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Face touch monitoring using an instrumented wristband using dynamic time warping and k-nearest neighbours
by
Ho, Chester
, Phan, Steven
, Rouhani, Hossein
, Fathian, Ramin
in
Accelerometers
/ Accuracy
/ Biology and Life Sciences
/ Cameras
/ Communicable diseases
/ Coronaviruses
/ COVID-19
/ COVID-19 - prevention & control
/ Disease control
/ Disease transmission
/ Electromyography
/ Engineering and Technology
/ Experiments
/ Face
/ Hand
/ Hand (anatomy)
/ Humans
/ Hygiene
/ Inertial platforms
/ Infections
/ Infectious diseases
/ K nearest neighbour classification tree analysis
/ K-nearest neighbors algorithm
/ Machine learning
/ Medicine and Health Sciences
/ Methods
/ Monitoring systems
/ Natural environment
/ Neural networks
/ Physical Sciences
/ Prevention
/ Risk factors
/ Sensors
/ Smartwatches
/ Social Sciences
/ Tactile stimuli
/ Technology
/ Touch
/ Touch Perception
/ Ultrasonic imaging
/ Warping
/ Wearable computers
/ Wrist
2023
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Face touch monitoring using an instrumented wristband using dynamic time warping and k-nearest neighbours
by
Ho, Chester
, Phan, Steven
, Rouhani, Hossein
, Fathian, Ramin
in
Accelerometers
/ Accuracy
/ Biology and Life Sciences
/ Cameras
/ Communicable diseases
/ Coronaviruses
/ COVID-19
/ COVID-19 - prevention & control
/ Disease control
/ Disease transmission
/ Electromyography
/ Engineering and Technology
/ Experiments
/ Face
/ Hand
/ Hand (anatomy)
/ Humans
/ Hygiene
/ Inertial platforms
/ Infections
/ Infectious diseases
/ K nearest neighbour classification tree analysis
/ K-nearest neighbors algorithm
/ Machine learning
/ Medicine and Health Sciences
/ Methods
/ Monitoring systems
/ Natural environment
/ Neural networks
/ Physical Sciences
/ Prevention
/ Risk factors
/ Sensors
/ Smartwatches
/ Social Sciences
/ Tactile stimuli
/ Technology
/ Touch
/ Touch Perception
/ Ultrasonic imaging
/ Warping
/ Wearable computers
/ Wrist
2023
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Face touch monitoring using an instrumented wristband using dynamic time warping and k-nearest neighbours
by
Ho, Chester
, Phan, Steven
, Rouhani, Hossein
, Fathian, Ramin
in
Accelerometers
/ Accuracy
/ Biology and Life Sciences
/ Cameras
/ Communicable diseases
/ Coronaviruses
/ COVID-19
/ COVID-19 - prevention & control
/ Disease control
/ Disease transmission
/ Electromyography
/ Engineering and Technology
/ Experiments
/ Face
/ Hand
/ Hand (anatomy)
/ Humans
/ Hygiene
/ Inertial platforms
/ Infections
/ Infectious diseases
/ K nearest neighbour classification tree analysis
/ K-nearest neighbors algorithm
/ Machine learning
/ Medicine and Health Sciences
/ Methods
/ Monitoring systems
/ Natural environment
/ Neural networks
/ Physical Sciences
/ Prevention
/ Risk factors
/ Sensors
/ Smartwatches
/ Social Sciences
/ Tactile stimuli
/ Technology
/ Touch
/ Touch Perception
/ Ultrasonic imaging
/ Warping
/ Wearable computers
/ Wrist
2023
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Face touch monitoring using an instrumented wristband using dynamic time warping and k-nearest neighbours
Journal Article
Face touch monitoring using an instrumented wristband using dynamic time warping and k-nearest neighbours
2023
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Overview
One of the main factors in controlling infectious diseases such as COVID-19 is to prevent touching preoral and prenasal regions. Face touching is a habitual behaviour that occurs frequently. Studies showed that people touch their faces 23 times per hour on average. A contaminated hand could transmit the infection to the body by a facial touch. Since controlling this spontaneous habit is not easy, this study aimed to develop and validate a technology to detect and monitor face touch using dynamic time warping (DTW) and KNN (k-nearest neighbours) based on a wrist-mounted inertial measurement unit (IMU) in a controlled environment and natural environment trials. For this purpose, eleven volunteers were recruited and their hand motions were recorded in controlled and natural environment trials using a wrist-mounted IMU. Then the sensitivity, precision, and accuracy of our developed technology in detecting the face touch were evaluated. It was observed that the sensitivity, precision, and accuracy of the DTW-KNN classifier were 91%, 97%, and 85% in controlled environment trials and 79%, 92%, and 79% in natural environment trials (daily life). In conclusion, a wrist-mounted IMU, widely available in smartwatches, could detect the face touch with high sensitivity, precision, and accuracy and can be used as an ambulatory system to detect and monitor face touching as a high-risk habit in daily life.
Publisher
Public Library of Science,Public Library of Science (PLoS)
Subject
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