
Mortality
EEG
reading
url http://journal.frontiersin.org/Journal/10.3389/fnhum.2016.00173/full
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